Добірка наукової літератури з теми "Thermal energy demand forecast"

Under the “carbon peaking and carbon neutrality” goal, Shanxi Province adjusts the power supply structure and promotes the development of a high proportion of new energy, which has a certain impact on the demand for thermal coal. Therefore, constructing a reasonable forecasting model for thermal coal demand can play a role in stabilizing coal supply and demand. This paper analyzes various factors related to coal demand, and uses Pearson coefficient to screen out six variables with strong correlation. Then, based on the scenario analysis method, combined with the “14th Five-Year Plan” of Shanxi Province, different scenarios of economic development and carbon emission reduction development are set. Finally, a multi-scenario GA–LSSVM forecasting model of thermal coal demand in Shanxi Province is constructed, and the future development trend of thermal coal demand in Shanxi Province is predicted. The results show that the demand for thermal coal is the largest in the mode of high-speed economic development and low emission reduction, and the demand for thermal coal is the lowest in the mode of low-speed economic development and strong emission reduction, which provides a scientific basis for the implementation of Shanxi Province’s thermal coal supply policy.

The use of Building Energy Models (BEM) has become widespread to reduce building energy consumption. Projection of the model in the future to know how different consumption strategies can be evaluated is one of the main applications of BEM. Many energy management optimization strategies can be used and, among others, model predictive control (MPC) has become very popular nowadays. When using models for predicting the future, we have to assume certain errors that come from uncertainty parameters. One of these uncertainties is the weather forecast needed to predict the building behavior in the near future. This paper proposes a methodology for quantifying the impact of the error generated by the weather forecast in the building’s indoor climate conditions and energy demand. The objective is to estimate the error introduced by the weather forecast in the load forecasting to have more precise predicted data. The methodology employed site-specific, near-future forecast weather data obtained through online open access Application Programming Interfaces (APIs). The weather forecast providers supply forecasts up to 10 days ahead of key weather parameters such as outdoor temperature, relative humidity, wind speed and wind direction. This approach uses calibrated EnergyPlus models to foresee the errors in the indoor thermal behavior and energy demand caused by the increasing day-ahead weather forecasts. A case study investigated the impact of using up to 7-day weather forecasts on mean indoor temperature and energy demand predictions in a building located in Pamplona, Spain. The main novel concepts in this paper are: first, the characterization of the weather forecast error for a specific weather data provider and location and its effect in the building’s load prediction. The error is calculated based on recorded hourly data so the results are provided on an hourly basis, avoiding the cancel out effect when a wider period of time is analyzed. The second is the classification and analysis of the data hour-by-hour to provide an estimate error for each hour of the day generating a map of hourly errors. This application becomes necessary when the building takes part in the day-ahead programs such as demand response or flexibility strategies, where the predicted hourly load must be provided to the grid in advance. The methodology developed in this paper can be extrapolated to any weather forecast provider, location or building.

The article presents a projection of Ukraine economy development up to 2040 according to the baseline scenario, taking into account the changes that have occurred during 2017-2020. Using the projection, a preliminary estimate of the forecasted demand for electricity at the national level (TOP-DOWN method) for 2040 was developed, which taking into account a new national thermal power production structure including structure of coal-fired power plants according to the NPC “Ukrenergo” 2020 Adequacy Report. Based on these data, the forecast for fuel demand in the country including coal for 2040 is developed, which takes into account consolidated economic activities, changes in household sector, the potential of energy savings from structural changes and technological changes. Also, the forecast of fuel and coal use for transformation in industrial technological processes and in power plants are calculated. The study shows that fuel consumption in the country is significantly influenced by two factors: the structure of the economy and the structure of generating capacity for electricity and heat. Reducing the share of fossil fuels in electricity generation leads to almost constant consumption. The structural potential for energy savings is almost 50% of the total. Keywords: forecast, demand, fuel, coal, structure of economy, technological potential of energy saving, method

The high penetration rate of renewable energy sources (RESs) in smart energy systems has both threat and opportunity consequences. On the positive side, it is inevitable that RESs are beneficial with respect to conventional energy resources from the environmental aspects. On the negative side, the RESs are a great source of uncertainty, which will make challenges for the system operators to cope with. To tackle the issues of the negative side, there are several methods to deal with intermittent RESs, such as electrical and thermal energy storage systems (TESSs). In fact, pairing RESs to electrical energy storage systems (ESSs) has favorable economic opportunities for the facility owners and power grid operators (PGO), simultaneously. Moreover, the application of demand-side management approaches, such as demand response programs (DRPs) on flexible loads, specifically thermal loads, is an effective solution through the system operation. To this end, in this work, an air conditioning system (A/C system) with a TESS has been studied as a way of volatility compensation of the wind farm forecast-errors (WFFEs). Additionally, the WFFEs are investigated from multiple visions to assist the dispatch of the storage facilities. The operation design is presented for the A/C systems in both day-ahead and real-time operations based on the specifications of WFFEs. Analyzing the output results, the main aims of the work, in terms of applying DRPs and make-up of WFFEs to the scheduling of A/C system and TESS, will be evaluated. The dispatched cooling and base loads show the superiority of the proposed method, which has a smoother curve compared to the original curve. Further, the WFFEs application has proved and demonstrated a way better function than the other uncertainty management techniques by committing and compensating the forecast errors of cooling loads.

THE PURPOSE. Improving the accuracy of forecast calculations of demand for energy resources is an urgent task, especially in the light of the Digital Energy of the Russian Federation program. Prediction is also required for he at supply systems. The complexity of the analysis is the lack of confirmation of the similarity properties of energy systems and complexes for buildings with similar functionality. On the example of buildings of secondary educational institutions located i n the territory of Moscow, the assumption of heteromorphism of thermal systems is proved. METHODS. In the work, an assumption was made that there were no significant changes in the data on the heat consumption of the energy facilities of schools, which was confirmed by the absence of changes in the average annual heat consumption and jumps in the monthly heat consumption diagrams. The amount of heat energy consumption measured and transferred to the IS is influenced by a number of additional factors: accura cy drift of heat energy metering devices; aging and overgrowing of the internal surfaces of the building's heating network equipment; physical aging and deterioration of the building envelope and deterioration of their thermal insulation performance. When compiling predicted energy consumption, this means that it is permissible to use not only statistical data about the analyzed object itself, but also about a variety of objects similar to those analyzed in structure and functionality. RESULTS. A set of input factors is proposed that makes it possible to accurately determine the predicted demand for thermal energy for buildings of secondary educational institutions. The possibility and similar accuracy of the results of forecasting the demand for thermal ene rgy is shown both through the use of multivariate regression analysis and artificial neural networks. CONCLUSION. ЭBased on the combined use of various mathematical approaches, it is proposed to use the methodology for forecasting energy demand by energy complexes and systems as a mechanism for determining the correctness of the transmitted meter readings.

An increase in energy demand in the coming years is inevitable, and therefore it is necessary to provide optimal solutions for this future need. This paper examines the future energy demands of the southern regions of Iran (with a hot and dry climate and high energy needs). In this regard, the overall structure of the research has been divided into three parts. In the first part, using historical energy consumption data, the energy demand in 2030 is predicted. This is carried out utilizing a time series analysis method, namely Holt–Winters. Then, relying on the plans of the Iran Ministry of Energy, various energy plans have been designed and energy modeling has been carried out for both base and forecast years. Finally, regarding a multi-criteria decision-making approach, energy plans are ranked and the best scenarios are selected and analyzed. The results of modeling and multi-criteria analysis showed that comprehensive and simultaneous development in the construction of thermal and renewable power plants is the best option to meet future energy needs.

Abstract. Space heating is a major contributor to the average energy consumption of private households, where the energy standard of a building is a controlling parameter for its heating energy demand. Vertical Ground Source Heat Pumps (vGSHP) present one possibility for a low-emission heating solution. In this paper, we present results of building performance simulations (BPS) coupled with vGSHP simulations for modelling the response of vGSHP-fields to varying heating power demands, i.e. different building types. Based on multi-year outdoor temperature data, our simulation results show that the cooling effect of the vGSHPs in the subsurface is about 2 K lower for retrofitted buildings. Further, a layout with one borehole heat exchanger per building can be efficiently operated over a time frame of 15 years, even if the vGSHP-field layout is parallel to regional groundwater flow in the reservoir body. Due to northward groundwater flow, thermal plumes of reduced temperatures develop at each vGSHP, showing that vGSHPs in the southern part of the model affect their northern neighbors. Considering groundwater flow in designing the layout of the vGSHP-field is conclusively important. Combining realistic estimates of the energy demand of buildings by BPS with subsurface reservoir simulations thus presents a tool for monitoring and managing the temperature field of the subsurface, affected by Borehole Heat Exchanger (BHE) installations.

