Dissertationen zum Thema „Time-Of-Use tariffs of electricity“

Includes bibliographical references (leaves 175-185).
In South Africa, Time of Use (TOU) tariffs have been available to Eskom's customers since 1986. TOU tariffs are intended to encourage users to avoid using electrical energy during the periods at which the national electricity system is stressed during normal operating conditions, i.e. peak periods. It has not always been clear how customers were responding to the different types of Eskom tariffs. A study was done of Eskom's Large Power Users (LPUs) in the Western Cape province of South Africa. Customers were categorised into City of Cape Town (CCT), 2 types of KSACS customers, Agricultural, Non-Agricultural and Rural Municipalities. At least 30 customers within a category were selected as a sample of that category.

A challenge for realising the benefits of smart meters, promoting energy security and decarbonising electricity is encouraging domestic consumers to switch from flat-rate electricity tariffs to a new generation of time of use (TOU) tariffs. However, a greater challenge is how to ensure that the right consumers sign up and that consent is informed: not all consumers will save money on a TOU tariff and evidence shows that a sizeable minority could be financially worse off. In a marked departure from the existing literature, this thesis argues that opt-out enrolment (a type of ‘nudge’) is unlikely to be a suitable method of recruiting consumers onto TOU tariffs, even though it could achieve almost universal enrolment. The first study shows that half of British energy consumers are unable to make informed choices about the cost-effective tariff for them, particularly those in low socio-economic grades. Consumers are therefore unlikely to opt-out of being switched onto a TOU tariff, even when unsuitable. Results from three further studies covering a collective sample size of 16,000 participants, show that tailoring the marketing of TOU tariffs towards electric vehicle (EV) owners could increase demand for TOUs amongst EV owners whilst reducing demand amongst non-EV owners, who pose less of a burden to the electricity network and are less likely to save money from switching. Unlike opt-out enrolment, tailored marketing is an ‘effective and selective’ nudge (Johnson, 2016). Unlike personalised defaults, tailored marketing can achieve informed consent. The results have implications for multiple ‘smart’ energy programmes, from signing up to TOU tariffs or direct load control contracts to participating in vehicle-to-grid services. In each case, a decision will need to be made about whether consumers will be left to opt-in or opt-out of such services, and to what extent it matters that consent is informed.

This master thesis evaluates the incentives of a newly implemented market controlled network tariff by analyzing consumption data and constructing a time-differentiated debiting model. The tariff was implemented by Sandviken Energi Elnät AB and the thesis evaluates its customers consumption data compared to data provided by Sundsvall Elnät AB. The differences in data is evaluated by statistical tests of Students t-test, Bayesian t-test and χ2-test with the result that no statistically significant change in user pattern can be found and thus an elucidation of the incentives must be made in the form of a hourly time-differentiated debating model. The thesis also evaluates the cost incentives of the model compared to spot prices where it is shown that the tariff model can benefit much from the spot prices hourly incentives in its hourly time-differentiated model. Five time-differentiated models were constructed and presented where three uses a color coding scheme. The conclusion is that a color coded time-differentiated tariff should give the costumers clear and cost-effective incentives.