The use of new energy to generate electricity in the power system and the large-scale increase of new energy grid connection has led to increasingly insufficient power system regulation, in order to solve this problem, the peak shaving auxiliary service market came into being.This article comprehensively analyzes the factors those affect the market clearing price of power peak shaving auxiliary services: The macro factors include energy economic policies (renewable energy and electric energy substitution), technological innovation, market operation rules, etc., and the micro factors include the quotation and demand of thermal power plants and wind power generation.The power peak shaving auxiliary service market is an important part of the power market. Its appearance makes the grid operation safer and more reliable, and the reasonable fluctuation of clearing prices and total market costs reflects the market’s sensitivity to peak shaving resource demand.This paper uses the BP neural network model to select 31 consecutive days of peak shaving auxiliary service clearing price data in North China for prediction.

In many regions, the heat used for space heating is a basic item in the energy balance of a building and significantly affects its operating costs. The accuracy of the assessment of heat consumption in an existing building and the determination of the main components of heat loss depends to a large extent on whether the energy efficiency improvement targets set in the thermal upgrading project are achieved. A frequent problem in the case of energy calculations is the lack of complete architectural and construction documentation of the analyzed objects. Therefore, there is a need to search for methods that will be suitable for a quick technical analysis of measures taken to improve energy efficiency in existing buildings. These methods should have satisfactory results in predicting energy consumption where the input is limited, inaccurate, or uncertain. Therefore, the aim of this work was to test the usefulness of a model based on Rough Set Theory (RST) for estimating the thermal energy consumption of buildings undergoing an energy renovation. The research was carried out on a group of 109 thermally improved residential buildings, for which energy performance was based on actual energy consumption before and after thermal modernization. Specific sets of important variables characterizing the examined buildings were distinguished. The groups of variables were used to estimate energy consumption in such a way as to obtain a compromise between the effort of obtaining them and the quality of the forecast. This has allowed the construction of a prediction model that allows the use of a fast, relatively simple procedure to estimate the final energy demand rate for heating buildings.

Accurate load forecasting in buildings plays an important role for grid operators, demand response aggregators, building energy managers, owners, customers, etc. Probabilistic load forecasting (PLF) becomes essential to understand and manage the building’s energy-saving potential. This research explains a methodology to optimize the results of a PLF using a daily characterization of the load forecast. The load forecast provided by a calibrated white-box model and a real weather forecast was classified and hierarchically selected to perform a kernel density estimation (KDE) using only similar days from the database characterized quantitatively and qualitatively. A real case study is presented to show the methodology using an office building located in Pamplona, Spain. The building monitoring, both inside—thermal sensors—and outside—weather station—is key when implementing this PLF optimization technique. The results showed that thanks to this daily characterization, it is possible to optimize the accuracy of the probabilistic load forecasting, reaching values close to 100% in some cases. In addition, the methodology explained is scalable and can be used in the initial stages of its implementation, improving the values obtained daily as the database increases with the information of each new day.

La prévention du changement climatique est l'une des priorités de la politique énergétique mondiale qui vise à réduire massivement les émissions de gaz à effet de serre. Face à ces défis, il est frappant de constater que notre connaissance de la modélisation de la demande énergétique demeure imparfaite car elle repose en grande partie sur des travaux empiriques anciens et des méthodologies aujourd'hui dépassées. L'objectif scientifique de cette thèse est double : analyser quantitativement les déterminants économiques de la demande énergétique et développer de nouveaux modèles de prévision. Cette thèse est structurée en quatre chapitres. Le premier chapitre montre que la consommation de gaz naturel en France peut être prédite à l'aide d'un modèle simple utilisant seulement les informations disponibles pour les acteurs du marché. Ce chapitre prouve l'existence d'une relation à long terme entre la demande de gaz naturel et les prix des autres énergies et il fournit des estimations de leurs impacts marginaux sur les niveaux de demande observés. Le deuxième chapitre étudie empiriquement le rôle de la température dans la prévision des prix du gaz aux États-Unis. Il développe une méthodologie de construction d’un nouvel indice mensuel basé sur la température. Cet indice capture les variations de la demande résiduelle de gaz naturel en temps réel. Il est utilisé comme variable exogène supplémentaire dans des modèles structurels VAR afin d’améliorer les prévisions ; et nous montrons que ces modèles prédictifs dérivés de modèles structurels sont améliorés en s’appuyant sur des données en temps réelles (non sujettes à révision). Le troisième chapitre propose d’utiliser dans le cas du pétrole, un modèle structurel capturant les anticipations à l’aide de VAR non causaux et d’identifier correctement les réactions des variables clés du pétrole à un choc d’actualité. Le quatrième chapitre réexamine le pouvoir prédictif de la structure par terme des prix, dite « convenience yield », du pétrole et du gaz en intégrant les anticipations dans une spécification empirique, par le biais d’un VAR non causal basé sur la théorie du stockage qui fournit des prévisions de prix très compétitives dans un cadre bivarié simple
The prevention of climate change is one of the priorities of the world energy policy that aims to massively reduce greenhouse gas emissions. Faced with these challenges, it is striking to note that our knowledge of energy demand modeling remains limited because it is largely based on old empirical work and methodologies that are now dated. Therefore, the objective of our work is twofold. First, we analyze quantitatively the economic determinants of energy demand. Second, we develop new forecasting models. This thesis is structured in four chapters. The first chapter shows that natural gas consumption in France can be predicted using a simple model which only includes public information that is available to market's participants. This chapter proves the existence of a long-term relationship between demand and prices of other energies and provides estimates of their marginal impacts on observed demand levels. The second chapter empirically investigates the role of temperature in forecasting gas prices in the US. It develops a methodology to build a new monthly index based on temperature. This index captures variations in residual demand for natural gas in real time. It is used as an additional exogenous variable in structural models (VAR) to improve forecasts and we show that, in our case, predictive models derived from a structural model are enhanced relying on true real-time (not subject to revisions) data. The third chapter proposes to use, in the case of oil market, a structural model capturing expectations in a noncausal VAR framework, and to properly identify the reactions of oil key variables to supply news shock. The fourth chapter revisits the predictive power of oil and gas convenience yield by incorporating expectations into an empirical specification through non-causal VAR based on the theory of storage which delivers very competitive price predictions in a simple bivariate setting

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
Nesta dissertação é desenvolvida uma metodologia para previsão de demanda mensal de energia elétrica considerando cenários de racionamento. A metodologia usada consiste em, a partir das taxas de crescimento da série temporal, identificar e eliminar os efeitos do racionamento de energia elétrica através da aplicação de Modelos Lineares Dinâmicos. São analisadas também estruturas de intervenção nos modelos estatísticos de Box & Jenkins e Holt & Winters. Os modelos são então comparados segundo alguns critérios, basicamente no que tange à sua eficiência preditiva. Conclui-se ao final sobre a eficiência da metodologia proposta, dado a grande dificuldade para solucionar o problema a partir dos modelos estatísticos de Box & Jenkins e Holt & Winters. Esta solução é então proposta como a mais viável para criar cenários de racionamento e pósracionamento de energia para ser utilizado por agentes do sistema elétrico nacional.
In this dissertation, a methodology is developed to forecast monthly demand of electric energy, considering the rationing scenery. The methodology is based on, taking the growth rate from the time series, identify and eliminate the effects of electric energy rationing, using Dynamic Linear Models. It is also analyzed intervention structures in the statistics models of Box & Jenkins and Holt & Winters. The models are compared according to some criterions, mainly forecast accuracy. At the end, we concluded that the methodology proposed is more efficient, due to the difficult to solve the problem using the statistics models with intervention. This solution is proposed as the best among them to create scenery during the energy rationing and after energy rationing, to be used by the national electric system agents.