The Swedish electricity system is transitioning due to the establishment of climate policy goals and trends related to technology and demographics. The transition has resulted in an increased demand for electricity. The increased demand for electricity in combination with lack of forecasts, planning and coordination between actors in the electricity sector has led to the occurrence of grid congestion. Extending the network is time-consuming and requires substantial investments. Instead, an alternative is to utilise the available grid capacity more efficiently by implementing flexibility solutions. Flexibility can be achieved by implementing incentives such as grid tariffs. This solution has recently gained much attention in Sweden, but it is not apparent how grid tariffs should be designed. The purpose of this thesis is to investigate how distribution grid tariffs could be designed to incentivise different actors to contribute to flexibility in a way that results in an efficient use of the electrical grid. A qualitative study was performed, collecting empirical data through semistructured interviews with actors in the Swedish electricity market. The aim is that the results from this thesis will act as a basis for DSOs planning to design grid tariffs with the purpose to utilise the grid more efficiently. The findings present a ToU capacity charge with off-peak periods that are free of charge as the preferable main price signal in the tariff to achieve efficient utilisation of the grid. It is further argued that other structural elements can complement the ToU capacity charge. A small fixed charge could be added in order to contribute to the cost reflectiveness of the grid tariff. A small energy charge could be incorporated in order to provide consumer with incentives to be flexible below the current metered maximum power and strengthen the signal from the ToU capacity charge. A small energy charge can avert difficulties related to providing incentives below the current metered maximum, as it still can provide some incentives to be flexible, or strengthen the signal from the ToU capacity charge. Further, the energy charge can ensure sustainability if customers respond well to a ToU capacity charge and to compensate solar PV customers. Furthermore, recommendations to further enable the grid tariffs potential to provide price signals include shifting the focus of the revenue cap from CapEx to OpEx and exploring the hampering signals of the energy tax as well as contradicting price signals from the wholesale electricity price.
Det svenska elsystemet genomgår en förändring till följd av införandet av klimatmål och trender relaterade till teknik och demografi. Denna förändring har resulterat i ett ökat effektbehov. Ett ökat effektbehov i kombination med bristande prognostisering, planering och samordning mellan aktörer inom elsektorn har lett till uppkomsten av kapacitetsbrist. Att bygga ut elnätet är tar tid och kräver större investeringar. Ett alternativ är att istället utnyttja det befintliga elnätet mer effektivt genom att implementera flexibilitetslösningar. Flexibilitet kan uppnås genom att införa incitament i form av elnätstariffer. Denna lösning har nyligen fått mycket uppmärksamhet i Sverige, men det är inte klart inte hur dessa elnätstariffer ska utformas. Syftet med detta arbete är att undersöka hur distributionsnätets tariffer kan utformas för att stimulera olika aktörer att bidra med flexibilitet på ett sätt som resulterar i en effektiv användning av det befintliga elnätet. En kvalitativ studie genomfördes där empiriska data samlades in genom semistrukturerade intervjuer med aktörer på den svenska elmarknaden. Syftet är att resultaten från detta arbete ska fungera som ett underlag för nätägare som planerar att utforma elnätstariffer med syftet att utnyttja nätet mer effektivt. Resultaten visar att en ToU-effektavgift med gratis off-peak perioder bör vara den huvudsakliga prissignalen i en elnätstariff som ämnar att utnyttja det befintliga nätet mer effektivt. Det visar även att andra strukturella element kan komplettera ToU-effektavgiften. En mindre fast avgift kan adderas i syfte att göra elnätstariffen mer kostnadsriktig. En mindre energiavgift kan införas för att ge kunder incitament att vara flexibla även under den nuvarande uppmätta maximala effekten och stärka signalen från ToU-effektavgiften. Vidare kan energiavgiften säkerställa tillräckliga intäkter för nätägaren om kunderna svarar bra på en ToU-effektavgift och för att kompensera kunder med solceller. Ytterligare rekommendationer för att möjliggöra prissignaler genom elnätstariffer inkluderar att skifta fokus på intäktsramen från CapEx till OpEx och utforska de hämmande prissignalerna från energiskatten och de motstridiga prissignalerna från elhandelspriset.

Les problèmes de planification liés aux tarifs multi-agents et au temps d'utilisation de l'électricité sont devenus des sujets de recherche d'actualité pour améliorer la satisfaction des clients et équilibrer l'offre et la demande en électricité. Les existant travaux révèlent que : 1) la plupart des problèmes d'ordonnancement se concentrent sur des configurations bi-agents ; 2) la plupart des recherches sur l'ordonnancement dans le cadre des tarifs horaires limitent aux machines uniques ou parallèles ou aux ateliers simplifiés ; et 3) très peu d'études prennent en compte des hypothèses réalistes, telles que les arrivées des tâches et les dates d'échéance souhaitées par les clients. Pour combler ces lacunes, cette thèse explore trois nouveaux problèmes d'ordonnancement flowshop qui intégrant successivement l'aspect de multi-agents et de tarifs horaires de l'électricité, tout en prenant en compte des hypothèses réalistes telles que les dates disponibles de tâches, les dates d'échéance et les activités de maintenance. Premièrement, un problème d'ordonnancement de flowshop et multi-agents avec dates de disponibilité et sous deux scénarios est étudié. L'objectif est de minimiser le temps total de réalisation des agents et le retard maximum. Pour obtenir une solution optimale pour les instances de petite taille, un algorithme de séparation et évaluation combinant des bornes inférieures et des stratégies d'élagage est développé. Pour les instances de taille moyenne, un algorithme co-évolutif intégrant des techniques d'apprentissage par renforcement est proposé pour obtenir des solutions proches d'optimum. Des expériences numériques démontrent l'efficacité des méthodes proposées.Deuxièmement, un bi-objectif problème d'ordonnancement de flowshop avec tarifs horaires de l'électricité est adressé. L'objectif est de trouver le meilleur compromis entre le coût total de l'électricité et le retard maximum. Basé sur l'analyse du problème, des inégalités valides sont conçues pour réduire l'espace de recherche.Ensuite, une méthode de contrainte ε combinant taille de pas maximale et stratégie d'inversion est proposée pour obtenir le front de Pareto. Pour les instances de taille moyenne et grande, un algorithme d'optimisation des mouches à fruits en deux étapes est appliqué pour obtenir un front de approché. Les performances des algorithmes proposés sont évaluées à travers diverses expériences numériques.Enfin, un problème d'ordonnancement de flowshop et multi-agents avec tarifs horaires de l'électricité est étudié. L'objectif est de minimiser le temps total de réalisation des agents et le coût total de l'électricité, simultanément. Un nouveau algorithme de séparation et évaluation est conçu pour résoudre le problème, dans lequel une stratégie de branchement à deux nœuds et des règles d'élagage sont fournies pour réduire efficacement le temps de calcul. La performance de l'algorithme proposé est évaluée en comparant les résultats proposés par un solveur commercial CPLEX
Multi-agent and time-of-use (ToU) tariff of electricity related scheduling problems have become hot research topics in production scheduling to improve customer satisfaction and balance electricity supply and demand.Existing works reveal that: 1) most multi-agent scheduling focuses on bi-agent problems; 2) most scheduling research under ToU tariffs addresses single and parallel machine, or simplified shop environments; and 3) very few studies consider real-world assumptions, such as dynamic job arrivals and customer-desired due dates.To bridge these research gaps, this thesis investigates three new flow shop scheduling problems which successively integrates the aspect of multi-agent and ToU tariffs, considering practical assumptions such as release dates, due dates and maintenance activities. Firstly, a multi-agent FSS problem with release dates under two scanerios is addressed. The objective is to minimize the total completion time of the agents and the maximum lateness. To obtain an optimal solution for small-size instances, a branch-and-bound (B&B) algorithm combining lower bounds and pruning strategies is developed. For medium-size instances, a co-evolutionary algorithm incorporating reinforcement learning techniques is proposed to obtain near-optimal solutions. Numerical experiments demonstrate the effectiveness of the proposed methods.Secondly, a bi-objective FSS problem under ToU tariffs is investigated. The objective is to find the best trad-off between the total electricity cost and the maximum lateness. Based on problem analysis, valid inequalities are designed to to reduce the search space. And then, an ε-constraint method combining maximum step size and inversion strategy is proposed to obtain the Pareto front. For medium- and large-size instances, a two-stage fruit fly optimization algorithm is applied to obtain an approximate Pareto front. The performance of the proposed algorithms is evaluated through various numerical experiments.Finally, a bi-objective multi-agent FSS problem under ToU tariffs is studied. The objective is to simultaneously minimize the total completion time of agents and the total electricity cost. A new B&B algorithm is designed for the problem, in which a two-node branching strategy and pruning rules are provided to effectively reduce the computational time. The performance of the proposed algorithm is evaluated by comparing the results proposed by a commercial solver CPLEX

Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools. In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management. Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented.
Libyan government

Various forecasting tools, based on historical data, exist for planners of national networks that are very effective in planning national interventions to ensure energy security, and meet carbon obligations over the long term. However, at a local community level, where energy demand patterns may significantly differ from the national picture, planners would be unable to justify local and more appropriate intervention due to the lack of appropriate planning tools. In this research, a new methodology is presented that initially creates a virtual community of households in a small community based on a survey of a similar community, and then predicts the energy behaviour of each household, and hence of the community. It is based on a combination of the statistical data, and a questionnaire survey. The methodology therefore enables realistic predictions and can help local planners decide on measures such as embedding renewable energy and demand management. Using the methodology developed, a study has been carried out in order to understand the patterns of electricity consumption within UK households. The methodology developed in this study has been used to investigate the incentives currently available to consumers to see if it would be possible to shift some of the load from peak hours. Furthermore, the possibility of using renewable energy (RE) at community level is also studied and the results presented. Real time pricing information was identified as a barrier to understanding the effectiveness of various incentives and interventions. A new pricing criteria has therefore been developed to help developers and planners of local communities to understand the cost of intervention. Conclusions have been drawn from the work. Finally, suggestions for future work have been presented.

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
This work project consists on the proposal of a product/service – Variable Time of Use Tariff – to enhance the innovativeness of the portfolio of EDP Comercial. This product/service is dependent on the simultaneous use of a smart meter, a home energy manager and a set of smart domestic appliances. To sustain my proposal I resorted to data about the wind energy, the use of smart meters together with time of use tariffs and the general characteristics of tariff structures in Europe. A SWOT analysis follows the description of the product/service, with one threat and one opportunity standing as major issues. The feasibility of the implementation of the tariff I propose depends entirely the future of these two factors, thus making this work project a future looking one.

L'industrie est le plus grand consommateur d'énergie dans le monde et la majeure partie de sa consommation est électrique. Pour moduler la consommation et équilibrer les périodes creuses et de pic, les producteurs d'électricité dans de nombreux pays pratiquent une tarification différenciée, en anglais "time-of-use (TOU) policy", afin d’encourager les industriels et les particuliers à adapter leur consommation. Cette stratégie incite les gros consommateurs industriels, en particulier le secteur semi-conducteur où la fabrication se fait souvent par lots, à réduire leurs factures d’électricité en adaptant leur production.Dans ce travail, nous étudions plusieurs problèmes d’ordonnancement de production par lots avec tarification différenciée d'électricité. Nous nous intéressons d’abord à l’ordonnancement d’une machine par lots pour minimiser le coût total d’électricité et le makespan. Le deuxième problème étudié généralise le premier en considérant le coût d’électricité pendant les périodes inactives de la machine telles que les périodes de réglage ou d'attente. Enfin, nous traitons l’ordonnancement sur machines parallèles par lots avec des pièces non identiques. Pour chacun de ces problèmes, nous construisons des modèles mathématiques appropriés, et évaluons sa complexité. Pour la résolution, nous proposons plusieurs méthodes de ɛ-contrainte dans lesquelles des sous-problèmes sont transformés en problèmes de sac-à-doc, de sacs-à-doc multiples et ou de bin packing. Nous développons aussi une méthode itérative à deux étapes. Les performances des méthodes développées sont évaluées à l'aide d'un grand nombre d'instances représentatives générées au hasard. Les résultats numériques montrent l'efficacité de ces méthodes par rapport au logiciel commercial CPLEX
The industrial sector is the largest consumer of the world's total energy and most of its consumption form is electricity. To strengthen the grid's peak load regulation ability, time-of-use (TOU) electricity pricing policy has been implemented in many countries to encourage electricity users to shift their consumption from on-peak periods to off-peak periods. This strategy provides a good opportunity for manufacturers to reduce their energy bills, especially for energy-intensive ones, where batch scheduling is often involved. In this thesis, several bi-objective batch scheduling problems under TOU tariffs are studied. We first investigate a single machine batch scheduling problem under TOU tariffs with the objectives of minimizing total electricity cost and makespan. This primary work is extended by further considering machine on/off switching. Finally, a parallel batch machines scheduling problem under TOU tariffs with non-identical job sizes to minimize total electricity cost and number of enabled machines is studied. For each of the considered problems, appropriate mathematical models are established, their complexities are demonstrated. Different bi-objective resolution methods are developed, including knapsack problem heuristic based ɛ-constraint method, multiple knapsack problem heuristic based ɛ-constraint method, bin packing heuristic based ɛ-constraint method and two-stage heuristic based iterative search algorithm. The performance of the proposed methods is evaluated by randomly generated instances. Extensive numerical results show that the proposed algorithms are more efficient and/or effective for the studied problems than the commercial software CPLEX

The thesis investigates the application of ice thermal storage technology to situations where the price of electricity varies continuously with instantaneous network demand. A central hypothesis is postulated in chapter 1, which states: "A variable electricity pricing structure, in which unit price continuously varies in response to instantaneous network demand, enhances the opportunities and benefits of ice thermal storage. The benefits both financial and environmental are dependent on the establishment of control and design strategies which optimise performance by matching refrigeration load with the instantaneous electricity price. " For ease of reference, the form of pricing described above is referred to in the thesis as 'real time' electricity pricing. The 'pool price' which is used to facilitate the competitive electricity awkct in England and Wales, is one of the foremost examples of real time pricing. The thesis therefore uses the electricity supply industry in the UK as its research vehicle. Notwithstanding this, the work contained in the thesis can be applied to any country which applies real time electricity pricing mechanisms. The validity of the hypothesis is assessed in the thesis through the development of a variety of numerical and computer models. These models fall into two distinct categories; those concerned with predicting and optimising the financial benefits of ice thermal storage, and those concerned with predicting and optimising the environmental benefits of ice thermal storage. Chapters 2,3 and 4 should be treated as support chapters, which equip the reader with the prerequisite knowledge necessary to understand the research work contained in the later chapters. As such, these chapters contain, respectively, a description of the electricity supply industry in the UK, a discussion of demand side management in the UK, and a description of the technology involved in ice thermal storage. The parametric study contained in chapter 4 is however an original piece of research work by the author. The models developed to evaluate and optimise the economic benefits of ice thermal storage are presented in chapters 5 and 6, and are applied to contrasting theoretical case study applications, namely an office building and a dairy. In chapter 5a 'long hand' numerical analysis technique is used. In chapter 6 this technique is rationalised and developed into a computer model for optimising both the design and control of ice storage installations in real time electricity pricing applications. The environmental studies are presented in chapter 7. These concentrate on the ability of ice thermal storage to reduce carbon dioxide emissions. Although the overall objective of the chapter is to evaluate the carbon dioxide emissions associated with ice thermal storage, the bulk of the chapter is concerned with the development of a model for predicting the carbon dioxide emissions per kWh of delivered electrical energy in England and Wales on a time related basis. The development of this 'time of day' carbon dioxide model is one of the main objectives of the thesis. Having established this model, it is then used to analyse the carbon dioxide emissions associated with the dairy case study.

Residential demand is a large and important factor of the utility load during the system peak period. And the control of residential demand can make a significant change to the system load of the utility. This research is designed to study the residential end-use appliances under various direct load control schemes. These appliances are water heaters, air conditioners, and space heaters which are the major electrical demand of the residential load. The study will apply the LOADSIM, an Electrical Power Research Institute (EPRI) load simulation program, to conduct load control strategies of these residential appliances. The LOADSIM program can be applied both for cycling and shedding control strategies during a specified control period. In this study, the cycling control is done on an air conditioner and space heater. The water heating control is performed under shedding strategy. The research has studied the appliance use of four house types under the same weather and control conditions. A total of 100,000 houses have been used in the study. These houses have the same dwelling and appliance characteristics but their house insulations are different. Diversity in house insulations gives different results in terms of load reduction and temperature change due to the load control. For example, a better-insulated house demands less electricity for its appliance than a low-insulated house. This study also uses the EPRl-LOADSIM program to estimate the load reduction and temperature change of each house type under the load control.
Master of Science