A smart home energy management system has been used to reshape the electricity demand of the residential buildings widely. It normally requires understanding the capability of residential buildings’ thermal mass which revisits to the temperature flatirons and providing enough energy buffers. In this project, phase change material (PCM) was used as the virtual thermal energy storage. Basically, two parts were included: thermal modelling of residential building with PCM layer. Secondly thermal behaviour of models under different conditions (heating, ventilation and air conditioning system, fenestration, solar radiation) is discussed. Some numerical methods for thermal modelling with EnergyPlus are also presented. A conduction finite difference algorithm in EnergyPlus are applied to calculate heat transfer between ambient and zone. The results indicate that PCM layers shift and decreased the indoor temperature during peak period. Also, solar radiation and fenestration can influence its performance. A model that is easily scalable in one thermal zone and convex as a function of the control inputs is derived based on energy balance equations. The indoor temperatures are treated as control inputs together with the cooling energy exchange with the virtual thermal storage. This simplifies the enforcement of comfort, which can be imposed through appropriate constraints on the control inputs. A convex constrained optimization program was formulated to address the optimal energy management, in order to minimize the electricity cost caused by Heating, Ventilation and Air Conditioning unit.

Refrigeration, air conditioning and heat pump (RACHP) systems currently account for nearly 20% of UK grid electricity use and over 7% of all UK greenhouse gas emissions. This research project has investigated the sources and levels of emissions from RACHP systems and how the cooling (and heating) energy and emissions from buildings might be reduced by optimizing the building’s design, construction and operation. Analysis of data from site surveys and maintenance logs confirmed that leakage of refrigerant can be a significant contributor to total RACHP emissions. TEWI (total equivalent warming impact) analyses showed that for RACHP systems with high GWP (global warming potential) refrigerants and annual leak rates of 10% or more, direct emissions from refrigerant leakage can exceed the indirect emissions associated with energy use. However, for heat pump and air conditioning systems, with typical leak rates of below 3%, using low GWP refrigerants (GWP = 500 or less), the direct emissions do not make a significant contribution to building emissions. A new dynamic energy balance model and Excel based tool were developed to help improve the understanding of building energy use and emissions. The tool can be used to predict the sensitivity to different building design concepts, features and operation and the parameters of the installed RACHP plant. Results for an office building suggest that the building fabric (with the exception of the glazing) is not necessarily a key factor influencing the total energy use and emissions. However, relatively simple measures to reduce electricity use and to reduce solar gain could each reduce building emissions by 10% or more. Results for a dwelling built to 2006 Building Regulations demonstrated an overheating risk in summer, even with mechanical ventilation, but adding a 2 kW air conditioning unit could prevent overheating, with lower energy use and emissions than a similar dwelling incorporating mechanical ventilation. Climate change simulations for the year 2080 predicted a net increase in energy demand and emissions of about 5% for the office building (mainly associated with the use of grid electricity), implying that the grid carbon factor is likely to be a key determinant of future emissions from such buildings. For dwellings without mechanical ventilation or air conditioning, internal temperatures might rise as high as 40°C in summer months, but a small air conditioning unit could maintain temperatures below 25°C with no increase in total energy use and emissions compared with the present day. For a grid electricity carbon factor reduction of 80%, total emissions for the simulated office building would fall by about 70% and for the dwelling by about 50%.

Energy plays a major role in the economic prosperity of the Middle Eastern countries. Since the region is the largest oil producer of the world, it is less anticipated that these countries would ever be face with an energy crisis similar to the one experienced by the rest of the world during 1970s. The region was going through a chronic electricity demand supply crises with the demand for electrical energy in the rapidly expanding towns, cities and industries, far exceeding the power being made available. The relatively low electrical tariff also contributed to the increasing power demand due to wastage and uneconomical usage of electrical energy. The power generating companies and the Government authorities in the Middle East encouraged scientists and engineers to engage in ambitious Demand Side Management (DSM) programmes to develop novel ideas and new technologies to improve system efficiencies and to reduce energy consumption specifically in the field of refrigeration and air conditioning. The researcher began analysing the potential and possible applications of cool storage as a tool for Demand Side Management (DSM) in central air conditioning systems in the Middle East in 1991. The coupling of a refrigerated water storage tank or an ice storage tank to an air-cooled chiller plant, operated at night for load shifting, electrical peak demand reduction and energy conservation has been the major interest of investigation. The model project commissioned in 1996 used as a typical example to investigate electrical demand management for an office building in Riyadh, Saudi Arabia. The aim of this research was to develop new modified comfort cooling system coupled with a cool storage or commonly known as Thermal Energy Storage (TES) network. The research was expected to establish certain favouring conditions in relation to technical, economical and environmental criteria to make the TES application a viable option in comfort cooling systems in commercial buildings in the Middle East for electrical demand reduction, load shifting and energy conservation.

The main objectives of this thesis have been to evaluate how, under which premises, and to what extent building thermal mass can contribute to reduce the net energy demand in office buildings. The thesis also assesses the potential thermal environmental benefits of utilizing thermal mass in office buildings, i.e. reduction of temperature peaks, reduction of temperature swings, and the reduction in the number of hours with excessive operative temperatures. This has been done by literature searches, and experimental and analytical assessments. This thesis mainly concerns office buildings in the Norwegian climate. However, the methods used and the results obtained from this work are transferable to other countries with similar climates and building codes.

Within the limitations of this thesis and based on the findings from all parts and papers this thesis comprises, it is shown that utilization of thermal mass in office buildings reduces the daytime peak temperature, reduces the diurnal temperature swing, decreases the number of hours with excessive temperatures, and increases the ability of a space to handle daytime heat loads. Exposed thermal mass also contributes to decrease the net cooling demand in buildings. However, thermal mass is found to have only a minor influence on the heating demand in office buildings.

The quantity of the achievements is dependent on the amount of exposed thermal mass, night ventilation strategy, and airflow rates. In addition, parameters such as set point temperatures, control ranges, occupancy patterns, daytime ventilation airflow rates, and prevailing convection regimes are influential for the achieved result. The importance of these parameters are quantified and discussed.

Hovedmålene med denne avhandlingen har vært å evaluere hvordan, under hvilke forutsetninger og i hvilken utstrekning termisk masse kan bidra til å redusere netto energibehov i kontorbygninger. Avhandlingen vurderer også hvilke potensielle fordeler termisk masse har for det termiske inneklimaet, dvs. reduksjon av maksimumstemperatur, temperatursvingninger og antall timer med overtemperaturer. Disse undersøkelsene er gjort gjennom søk i litteraturen, feltstudier og analytiske metoder. Avhandlingen omfatter i hovedsak kontorbygninger under norske forhold, men metodene og resultatene er overførbare til andre land med sammenlignbare klimatiske forhold og byggeskikk.

Innenfor avgrensningene gjort i avhandlingen og basert funnene i de ulike delene og artiklene avhandlingen består av, er det vist at utnyttelse av termisk masse i kontorbygg bidrar til å redusere netto energibehov. Termisk masse reduserer også maksimumstemperaturen dagtid, demper temperaturvariasjonene over døgnet og reduserer antall timer med overtemperaturer. Utnyttelse av termisk masse bidrar også til at rom kan tåle en høyere intern varmelast enn lette rom uten at dette går ut over den termiske komforten. Termisk masse har imidlertid liten betydning for energibehovet for oppvarming i kontorbygg.

Gevinsten med å utnytte termisk masse avhenger av tilgjengeligheten av eksponerte tunge materialer, strategi for nattventilasjon og ventilasjonsluftmengder. I tillegg innvirker parametere som settpunkttemperaturer, dødbånd og kontrollintervaller for ventilasjonen og bruksmønster. Innvirkningen av disse parametrene er diskutert og kvantifisert.

In the year 2006, the energy performance directive 2002/91/EG was passed by the European Union, according to this directive the Swedish building code was supplemented by a key measure of energy use intensity (EUI). The implemented EUI equals some energy use within a building divided by its floor area and must be calculated in new housing estate and shown when renting or selling housing property. In order to improve the EUI, energy efficiency refurbishments could be implemented. Building energy simulation tools enables a virtual view a building model and can estimate the energy use before implementing any refurbishments. They are a powerful resource when determine the impact of the refurbishment measure. In order to obtain a correct model which corresponds to the actual energy use, some adjustments of the model are often needed. This process refers to as calibration. The used EUI has been criticized and thus, the first objective in this work was to suggest an alternative key measure of a buildings performance. The results showed that the currently used EUI is disfavoring some districts in Sweden. New housing estate in the far north must take more refined actions in order to fulfill the regulation demand, given that the users are behaving identical regardless where the house is located. Further, the suggested measure is less sensitive to the users’ behavior than the presently used EUI. It also has a significance meaning in building design as it relating the building shape and thermal properties and stating that extreme building shapes must undergo a stricter thermal construction rather than buildings that are more compact. Thus, the suggested key measure also creates a communication link between architects and the consultant constructors. The second objective of this thesis has been to investigate a concept of calibration using the data normally provided by energy bills, i.e. some monthly aggregated data. A case study serves to answer this objective, by using the building energy simulation tool IDA ICE 4.7 and a building located in Umeå, Sweden. The findings showed that the used calibration approach yielded a model considered as calibrated in eleven of twelve months. Furthermore, the method gives a closer agreement to the actual heat demand rather than using templates and standardized values. The major explanation of the deviation was influence of the users, but also that the case study building burden with large heat losses by domestic hot water circulation and thus, more buildings should be subjected to this calibration approach.

As fossil fuel usage has been proven to have a negative impact on human health and the environment, the world has embraced the usage of renewable energy sources, mainly for energy production. In Cyprus, solar energy is the most potent renewable source and this can be seen by the vast majority of the population using solar water heaters in their households. This thesis explores the usage of solar energy for electricity and domestic hot water production at a residential level by presenting the designs of three solar-thermal concept systems for achieving this task; the first being the basic design of all three without any form of storage, the second is fitted with thermal latent heat storage and the third is fitted with a natural gas boiler instead. The optimal solution is the second concept system that is capable of storing thermal energy around the year thus having a nearly uninterrupted operation, reducing the dependency on fossil fuel produced electricity and emissions. The thesis also explored the usage of siloxane organic compounds as working fluids for a low temperature Rankine cycle, which had a significant impact in the increase of the thermal-to-electrical efficiency of the cycle, raising it to nearly 25%, greater than the efficiency of best acclaimed photovoltaic collector currently available. Lastly, taking into account a typical household’s demand profile and by allowing the optimal system to operate as part of the national electrical network continuously, the size of the system’s components could be reduced significantly making it more feasible for installing in a typical household’s premises. However, due to the non-existence of these components in the within the project’s specifications, the thesis could not include a useful economic analysis for a more realistic comparison with a similar sized photovoltaic system.

Applying building energy simulations, the dissertation investigates the issu-es of energy efficiency of public buildings. The main object of research – influence of the glazing of the public building on its energy demand. Next to its main function to ensure daylighting, glazing must to be energy efficient. So these requirements conflict. The aim of this dissertation is to perform the complex analysis of the influence of glazing characteristics on the building‘s microclimate and lighting systems energy demand, taking into account DL demand. Also define, what glazing characteristics in Lithuanian and similar climate countries, are able to decrease buildings energy demand to the level of the low energy building. The paper approaches two major tasks. Task 1 is performance of the detailed analysis of influence of glazing on energy demand of the public building. Task 2 is determination of the efficient glazing characteristics of the energy efficient building. The dissertation consists of Introduction, 4 chapters, Conclusions, references and list of published works of the author on the topic of dissertation. The introduction reveals the investigated problem, importance of the thesis and the object of research and describes the purpose and tasks of the paper, research methodology, scientific novelty, the practical significance of results examined in the paper and defended statements. The introduction ends in presenting the author’s publications on the subject of the defended... [to full text]
Disertacijoje, taikant dinaminį pastatų energijos poreikių modeliavimą, nag-rinėjamos viešosios paskirties pastatų energinio efektyvumo problemos. Pagrin-dinis tyrimo objektas yra viešosios paskirties pastato fasado įstiklinimo įtaka energijos poreikiams. Greta savo pagrindinės funkcijos – pakankamo natūralaus apšvietimo užtikrinimo, fasado įstiklinimas privalo būti energiškai efektyvus. Tai prieštaringi reikalavimai. Pagrindinis disertacijos tikslas – įvertinant natūralaus apšvietimo poreikį, kompleksiškai išanalizuoti viešosios paskirties pastato įstiklinimo charakteristi-kų įtaką pastato mikroklimato ir apšvietimo sistemų energijos poreikiams bei nustatyti, kokioms pastato įstiklinimo charakteristikoms esant, Lietuvoje bei pa-našaus klimato šalyse pastato energijos poreikius galima būtų sumažinti iki ma-žai energijos vartojančio pastato lygio. Darbe sprendžiami du pagrindiniai užda-viniai: pirmasis – atliekama įstiklinimo įtakos kondicionuojamo pastato energijos poreikiams analizė; antrasis – nustatomos efektyvios energiškai efek-tyvaus pastato įstiklinimo charakteristikos. Disertaciją sudaro įvadas, keturi skyriai, rezultatų apibendrinimas, naudotos literatūros ir autoriaus publikacijų disertacijos tema sąrašai. Įvadiniame skyriuje aptariama tiriamoji problema, darbo aktualumas, apra-šomas tyrimų objektas, formuluojamas darbo tikslas bei uždaviniai, aprašoma tyrimų metodika, darbo mokslinis naujumas, darbo rezultatų praktinė reikšmė, ginamieji teiginiai, pristatomos... [toliau žr. visą tekstą]

The use of energy in buildings is a complex problem, but it can be reduced and alleviated by making appropriate decisions. Therefore, architects face a major and responsible task of designing the built environment in such a way that its energy dependence will be reduced to a minimum, while at the same time being able to provide comfortable living conditions. Today, architects have many tools at their disposal, facilitating the design process and simultaneously ensuring proper assessment in the early stages of building design. The purpose of this book is to present ongoing research from the universities involved in the project Creating the Network of Knowledge Labs for Sustainable and Resilient Environments (KLABS). This book attempts to highlight the problem of energy use in buildings and propose certain solutions. It consists of nine chapters, organised in three parts. The gathering of chapters into parts serves to identify the different themes that the designer needs to consider, namely energy resources, energy use and comfort, and energy efficiency. Part 1, entitled “Sustainable and Resilient Energy Resources,” sets off by informing the reader about the basic principles of energy sources, production, and use. The chapters give an overview of all forms of energies and energy cycle from resources to end users and evaluate the resilience of renewable energy systems. This information is essential to realise that the building, as an energy consumer, is part of a greater system and the decisions can be made at different levels. Part 2, entitled “Energy and Comfort in the Built Environment”, explain the relationship between energy use and thermal comfort in buildings and how it is predicted. Buildings consume energy to meet the users’ needs and to provide comfort. The appropriate selection of materials has a direct impact on the thermal properties of a building. Moreover, comfort is affected by parameters such as temperature, humidity, air movement, air quality, lighting, and noise. Understanding and calculating those conditions are valuable skills for the designers. After the basics of energy use in buildings have been explained, Part 3, entitled “Energy Saving Strategies” aims to provide information and tools that enable an energy- and environmentally-conscious design. This part is the most extensive as it aims to cover different design aspects. Firstly, passive and active measures that the building design needs to include are explained. Those measures are seen from the perspective of heat flow and generation. The Passive House concept, which is explained in the second chapter of Part 3, is a design approach that successfully incorporates such measures, resulting in low energy use by the building. Other considerations that the following chapters cover are solar control, embodied energy and CO2 emissions, and finally economic evaluation. The energy saving strategies explained in this book, despite not being exhaustive, provide basic knowledge that the designer can use and build upon during the design of new buildings and existing building upgrades. In the context of sustainability and resilience of the built environment, the reduction of energy demand is crucial. This book aims to provide a basic understanding of the energy flows in buildings and the subsequent impact for the building’s operation and its occupants. Most importantly, it covers the principles that need to be taken into account in energy efficient building design and demonstrates their effectiveness. Designers are shaping the built environment and it is their task to make energy-conscious and informed decisions that result in comfortable and resilient buildings.

Effective energy planning and governmental decision making policies heavily rely on accurate forecast of energy demand. This paper discusses and compares five different forecasting techniques to model energy demand in the United States using economic and demographic factors. Two Artificial Neural Network (ANN) models, two regression analysis models and one autoregressive integrated moving average (ARIMA) model are developed based on historical data from 1950–2013. While ANN model 1 and regression model 1 use Gross Domestic Product (GDP), Gross National Product (GNP) and per capita personal income as independent input factors, ANN model 2 and regression model 2 employ GDP, GNP and population (POP) as the predictive factors. The forecasted values resulted from these models are compared with the forecast made by the U.S. Energy Information Administration (EIA) for the period of 2014–2019. The forecasted results of ANN models and regression model 1 are close to those of the U.S. EIA, however the results of regression model 2 and ARIMA model are significantly different from the forecast made by the U.S. EIA. Finally, a comparison of the forecasted values resulted from three efficient models showed the energy demand would vary between 95.51 and 100.08 quadrillion British thermal unit for the period of 2014–2019.