The 2008 Climate Change Act set legally-binding carbon reduction targets. Demand side management (DSM) includes energy use reduction and peak shaving and offers significant potential to reduce the amount of carbon used by the electricity grid. The demand side management (DSM) schemes that have tried to meet this challenge have been dominated by engineering-based approaches and so favour tools like automation (which aims to make shifting invisible) and pricing (which requires customer response) to shift demand. These approaches tend to focus on the tools for change and take little account of people and energy-use practices. This thesis argues that these approaches are limited and therefore unlikely to produce the level of response that will be needed in future. The thesis therefore investigates the potential for time-shifting domestic energy demand but takes a different angle by trying to understand how people use energy in their daily lives, whether this use can be shifted and some of the implications of shifting it. The centrepiece of the work is an empirical study of eleven households energy-use practices. The interdisciplinary methodology involved in-house observations, interviews, photographs, metered energy data and disruptive interventions. The data was collected in two phases. Initially, a twenty-four hour observation was carried out in each household to find out how energy was implicated in everyday practices. Next, a series of three challenges were carried out, aimed at assessing the implications of disrupting practices by time-shifting food preparation, laundry and work/ leisure. A practice theory approach is used to shift the focus of attention from appliances, tools for change, behaviour or even people, to practices. The central finding of this work is that practices were flexible. This finding is nuanced, in the light of the empirical research, by an extended discussion on the nature of practices; in particular, the relationship between practices and agency and the temporal-spatial locatedness of practices. The findings demonstrate that, in this study at least, expanding the range of demand response options was possible. The research suggests numerous possibilities for extending the potential of practices to shift in time and space, shift the energy used in practices or substitute practices for other non-energy-using practices, though there are no simple technological or behavioural fixes . More profoundly, however, the thesis concludes that infrastructures of provision , such as the electricity grid and the companies that run it, underpin and facilitate energy-use practices irrespective of the time of day and year. In this context technology-led demand response schemes may ultimately contribute to the problem they purport to solve. A more fundamental interrogation of demand and the infrastructures that serve it is therefore necessary and is almost entirely absent from the demand response debate.

Master of Science
Department of Electrical and Computer Engineering
Anil Pahwa
With the Smart Grid trend setting in, various techniques to make the existing grid smarter are being considered. The price of electricity is one of the major factors, which affects the electric utility as well as the numerous consumers connected to the grid. Therefore deciding the right price of electricity for the time of day would be an important decision to make. Consumers’ response to this change in price will impact peak demand as well as their own annual energy bill. Owning a small wind generator under the Critical Peak Pricing (CPP) and Time of Use (TOU) price-based demand response programs could be a viable option. Economic evaluation of owning a small wind generator under the two pricing schemes, namely Critical Peak Pricing (CPP) and Time of Use (TOU), is the main focus of this research. Analysis shows that adopting either of the pricing schemes will not change the annual energy bill for the consumer. Taking into account the installed cost of the turbine, it may not be significantly economical for a residential homeowner to own a small wind turbine with either of the pricing schemes in effect under the conditions assumed.

This thesis describes the trial design and analysis of the Low Carbon London (LCL) residential dynamic Time-of-Use (dToU) trial. This trial investigated the potential for dToU tariffs to deliver residential demand response to the Supplier, where it may contribute to system balancing through Supply Following (SF) actions, and to the distribution network operator (DNO), where it may be used for network Constraint Management (CM). 5,533 households from the London area participated in the trial and their consumption was measured at 30 minute resolution. 1,119 of these received the dToU tariff, which subjected them to CM and SF price events that were designed according to the specific requirements of these respective use cases. A novel, data driven, engagement ranking index was developed that allowed stratification of subsequent results into sets of the most engaged consumers, who may be indicative of a future populace that is more experienced/engaged in home energy management. Demand response (DR) was calculated relative to baseline model that used the dToU group mean demand as an input, with aggregate response levels calculated over a range of time, socio-economic and household occupancy related variables. Taking a network perspective, the reliability of CM event response was examined and two simple linear models presented as candidate predictors of response level, which was found to be consistent with an 8% reduction in demand. The network capacity contribution of residential DR was theorised to consist of two components: 'mean response' and 'variance response', and the real impact of these was investigated using the LCL gathered data. Potential risks to the network from low price induced demand spikes were explored empirically using the SF event data and the times of highest risk were identified. The extensive metadata set gathered from trial participants was processed into some 200 numerical variables. A correlation analysis was performed which was visualised using weighted correlation network graphs. A number of parameters were found to predict response level, but responsiveness (the level of deliberate engagement) could only be reliably measured by engagement rank.

Suppliers in competitive electricity markets regularly respond to prices that change hour by hour or even more frequently, but most consumers respond to price changes on a very different time scale, i. e. they observe and respond to changes in price as reflected on their monthly bills. This thesis examines mixed complementarity programming models of equilibrium that can bridge the speed of response gap between suppliers and consumers, yet adhere to the principle of marginal cost pricing of electricity. It develops a computable equilibrium model to estimate the time-of-use (TOU) prices that can be used in retail electricity markets. An optimization model for the supply side of the electricity market, combined with a price-responsive geometric distributed lagged demand function, computes the TOU prices that satisfy the equilibrium conditions. Monthly load duration curves are approximated and discretized in the context of the supplier's optimization model. The models are formulated and solved by the mixed complementarity problem approach. It is intended that the models will be useful (a) in the regular exercise of setting consumer prices (i. e. , TOU prices that reflect the marginal cost of electricity) by a regulatory body (e. g. , Ontario Energy Board) for jurisdictions (e. g. , Ontario) where consumers' prices are regulated, but suppliers offer into a competitive market, (b) for forecasting in markets without price regulation, but where consumers pay a weighted average of wholesale price, (c) in evaluation of the policies regarding time-of-use pricing compared to the single pricing, and (d) in assessment of the welfare changes due to the implementation of TOU prices.