Thermal storage systems were originally designed to shift on-peak cooling production to off-peak cooling production to reduce on-peak electricity demand. Recently, however, the reduction of both on- and off-peak demands is becoming an exceedingly important issue. Reduction of on- and off-peak demands can also extend the life span and defer or eliminate the replacement of power transformers due to potential shortage of building power capacity caused by anticipated equipment load increases. Next day daily average electricity demand is a critical set point to operate chillers and associated pumps at the appropriate time. For this paper, a mathematical analysis of the annual daily average cooling of a building was conducted, and three real-time building load forecasting models were developed: a first-order autoregressive model, a random walk model, and a linear regression model. A comparison of results shows that the random walk model provides the best forecast. A complete control algorithm integrated with forecast model for a chiller plant including chillers, thermal storage system and pumping systems was developed to verify the feasibility of applying this algorithm in the building automation system. Application results are introduced in this paper as well.

The thermal response of a large city including the energy production aspects of it are explored for a large and complex city using urbanized atmospheric mesoscale modeling. The Weather Research and Forecasting (WRF) mesocale model is coupled to a multi-layer urban canopy model that considers thermal and mechanical effects of the urban environment including a building scale energy model to account for anthropogenic heat contributions due to indoor-outdoor temperature differences. This new urban parameterization is used to evaluate the evolution and the resulting urban heat island formation associated to a 3-day heat wave in New York City (NYC) during the summer of 2010. High resolution (250 m.) urban canopy parameters (UCPs) from the National Urban Database were employed to initialize the multi-layer urban parameterization. The precision of the numerical simulations is evaluated using a range of observations. Data from a dense network of surface weather stations, wind profilers and Lidar measurements are compared to model outputs over Manhattan and its surroundings during the 3-days event. The thermal and drag effects of buildings represented in the multilayer urban canopy model improves simulations over urban regions giving better estimates of the surface temperature and wind speed. An accurate representation of the nocturnal urban heat island registered over NYC in the event was obtained from the improved model. The accuracy of the simulation is further assessed against more simplified urban parameterizations models with positive results with new approach. Results are further used to quantify the energy consumption of the buildings during the heat wave, and to explore alternatives to mitigate the intensity of the UHI during the extreme event.

Residential buildings in Canada and the United States are responsible for approximately 20% of secondary energy consumption. Over the past 25 years, air conditioning has seen the single largest increase of any residential end use. This load currently places a significant peak load on the electrical grid during later afternoon periods during the cooling season. One method to reduce or eliminate this peak load being placed in the grid is the use of a chiller coupled with a thermal storage system. The chiller operates during off-peak periods, predominately over-night to charge the thermal storage tank, and the stored cooling potential is realized to meet the cooling loads during peak periods. In previous studies, the use of a chiller has seen a reduction in annual operating costs, however a significant increase in energy occurs as a result of decreased performance of the chiller. To improve system performance, a new control scheme was developed, which uses the forecasted daily high for the next day to predict the cooling load for the day during peak periods for the day. The predicted cooling load is then used as the set-point for the cold thermal storage tank, allowing the peak cooling load to be met using stored cooling potential. This control scheme was implemented into a modelled house located in each of the 7 major ASHRAE zones, with a storage tank with a previously found optimal tank volume. Across each of the locations, a reduction in annual utility costs and overall energy required to meet the building loads observed, with the total cost savings between 0.3% and 1.5% and total electricity required to meet the cooling demand decreasing by as much as 10.2%.

Thermoacoustic technology potentially offers a sustainable and reliable solution to help address the continuing demand for electric power. Thermoacoustic devices, operating on the principle of standing or traveling acoustic waves, can be designed as a heat pump or a prime mover system. This technical strategy is environmentally friendly as it utilizes noble gases, or air, as the working fluid and does not directly produce harmful emissions. However, heating and cooling sources are required to create the required thermal gradient. Due to the inherit simplicity and limitation of moving components, thermoacoustic devices require little maintenance and have a forecasted long operational lifespan. This paper will present the design considerations necessary to construct a traveling wave thermoacoustic heat engine. The modeling, analysis, fabrication, and testing with integrated sensors will be discussed to offer insight into the capabilities and subtleties. A case study with system operation at 54 Hz and 7.8% thermal to acoustic efficiency will be presented.

The International Atomic Energy Agency’s (IAEA’s) International Project on Innovative Nuclear Reactors and Fuel Cycles (INPRO) was established in 2000 with the goal to ensure a sustainable nuclear energy supply to meet the global energy needs in the 21st century. The INPRO activities on global and regional nuclear energy scenarios provide newcomers and mature nuclear countries alike with better understanding of options for making a collaborative transition to future sustainable nuclear energy systems. Collaborative project GAINS (Global Architecture of Innovative Nuclear Energy Systems Based on Thermal and Fast Reactors Including a Closed Fuel Cycle) developed an internationally verified analytical framework for assessing such transition scenarios. The framework (hereafter, GAINS framework) is a part of the integrated services provided by IAEA to Member States considering initial development or expansion of their nuclear energy programmes. The paper presents major elements of the analytical framework and selected results of its application, including: • Long-term nuclear energy demand scenarios based on the IAEA Member States’ high and low estimations of nuclear power deployment until 2030 and expected trends until 2050 and on forecasts of competent international energy organizations; • Heterogeneous world model comprised of groups of non-personified non-geographical countries (NGs) with different policy regarding nuclear fuel cycle back end; • Architectures of nuclear energy systems; • Metrics and tools for the assessment of dynamic nuclear energy system evolution scenarios regarding sustainability, including a set of key indicators and evaluation parameters; • An internationally verified database with best estimate material flow and economic characteristics of existing and advanced nuclear reactors and associated nuclear fuel cycles needed for material flow analysis and comparative economic analysis, extending the previously developed IAEA databases and taking into account preferences of different countries; • Selected results of sample analysis for scenarios involving transition from the present fleets of nuclear reactors and fuel cycles to future sustainable nuclear energy system architectures involving innovative technological solutions.

At present, offshore gas turbines are operated encouraging high thermal efficiency and low power consumption. High thermal efficiency normally demands operation close to full load, which may increase the emission of specific components. The present emission tax on CO2 has a substantial impact on gas turbine operation and maintenance costs. At present, it is of great importance to include the influence of emission taxes by focusing on optimum energy operation and maintenance. The influence of gas turbine degradation on operating costs is high. Analysis based on operational experience and field test performance data show an extra cost due to deterioration up to NOK 4.5 million a year. To obtain optimum energy operation and maintenance for the gas turbine drivers on Sleipner A, analysis and developments are based on: • on-line condition monitoring, to detect machinery condition and component degradation • prediction routines, to forecast degradation “development” as a function of time • optimisation routines, to predict optimum intervention time based on operating and maintenance costs • sensitivity analysis, including site performance correction to actual operating condition The developed procedure has resulted in increased flexibility and availability, in addition to reduced operating and maintenance costs. Total potential savings are estimated up to NOK 2.5 mill. per gas turbine a year. The system forms an important tool in future operation of the 60 gas turbines in present service.

The main objective of Subtask C is to identify, assess and in some cases further develop retrofit solutions and strategies for historic buildings. The solutions should fulfil the conservation compatibility of historic buildings as well as energy efficiency goals towards lowest possible energy demand and CO2 emissions (NZEB). Further, the objective is to make the solutions available for comprehensive integrated refurbishing concepts and strategies.

This publication assesses the potential for deployment of the leading Marine Renewable Energy (MRE) technologies including Fixed Offshore Wind, Floating Offshore Wind, Ocean Thermal Energy Conversion across nine Countries of Interest (COI) in the Caribbean region. This is achieved by conducting a technology review, analysing resource levels in each of the COIs, and presenting the outputs of Locational Guidance work identifying preferred areas for potential future project development. This work concludes that MRE can offer a secure supply of indigenous clean energy, that resources are sufficiently abundant to meet the current and future energy demand of each of the COIs many times over, and that the leading MRE technologies are sufficiently advanced to be worthy of immediate prioritisation. This Technical Note draws on and presents outcomes from work undertaken in 2019 as part of a Technical Cooperation Agreement between the IDB and CDB under the Support for Sustainable and Resilient Projects in the Caribbean programme.

1.1 Macroeconomic summary Economic recovery has consistently outperformed the technical staff’s expectations following a steep decline in activity in the second quarter of 2020. At the same time, total and core inflation rates have fallen and remain at low levels, suggesting that a significant element of the reactivation of Colombia’s economy has been related to recovery in potential GDP. This would support the technical staff’s diagnosis of weak aggregate demand and ample excess capacity. The most recently available data on 2020 growth suggests a contraction in economic activity of 6.8%, lower than estimates from January’s Monetary Policy Report (-7.2%). High-frequency indicators suggest that economic performance was significantly more dynamic than expected in January, despite mobility restrictions and quarantine measures. This has also come amid declines in total and core inflation, the latter of which was below January projections if controlling for certain relative price changes. This suggests that the unexpected strength of recent growth contains elements of demand, and that excess capacity, while significant, could be lower than previously estimated. Nevertheless, uncertainty over the measurement of excess capacity continues to be unusually high and marked both by variations in the way different economic sectors and spending components have been affected by the pandemic, and by uneven price behavior. The size of excess capacity, and in particular the evolution of the pandemic in forthcoming quarters, constitute substantial risks to the macroeconomic forecast presented in this report. Despite the unexpected strength of the recovery, the technical staff continues to project ample excess capacity that is expected to remain on the forecast horizon, alongside core inflation that will likely remain below the target. Domestic demand remains below 2019 levels amid unusually significant uncertainty over the size of excess capacity in the economy. High national unemployment (14.6% for February 2021) reflects a loose labor market, while observed total and core inflation continue to be below 2%. Inflationary pressures from the exchange rate are expected to continue to be low, with relatively little pass-through on inflation. This would be compatible with a negative output gap. Excess productive capacity and the expectation of core inflation below the 3% target on the forecast horizon provide a basis for an expansive monetary policy posture. The technical staff’s assessment of certain shocks and their expected effects on the economy, as well as the presence of several sources of uncertainty and related assumptions about their potential macroeconomic impacts, remain a feature of this report. The coronavirus pandemic, in particular, continues to affect the public health environment, and the reopening of Colombia’s economy remains incomplete. The technical staff’s assessment is that the COVID-19 shock has affected both aggregate demand and supply, but that the impact on demand has been deeper and more persistent. Given this persistence, the central forecast accounts for a gradual tightening of the output gap in the absence of new waves of contagion, and as vaccination campaigns progress. The central forecast continues to include an expected increase of total and core inflation rates in the second quarter of 2021, alongside the lapse of the temporary price relief measures put in place in 2020. Additional COVID-19 outbreaks (of uncertain duration and intensity) represent a significant risk factor that could affect these projections. Additionally, the forecast continues to include an upward trend in sovereign risk premiums, reflected by higher levels of public debt that in the wake of the pandemic are likely to persist on the forecast horizon, even in the context of a fiscal adjustment. At the same time, the projection accounts for the shortterm effects on private domestic demand from a fiscal adjustment along the lines of the one currently being proposed by the national government. This would be compatible with a gradual recovery of private domestic demand in 2022. The size and characteristics of the fiscal adjustment that is ultimately implemented, as well as the corresponding market response, represent another source of forecast uncertainty. Newly available information offers evidence of the potential for significant changes to the macroeconomic scenario, though without altering the general diagnosis described above. The most recent data on inflation, growth, fiscal policy, and international financial conditions suggests a more dynamic economy than previously expected. However, a third wave of the pandemic has delayed the re-opening of Colombia’s economy and brought with it a deceleration in economic activity. Detailed descriptions of these considerations and subsequent changes to the macroeconomic forecast are presented below. The expected annual decline in GDP (-0.3%) in the first quarter of 2021 appears to have been less pronounced than projected in January (-4.8%). Partial closures in January to address a second wave of COVID-19 appear to have had a less significant negative impact on the economy than previously estimated. This is reflected in figures related to mobility, energy demand, industry and retail sales, foreign trade, commercial transactions from selected banks, and the national statistics agency’s (DANE) economic tracking indicator (ISE). Output is now expected to have declined annually in the first quarter by 0.3%. Private consumption likely continued to recover, registering levels somewhat above those from the previous year, while public consumption likely increased significantly. While a recovery in investment in both housing and in other buildings and structures is expected, overall investment levels in this case likely continued to be low, and gross fixed capital formation is expected to continue to show significant annual declines. Imports likely recovered to again outpace exports, though both are expected to register significant annual declines. Economic activity that outpaced projections, an increase in oil prices and other export products, and an expected increase in public spending this year account for the upward revision to the 2021 growth forecast (from 4.6% with a range between 2% and 6% in January, to 6.0% with a range between 3% and 7% in April). As a result, the output gap is expected to be smaller and to tighten more rapidly than projected in the previous report, though it is still expected to remain in negative territory on the forecast horizon. Wide forecast intervals reflect the fact that the future evolution of the COVID-19 pandemic remains a significant source of uncertainty on these projections. The delay in the recovery of economic activity as a result of the resurgence of COVID-19 in the first quarter appears to have been less significant than projected in the January report. The central forecast scenario expects this improved performance to continue in 2021 alongside increased consumer and business confidence. Low real interest rates and an active credit supply would also support this dynamic, and the overall conditions would be expected to spur a recovery in consumption and investment. Increased growth in public spending and public works based on the national government’s spending plan (Plan Financiero del Gobierno) are other factors to consider. Additionally, an expected recovery in global demand and higher projected prices for oil and coffee would further contribute to improved external revenues and would favor investment, in particular in the oil sector. Given the above, the technical staff’s 2021 growth forecast has been revised upward from 4.6% in January (range from 2% to 6%) to 6.0% in April (range from 3% to 7%). These projections account for the potential for the third wave of COVID-19 to have a larger and more persistent effect on the economy than the previous wave, while also supposing that there will not be any additional significant waves of the pandemic and that mobility restrictions will be relaxed as a result. Economic growth in 2022 is expected to be 3%, with a range between 1% and 5%. This figure would be lower than projected in the January report (3.6% with a range between 2% and 6%), due to a higher base of comparison given the upward revision to expected GDP in 2021. This forecast also takes into account the likely effects on private demand of a fiscal adjustment of the size currently being proposed by the national government, and which would come into effect in 2022. Excess in productive capacity is now expected to be lower than estimated in January but continues to be significant and affected by high levels of uncertainty, as reflected in the wide forecast intervals. The possibility of new waves of the virus (of uncertain intensity and duration) represents a significant downward risk to projected GDP growth, and is signaled by the lower limits of the ranges provided in this report. Inflation (1.51%) and inflation excluding food and regulated items (0.94%) declined in March compared to December, continuing below the 3% target. The decline in inflation in this period was below projections, explained in large part by unanticipated increases in the costs of certain foods (3.92%) and regulated items (1.52%). An increase in international food and shipping prices, increased foreign demand for beef, and specific upward pressures on perishable food supplies appear to explain a lower-than-expected deceleration in the consumer price index (CPI) for foods. An unexpected increase in regulated items prices came amid unanticipated increases in international fuel prices, on some utilities rates, and for regulated education prices. The decline in annual inflation excluding food and regulated items between December and March was in line with projections from January, though this included downward pressure from a significant reduction in telecommunications rates due to the imminent entry of a new operator. When controlling for the effects of this relative price change, inflation excluding food and regulated items exceeds levels forecast in the previous report. Within this indicator of core inflation, the CPI for goods (1.05%) accelerated due to a reversion of the effects of the VAT-free day in November, which was largely accounted for in February, and possibly by the transmission of a recent depreciation of the peso on domestic prices for certain items (electric and household appliances). For their part, services prices decelerated and showed the lowest rate of annual growth (0.89%) among the large consumer baskets in the CPI. Within the services basket, the annual change in rental prices continued to decline, while those services that continue to experience the most significant restrictions on returning to normal operations (tourism, cinemas, nightlife, etc.) continued to register significant price declines. As previously mentioned, telephone rates also fell significantly due to increased competition in the market. Total inflation is expected to continue to be affected by ample excesses in productive capacity for the remainder of 2021 and 2022, though less so than projected in January. As a result, convergence to the inflation target is now expected to be somewhat faster than estimated in the previous report, assuming the absence of significant additional outbreaks of COVID-19. The technical staff’s year-end inflation projections for 2021 and 2022 have increased, suggesting figures around 3% due largely to variation in food and regulated items prices. The projection for inflation excluding food and regulated items also increased, but remains below 3%. Price relief measures on indirect taxes implemented in 2020 are expected to lapse in the second quarter of 2021, generating a one-off effect on prices and temporarily affecting inflation excluding food and regulated items. However, indexation to low levels of past inflation, weak demand, and ample excess productive capacity are expected to keep core inflation below the target, near 2.3% at the end of 2021 (previously 2.1%). The reversion in 2021 of the effects of some price relief measures on utility rates from 2020 should lead to an increase in the CPI for regulated items in the second half of this year. Annual price changes are now expected to be higher than estimated in the January report due to an increased expected path for fuel prices and unanticipated increases in regulated education prices. The projection for the CPI for foods has increased compared to the previous report, taking into account certain factors that were not anticipated in January (a less favorable agricultural cycle, increased pressure from international prices, and transport costs). Given the above, year-end annual inflation for 2021 and 2022 is now expected to be 3% and 2.8%, respectively, which would be above projections from January (2.3% and 2,7%). For its part, expected inflation based on analyst surveys suggests year-end inflation in 2021 and 2022 of 2.8% and 3.1%, respectively. There remains significant uncertainty surrounding the inflation forecasts included in this report due to several factors: 1) the evolution of the pandemic; 2) the difficulty in evaluating the size and persistence of excess productive capacity; 3) the timing and manner in which price relief measures will lapse; and 4) the future behavior of food prices. Projected 2021 growth in foreign demand (4.4% to 5.2%) and the supposed average oil price (USD 53 to USD 61 per Brent benchmark barrel) were both revised upward. An increase in long-term international interest rates has been reflected in a depreciation of the peso and could result in relatively tighter external financial conditions for emerging market economies, including Colombia. Average growth among Colombia’s trade partners was greater than expected in the fourth quarter of 2020. This, together with a sizable fiscal stimulus approved in the United States and the onset of a massive global vaccination campaign, largely explains the projected increase in foreign demand growth in 2021. The resilience of the goods market in the face of global crisis and an expected normalization in international trade are additional factors. These considerations and the expected continuation of a gradual reduction of mobility restrictions abroad suggest that Colombia’s trade partners could grow on average by 5.2% in 2021 and around 3.4% in 2022. The improved prospects for global economic growth have led to an increase in current and expected oil prices. Production interruptions due to a heavy winter, reduced inventories, and increased supply restrictions instituted by producing countries have also contributed to the increase. Meanwhile, market forecasts and recent Federal Reserve pronouncements suggest that the benchmark interest rate in the U.S. will remain stable for the next two years. Nevertheless, a significant increase in public spending in the country has fostered expectations for greater growth and inflation, as well as increased uncertainty over the moment in which a normalization of monetary policy might begin. This has been reflected in an increase in long-term interest rates. In this context, emerging market economies in the region, including Colombia, have registered increases in sovereign risk premiums and long-term domestic interest rates, and a depreciation of local currencies against the dollar. Recent outbreaks of COVID-19 in several of these economies; limits on vaccine supply and the slow pace of immunization campaigns in some countries; a significant increase in public debt; and tensions between the United States and China, among other factors, all add to a high level of uncertainty surrounding interest rate spreads, external financing conditions, and the future performance of risk premiums. The impact that this environment could have on the exchange rate and on domestic financing conditions represent risks to the macroeconomic and monetary policy forecasts. Domestic financial conditions continue to favor recovery in economic activity. The transmission of reductions to the policy interest rate on credit rates has been significant. The banking portfolio continues to recover amid circumstances that have affected both the supply and demand for loans, and in which some credit risks have materialized. Preferential and ordinary commercial interest rates have fallen to a similar degree as the benchmark interest rate. As is generally the case, this transmission has come at a slower pace for consumer credit rates, and has been further delayed in the case of mortgage rates. Commercial credit levels stabilized above pre-pandemic levels in March, following an increase resulting from significant liquidity requirements for businesses in the second quarter of 2020. The consumer credit portfolio continued to recover and has now surpassed February 2020 levels, though overall growth in the portfolio remains low. At the same time, portfolio projections and default indicators have increased, and credit establishment earnings have come down. Despite this, credit disbursements continue to recover and solvency indicators remain well above regulatory minimums. 1.2 Monetary policy decision In its meetings in March and April the BDBR left the benchmark interest rate unchanged at 1.75%.