Thesis advisor: Scott Fulford
Can smart metering program and time-of-use (TOU) prices help reduce energy consumption in New York City? Being able to track electricity consumption levels and to modify consumer usage patterns are important for policy makers to efficiently manage the energy markets. Unfortunately, no reliable and up-to-date data have been brought to bear on this question. I study the effects of time-of-use (TOU) prices and smart metering for the residents of Shanghai and I investigate further what can policy makers do in order to adapt and transfer this successful DSM experience from Shanghai to the residential sector in New York City. The primary objective of my study is to characterize the realistic short-term and long-term potential for the smart metering program in New York City given my empirical findings that the smart metering program has had brought great benefits to the residents of Shanghai. People respond to incentives; if electricity is charged at different prices throughout a day, consumers are likely to shift their usage to when it is cheaper. My findings suggest that policy makers should think harder about designing a pricing scheme that can optimize the social plus
Thesis (BA) — Boston College, 2011
Submitted to: Boston College. College of Arts and Sciences
Discipline: College Honors Program
Discipline: Economics Honors Program
Discipline: Economics

M.Com. (Business Management)
The residential demand profile for electricity shows that this segment of the market has. a great demand in the morning and early evening. Due to a shortage of generation capacity during these peak consumption periods, different strategies are now needed to persuade customers to use their electricity in the periods when there is not a great demand. One way in which this can be achieved is to give the customers a time differentiated tariff i.e. a time-of-use (TOU) tariff, whereby the customer will pay a high energy rate in the peak periods, and lower energy rates in the off-peak and standard periods. The overall goal of this study was to determine to what extent residential customers would respond to such a tariff The study covered three consumption groups i.e. customers using more than 1500 kWh per month, between 600 and 1000 kWh per month, and between 300 and 600 kWh per month. All the customers taking part in the study were direct Eskom customers. Once the customers had agreed to participate in the study, they had TOU measuring equipment installed in their homes, which measured their consumption according to the time of day it was consumed.

One way of energy conservation and Greenhouse Gases (GHG) reduction is a more rational energy consumption. However, increased energy efficiency does not always leads to the desired outcomes regarding the reduction of consumption and consequently the reduction of GHG. The effect that makes it impossible to obtain the totality of benefits due to increasing energy efficiency is known as the rebound effect. This study aims to focus on rebound effect, controlling them by setting different prices according to the consumption period. A family production function is developed incorporating the electricity consumption, dividing them between peak and off-peak periods. The function for the direct rebound effect is calculated through the elasticity of electricity service comparing to the increased energy efficiency. The consumption variations are thus obtained in each of the periods that are associated with a particular direct rebound effect. In this perspective, a new Time-of-Use tariff (TOU) dual tariff is defined wherein the prices vary in order to cancel the full rebound effect. This way, the increased energy efficiency causes a further decrease of consumption in the critical period (peak period), promoting the smooth of the load diagram. It is proposed a partial sectioning of the dispatch priority of renewables based electricity in a special regime (SR). This procedure allows freeing resources to promote greater energy efficiency. Increased energy efficiency will be accompanied by the TOU tariff we are proposing, making these actually effective efficiency gains, since the proposed tariff ensures the control of RE.
Uma das formas de conservação de energia e de redução dos Gases de Efeito Estufa (GEE) é a utilização mais racional no consumo. No entanto, nem sempre o aumento da eficiência conduz à diminuição do consumo e consequentemente à diminuição dos GEE. O efeito da não obtenção da totalidade dos benefícios decorrentes do aumento da eficiência da energia é conhecido como rebound effect. Assim, este trabalho tem como objetivo focar-se no rebound effect, controlando-o através da definição de preços diferenciados consoante o período de consumo. É desenvolvida uma função de produção familiar que incorpora o consumo de eletricidade, diferenciando-o nos períodos em pico e em fora de pico. Calcula-se a função para o rebound effect direto através da elasticidade do serviço em eletricidade em relação ao aumento da eficiência de energia. Obtém-se as variações de consumo, em cada um dos períodos, que estão associadas a determinado rebound effect direto. Nesta perspetiva, é definida uma nova tarifa time-of-use (TOU) (bi-horária) sendo que os preços variam com o objetivo de anular o rebound effect total. Desta forma, o aumento da eficiência em energia provoca uma maior diminuição do consumo no período mais crítico (período de pico), promovendo a suavização do diagrama de carga. Propõe-se corte parcial da prioridade de despacho da eletricidade de base renovável em regime especial libertando assim recursos para promover maior eficiência de energia. O aumento da eficiência em energia será acompanhado pela nova tarifa TOU, tornando esses ganhos de eficiência efetivamente eficazes, uma vez que a tarifa proposta assegura o controlo dos RE.

碩士
大同大學
電機工程學系(所)
99
Since the energy price fluctuates significantly and many countries face economic crisis, it will be an important issue to reduce expense and conserve the energy. Regarding energy conservation, including the improvement of electric equipment efficiency, it has the significant achievement. There are many successful cases and well-developed technologies of the load reduction in the peak period and the load shifting to the off-peak period. However, the study on the target value’s optimization of the controlling electric expense is very rare. In modern power system, beside the time-of-use tariff, the hardware facilities of Hi-Tech are the essential condition. The intelligent meter which is so-called smart meter has a great deal of functions, such as measurement, computation, memory, control and communication, etc. By combining the wireless communication and the information management system, the advanced metering infrastructure (AMI) has been developed successfully and adopted in many countries. This study, based on the AMI environment mentioned above, precedes electricity bill management. The factors of the usable electricity bill and the acceptable delay time should be considered. By using fuzzy theory to coordinate the cheaper electricity price and rescheduling the appliances, the electricity bill can be achieved to the expectable budget. Therefore, the advantage not only can conserve the energy and reduce the carbons, but also can achieve saving the electricity bill without sacrificing users’ comfort and convenience.

This thesis proposes equilibrium models to link the wholesale and retail electricity markets which allow for reconciliation of the differing time scales of responses of producers (e.g., hourly) and consumers (e.g., monthly) to changing prices. Electricity market equilibrium models with time of use (TOU) pricing scheme are formulated as large-scale variational inequality (VI) problems, a unified and concise approach for modeling the equilibrium. The demand response is dynamic in these models through a dependence on the lagged demand. Different market structures are examined within this context. With an illustrative example, the welfare gains/losses are analyzed after an implementation of TOU pricing scheme over the single pricing scheme. An approximation of the welfare change for this analysis is also presented. Moreover, break-up of a large supplier into smaller parts is investigated. For the illustrative examples presented in the dissertation, overall welfare gains for consumers and lower prices closer to the levels of perfect competition can be realized when the retail pricing scheme is changed from single pricing to TOU pricing. These models can be useful policy tools for regulatory bodies i) to forecast future retail prices (TOU or single prices), ii) to examine the market power exerted by suppliers and iii) to measure welfare gains/losses with different retail pricing schemes (e.g., single versus TOU pricing). With the inclusion of linearized DC network constraints into these models, the problem size grows considerably. Dantzig-Wolfe (DW) decomposition algorithm for VI problems is used to alleviate the computational burden and it also facilitates model management and maintenance. Modification of the DW decomposition algorithm and approximation of the DW master problem significantly improve the computational effort required to find the equilibrium. These algorithms are applied to a two-region energy model for Canada and a realistic Ontario electricity test system. In addition to empirical analysis, theoretical results for the convergence properties of the master problem approximation are presented for DW decomposition of VI problems.

碩士
國立臺中科技大學
企業管理系碩士班
107
The electricity cost accounts for about 4% of the annual turnover of Company F. According to the study, the saved electricity cost has been over 10 million NTD accumulatively in recent 8 years. The current total charge of Taiwan Power Company consists of 5 parts including basic charge, energy charge, power factor clause, penalty charge and others. Based on the actual electricity consumption data of Company F, this study conducted regression and variation analyses with SPSS statistical software and found out the effects of optimized contract capacity and time-of-use on electricity cost. The results show that: contract capacity is positively related to basic charge, unrelated to energy charge, negatively related to power factor clause, inversely proportional to penalty charge and quadratically related to payable total charge. The lowest position is found out, namely, the optimized contract capacity and the minimum payable total charge. The payable total charge has significant effects on contract capacity and basic charge and penalty charge. It is more advantageous for Company F to choose 3-secion time-of-use than the 2-secion time-of-use, but affected by the policy of “one regular leave day and one rest day”, the difference of time-of-use becomes insignificant. Because the optimized contract capacity is stable in recent 3 years, Company F is suggested to reduce the original contract capacity of 2,880 KW to 2,500 KW. In this way, the basic charge of about NTD 847,000 may be reduced, but the penalty charge may be occured in summer. It is expected that this study can be helpful for enterprises to optimize contract capacity and choose time-of-use.