There is a high degree of freedom and flexibility in the way to integrate renewable process heat in industrial processes. Nearly in every industrial or commercial application various heat sinks can be found, which are suitable to be supplied by renewable heat, e.g. from solar thermal, heat pumps, biomass or others. But in contrast to conventional fossil fuel powered heating systems, most renewable heating technologies are more sensitive to the requirements defined by the specific demand of the industrial company. Fossil fuel-based systems benefit from their indifference to process temperatures in terms of energy efficiency, their flexibility with respect to part-load as well as on-off operation, and the fuel as a (unlimited) chemical storage. In contrast, the required temperature and the temporal course of the heat demand over the year determine whether a certain regenerative heat generator is technically feasible at all or at least significantly influence parameters like efficiency or coverage rate.

Our hypothesis was that postnatal stress exposure or sensory input alters brain activity, which induces acetylation and/or methylation on lysine residues of histone 3 and alters methylation levels in the promoter regions of stress-related genes, ultimately resulting in long-lasting changes in the stress-response set point. Therefore, the objectives of the proposal were: 1. To identify the levels of total histone 3 acetylation and different levels of methylation on lysine 9 and/or 14 during both heat and feed stress and challenge. 2. To evaluate the methylation and acetylation levels of histone 3 lysine 9 and/or 14 at the Bdnfpromoter during both heat and feed stress and challenge. 3. To evaluate the levels of the relevant methyltransferases and transmethylases during infliction of stress. 4. To identify the specific localization of the cells which respond to both specific histone modification and the enzyme involved by applying each of the stressors in the hypothalamus. 5. To evaluate the physiological effects of antisense knockdown of Ezh2 on the stress responses. 6. To measure the level of CpG methylation in the promoter region of BDNF in thermal treatments and free-fed, 12-hour fasted, and re-fed chicks during post-natal day 3, which is the critical period for feed-control establishment, and 10 days later to evaluate longterm effects. 7. The phenotypic effect of antisense “knock down” of the transmethylaseDNMT 3a. Background: The growing demand for improvements in poultry production requires an understanding of the mechanisms governing stress responses. Two of the major stressors affecting animal welfare and hence, the poultry industry in both the U.S. and Israel, are feed intake and thermal responses. Recently, it has been shown that the regulation of energy intake and expenditure, including feed intake and thermal regulation, resides in the hypothalamus and develops during a critical post-hatch period. However, little is known about the regulatory steps involved. The hypothesis to be tested in this proposal is that epigenetic changes in the hypothalamus during post-hatch early development determine the stress-response set point for both feed and thermal stressors. The ambitious goals that were set for this proposal were met. It was established that both stressors i.e. feed and thermal stress, can be manipulated during the critical period of development at day 3 to induce resilience to stress later in life. Specifically it was established that unfavorable nutritional conditions during early developmental periods or heat exposure influences subsequent adaptability to those same stressful conditions. Furthermore it was demonstrated that epigenetic marks on the promoter of genes involved in stress memory are altered both during stress, and as a result, later in life. Specifically it was demonstrated that fasting and heat had an effect on methylation and acetylation of histone 3 at various lysine residues in the hypothalamus during exposure to stress on day 3 and during stress challenge on day 10. Furthermore, the enzymes that perform these modifications are altered both during stress conditioning and challenge. Finally, these modifications are both necessary and sufficient, since antisense "knockdown" of these enzymes affects histone modifications, and as a consequence stress resilience. DNA methylation was also demonstrated at the promoters of genes involved in heat stress regulation and long-term resilience. It should be noted that the only goal that we did not meet because of technical reasons was No. 7. In conclusion: The outcome of this research may provide information for the improvement of stress responses in high yield poultry breeds using epigenetic adaptation approaches during critical periods in the course of early development in order to improve animal welfare even under suboptimum environmental conditions.