Through the Smart Metering Initiative in the Canadian province of Ontario, all residential electricity customers will be converted from a tiered rate regime to a time-of-use (TOU) rate regime by the year 2010. Although TOU rates are designed to be cost-neutral for the average consumer, research suggests that TOU rates may affect consumers differently depending on their socioeconomic characteristics. In an effort to better understand the effects of TOU rates on lower-income and senior-headed households, a case-study in Milton was conducted between June and December of 2007. The overarching thesis question is: What are the behavioural responses to, and financial impacts of, TOU electricity rates on lower-income and senior-headed households? Nine expert interviews were conducted with Ontario professionals working in government, environmental non-profit groups, citizen advocacy organizations and affordable housing associations in order to provide context for the study. Time-differentiated electricity consumption data were then collected from 199 households from two senior housing complexes and two affordable housing complexes in Milton, Ontario between June and December 2007. A questionnaire was also sent to each household to determine some socio-economic and structural characteristics of the households. The electricity consumption data collected from the four sites suggest that the households would not benefit financially from TOU rates given electricity consumption behaviour during the period prior to the implementation of TOU rates in June 2007. Thus, they would have to change their behaviour in order to benefit financially from TOU rates. During this pre-TOU period, Site A, Site B and Site C would have paid more, on average, for their electricity under TOU rates than on tiered rates ($0.34, $0.61 and $0.15 per week, respectively). While Site D, on average, would have seen no change under TOU rates. A conservation effect was detected by comparing the electricity consumption from billing periods in 2006 to corresponding billing periods in 2007 after the implementation of TOU rates. Site A saw a conservation effect during the first corresponding billing period (35%); while Site B saw a conservation effect for three corresponding billing periods (21%, 24% and 9%). Site C saw a conservation effect for the first five corresponding billing periods (ranging from 8% to 21%), while Site D saw a conservation effect for all corresponding billing periods (ranging from 10% to 34%). The presence of a conservation effect at Site D was unexpected, particularly because households at Site D are not responsible for paying their own electricity bills. Although a conservation effect was observed after the implementation of TOU rates, the extent to which it could be attributed to the implementation of TOU rates is unclear, and should be investigated further. There was no considerable shift in the proportion of electricity consumed during each of the peak periods during the summer TOU period for Site A and Site D after the introduction of TOU rates. There was, however, a slight reduction in the portion of electricity consumed during the summer TOU period for Site B and Site C (0.2% and 0.1% per week, respectively). Due to the change in the on-, mid- and off-peak schedule from the summer TOU period to the winter TOU period, the households consume more electricity during the off-peak periods in the winter than they do during the off-peak periods in the summer (even though their patterns of consumption do not change). Similar to the pre-TOU period, during the summer post-TOU period, Site A and Site B, and Site C, on average, paid more for electricity (commodity) under TOU rates than they would have paid if they had continued on tiered rates ($0.38, $0.51 and $0.16 more per week, respectively), while Site D would have seen no change in their electricity costs. In contrast, during the winter post-TOU period several sites paid less for electricity on TOU rates than they would have if they had continued on tiered rates. Site B, Site C and Site D paid, on average, $0.78, $0.16 and $1.76 less per week, respectively. Although Site A paid more under on TOU rates during the winter post-TOU (on average $0.18 more per week), the cost was less than during the summer post-TOU period. The change in costs expressed here does not reflect any reduced costs that may have resulted from conservation. For example, if the households were shown to have a conservation effect, they might have lower electricity costs. Additionally, the changes in costs do not reflect any additional fees or charges that might be attributed to the smart meter installation and the Smart Metering Initiative (e.g., additional fees from Milton Hydro). In conclusion, TOU rates appear to be ineffective at motivating these lower-income and senior-headed households in Milton, Ontario to shift electricity from on-peak periods to off-peak periods, however, a reduction in electricity usage may be attributed to TOU rates. Further research is required to confirm these effects. It is important to note that some of the lower-income and senior-headed households in this study appeared to see an increase in their electricity bill, particularly during the summer TOU period. Lower-income and senior-headed households are thought to be less able to shift electricity consumption, therefore it is important to develop mechanisms to identify households that are at risk of bill increases.

碩士
正修科技大學
資訊管理研究所
107
Scheduling problems can be seen everywhere in life, and the scheduling discussed in this research is to simulate manufacturing order scheduling. In the past, many dispatching companies did not consider capacity limitations, which caused the tardiness. This research explores the order acceptance scheduling problem (OAS), which considers the due day under the capacity constraints toward higher revenue. In recent years, many researchers have changed the study of environmental pollution and time-of-use electricity cost (TOU). It means that the cost of electricity has made a heavy burden on enterprises. Because no study combines the OAS with the TOU cost, it is the significant contribution of this research. We employed the model and benchmark instances from OĞUZ et al.[41], and add the TOU constraints and power consumptions into the model and instances, respectively. In order to solve this new problem, a genetic algorithm with the multi-layer perceptron (MLP) neural network is developed. We use MLP predicts the fitness function of the chromosomes and guide the evolution process. CPLEX is used to provide the upper bound value to validate the effectiveness of the proposed algorithm compared to stand genetic algorithms (SGA). We found the proposed algorithm founds better solutions than SGA in some instances, even though the computational time is higher.

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in ful lment of the requirements for the degree of Master of Science in Engineering. Johannesburg, 2015
The work presented extends and contributes to research in Non-Intrusive Load Monitoring (NILM), focussing on steady-state and transient power measurement disaggregation techniques for circuits containing household ap- pliances. Although previous work in this area has produced and evaluated a wide range of NILM approaches, much of it has involved the use of datasets captured from real-world household implementations. In such cases, the lack of accurate ground truth data makes it di cult to assess disaggregation tech- niques. In the research presented, three NILM techniques are comparatively evaluated using measurements from typical household appliances assembled within a laboratory environment, where accurate ground truth data could be compiled to complement the measurements. This allows for the accu- racy of the various disaggregation approaches to be precisely evaluated. It is demonstrated that the correlation of transient event edges in aggregated power measurements to individual appliance transient exemplars performs better than the matching of steady-state power levels against individual ap- pliance state combinations. Furthermore, the transient approach is shown to be the most appropriate technique for further development.
MT2017