Population growth, increasing prosperity and changing consumer habits globally are increasing demand for consumer electronics. Further to this, rapid changes in technology, falling prices and consumer appetite for better products have exacerbated e-waste management challenges and seen millions of tons of electronic devices become obsolete. This rapid literature review collates evidence from academic, policy focussed and grey literature on e-waste management in Africa. This report provides an overview of constitutes e-waste, the environmental and health impacts of e-waste, of the barriers to effective e-waste management, the opportunities associated with effective e-waste management and of the limited literature available that estimate future volumes of e-waste. Africa generated a total of 2.9 million Mt of e-waste, or 2.5 kg per capita, the lowest regional rate in the world. Africa’s e-waste is the product of Local and imported Sources of Used Electronic and Electrical Equipment (UEEE). Challenges in e-waste management in Africa are exacerbated by a lack of awareness, environmental legislation and limited financial resources. Proper disposal of e-waste requires training and investment in recycling and management technology as improper processing can have severe environmental and health effects. In Africa, thirteen countries have been identified as having a national e-waste legislation/policy.. The main barriers to effective e-waste management include: Insufficient legislative frameworks and government agencies’ lack of capacity to enforce regulations, Infrastructure, Operating standards and transparency, illegal imports, Security, Data gaps, Trust, Informality and Costs. Aspirations associated with energy transition and net zero are laudable, products associated with these goals can become major contributors to the e-waste challenge. The necessary wind turbines, solar panels, electric car batteries, and other "green" technologies require vast amounts of resources. Further to this, at the end of their lifetime, they can pose environmental hazards. An example of e-waste associated with energy transitions can be gleaned from the solar power sector. Different types of solar power cells need to undergo different treatments (mechanical, thermal, chemical) depending on type to recover the valuable metals contained. Similar issues apply to waste associated with other energy transition technologies. Although e-waste contains toxic and hazardous metals such as barium and mercury among others, it also contains non-ferrous metals such as copper, aluminium and precious metals such as gold and copper, which if recycled could have a value exceeding 55 billion euros. There thus exists an opportunity to convert existing e-waste challenges into an economic opportunity.

Macroeconomic summary Annual inflation continued to rise in the first quarter (8.5%) and again outpaced both market expectations and the technical staff’s projections. Inflation in major consumer price index (CPI) baskets has accelerated year-to-date, rising in March at an annual rate above 3%. Food prices (25.4%) continued to contribute most to rising inflation, mainly affected by a deterioration in external supply and rising costs of agricultural inputs. Increases in transportation prices and in some utility rates (energy and gas) can explain the acceleration in regulated items prices (8.3%). For its part, the increase in inflation excluding food and regulated items (4.5%) would be the result of shocks in supply and external costs that have been more persistent than expected, the effects of indexation, accumulated inflationary pressures from the exchange rate, and a faster-than-anticipated tightening of excess productive capacity. Within the basket excluding food and regulated items, external inflationary pressures have meaningfully impacted on goods prices (6.4%), which have been accelerating since the last quarter of 2021. Annual growth in services prices (3.8%) above the target rate is due primarily to food away from home (14.1%), which was affected by significant increases in food and utilities prices and by a rise in the legal monthly minimum wage. Housing rentals and other services prices also increased, though at rates below 3%. Forecast and expected inflation have increased and remain above the target rate, partly due to external pressures (prices and costs) that have been more persistent than projected in the January report (Graphs 1.1 and 1.2). Russia’s invasion of Ukraine accentuated inflationary pressures, particularly on international prices for certain agricultural goods and inputs, energy, and oil. The current inflation projection assumes international food prices will increase through the middle of this year, then remain high and relatively stable for the remainder of 2022. Recovery in the perishable food supply is forecast to be less dynamic than previously anticipated due to high agricultural input prices. Oil prices should begin to recede starting in the second half of the year, but from higher levels than those presented in the previous report. Given the above, higher forecast inflation could accentuate indexation effects and increase inflation expectations. The reversion of a rebate on value-added tax (VAT) applied to cleaning and hygiene products, alongside the end of Colombia’s COVID-19 health emergency, could increase the prices of those goods. The elimination of excess productive capacity on the forecast horizon, with an output gap close to zero and somewhat higher than projected in January, is another factor to consider. As a consequence, annual inflation is expected to remain at high levels through June. Inflation should then decline, though at a slower pace than projected in the previous report. The adjustment process of the monetary policy rate wouldcontribute to pushing inflation and its expectations toward the target on the forecast horizon. Year-end inflation for 2022 is expected to be around 7.1%, declining to 4.8% in 2023. Economic activity again outperformed expectations. The technical staff’s growth forecast for 2022 has been revised upward from 4.3% to 5% (Graph 1.3). Output increased more than expected in annual terms in the fourth quarter of 2021 (10.7%), driven by domestic demand that came primarily because of private consumption above pre-pandemic levels. Investment also registered a significant recovery without returning to 2019 levels and with mixed performance by component. The trade deficit increased, with significant growth in imports similar to that for exports. The economic tracking indicator (ISE) for January and February suggested that firstquarter output would be higher than previously expected and that the positive demand shock observed at the end of 2021 could be fading slower than anticipated. Imports in consumer goods, retail sales figures, real restaurant and hotel income, and credit card purchases suggest that household spending continues to be dynamic, with levels similar to those registered at the end of 2021. Project launch and housing starts figures and capital goods import data suggest that investment also continues to recover but would remain below pre-pandemic levels. Consumption growth is expected to decelerate over the year from high levels reached over the last two quarters. This would come amid tighter domestic and external financial conditions, the exhaustion of suppressed demand, and a deterioration of available household income due to increased inflation. Investment is expected to continue to recover, while the trade deficit should tighten alongside high oil and other export commodity prices. Given all of the above, first-quarter economic growth is now expected to be 7.2% (previously 5.2%) and 5.0% for 2022 as a whole (previously 4.3%). Output growth would continue to moderate in 2023 (2.9%, previously 3.1%), converging similar to long-term rates. The technical staff’s revised projections suggest that the output gap would remain at levels close to zero on the forecast horizon but be tighter than forecast in January (Graph 1.4). These estimates continue to be affected by significant uncertainty associated with geopolitical tensions, external financial conditions, Colombia’s electoral cycle, and the COVID-19 pandemic. External demand is now projected to grow at a slower pace than previously expected amid increased global inflationary pressures, high oil prices, and tighter international financial conditions than forecast in January. The Russian invasion of Ukraine and its inflationary effects on prices for oil and certain agricultural goods and inputs accentuated existing global inflationary pressures originating in supply restrictions and increased international costs. A decline in the supply of Russian oil, low inventory levels, and continued production limits on behalf of the Organization of Petroleum Exporting Countries and its allies (OPEC+) can explain increased projected oil prices for 2022 (USD 100.8/barrel, previously USD 75.3) and 2023 (USD 86.8/barrel, previously USD 71.2). The forecast trajectory for the U.S. Federal Reserve (Fed) interest rate has increased for this and next year to reflect higher real and expected inflation and positive performance in the labormarket and economic activity. The normalization of monetary policy in various developed and emerging market economies, more persistent supply and cost shocks, and outbreaks of COVID-19 in some Asian countries contributed to a reduction in the average growth outlook for Colombia’s trade partners for 2022 (2.8%, previously 3.3%) and 2023 (2.4%, previously 2.6%). In this context, the projected path for Colombia’s risk premium increased, partly due to increased geopolitical global tensions, less expansionary monetary policy in the United States, an increase in perceived risk for emerging markets, and domestic factors such as accumulated macroeconomic imbalances and political uncertainty. Given all the above, external financial conditions are tighter than projected in January report. External forecasts and their impact on Colombia’s macroeconomic scenario continue to be affected by considerable uncertainty, given the unpredictability of both the conflict between Russia and Ukraine and the pandemic. The current macroeconomic scenario, characterized by high real inflation levels, forecast and expected inflation above 3%, and an output gap close to zero, suggests an increased risk of inflation expectations becoming unanchored. This scenario offers very limited space for expansionary monetary policy. Domestic demand has been more dynamic than projected in the January report and excess productive capacity would have tightened more quickly than anticipated. Headline and core inflation rose above expectations, reflecting more persistent and important external shocks on supply and costs. The Russian invasion of Ukraine accentuated supply restrictions and pressures on international costs. This partly explains the increase in the inflation forecast trajectory to levels above the target in the next two years. Inflation expectations increased again and are above 3%. All of this increased the risk of inflation expectations becoming unanchored and could generate indexation effects that move inflation still further from the target rate. This macroeconomic context also implies reduced space for expansionary monetary policy. 1.2 Monetary policy decision Banco de la República’s board of directors (BDBR) continues to adjust its monetary policy. In its meetings both in March and April of 2022, it decided by majority to increase the monetary policy rate by 100 basis points, bringing it to 6.0% (Graph 1.5).