Littérature scientifique sur le sujet « Sub-Regional electricity demand »

The BBIN sub-region - Bangladesh, Bhutan, India, and Nepal - are witnessing a significant surge in electricity demand, accompanied by an uneven distribution of resources and consumption patterns across the region. Optimizing the unevenly distributed energy resources through a harmonized generation mix, tailored to the distinct load patterns and demands of individual nations, creates opportunities for enhanced electricity trade through multilateral cooperation. To facilitate this, the region has been conceptualized into four nodes connected by five interconnections: Bangladesh-Bhutan, Bangladesh-India, Bangladesh-Nepal, Bhutan-India, and India. While electricity trade has existed historically, a systematic approach to allocating the costs of cross-border transmission infrastructure has not been adopted. This study quantifies the benefits of regional electricity trade and proposes cost-sharing mechanisms using methodologies rooted in Game Theory, particularly the Shapley Value, alongside cooperative game theory, to ensure equitable cost distribution. A dynamic optimal power generation mix model reveals that the grand coalition - where all nations cooperate - is the most efficient configuration. In this scenario, India incurs the highest transmission line cost, reflective of its substantial size and electricity demand.

In sub-Saharan Africa (SSA), diets are largely based on cereal or root staple crops. Together with socio-cultural change, economic and demographic growth could boost the demand for meat, with significant environmental repercussions. We model meat consumption pathways to 2050 for SSA based on several scenarios calibrated on historical demand drivers. To assess the consequent environmental impact, we adopt an environmentally-extended input-output (EEIO) framework and apply it on the EXIOBASE 3.3 hybrid tables. We find that, depending on the interplay of resources efficiency and demand growth, by 2050 the growth in meat consumption in SSA could cause a growth in greenhouse gases emissions of 1.4 [0.9–1.9] Gt CO2e/yr (~175% of current regional agriculture-related emissions), which is an extension of cropping and grazing-related land of 15 [12.5–21] · 106 km2 (one quarter of today’s global agricultural land), the consumption of an additional 36 [29–47] Gm3/yr of blue water (nearly doubling the current regional agricultural consumption), an eutrophication potential growth of 7.6 [4.9–9.5] t PO4e/yr, and the consumption of additional 0.9 [0.5–1.4] EJ/yr of fossil fuels and 49 [32–73] TWh/yr of electricity. These results suggest that—in the absence of significant improvements in the regional sectoral resource efficiency—meat demand growth in SSA is bound to become a major global sustainability challenge. In addition, we show that a partial substitution of the protein intake from the expected growth in meat consumption with plant-based alternatives carries additional significant potential for mitigating environmental impacts. The policies affecting both farming practices and dietary choices will thus have a significant impact on the SSA and global environmental flows.

The analysis of the main directions of renewable energy in Africa, as a factor in sustainable development and reduction of greenhouse gas emissions is performed. The ecological problems of the modern and prospective development of the energy complex of African countries are considered. For African countries the issue of ensuring reliable and environmentally friendly access to electricity for the population is extremely acute. It is shown, that the electricity demand for industry in Sub-Saharan Africa the most problematic region is growing on a very large scale. The construction of new large coal-fired thermal power plants in the required volumes will lead to serious environmental and climatic consequences. The study of regional data allowed us to conclude that PV solar systems are of priority importance for increasing people’s access to electricity in rural SubSaharan Africa. Based on numerous materials from international energy structures the estimates and calculations of volumes of reduction of greenhouse gas emissions due to the use of renewable energy sources as an alternative to carbon fuel are carried out. The study has shown that of particularly great importance for reducing CO2 emissions in Kenya is the development of geothermal energy.

It is still possible to comply with the Paris Climate Agreement to maintain a global temperature ‘well below +2.0 °C’ above pre-industrial levels. We present two global non-overshoot pathways (+2.0 °C and +1.5 °C) with regional decarbonization targets for the four primary energy sectors—power, heating, transportation, and industry—in 5-year steps to 2050. We use normative scenarios to illustrate the effects of efficiency measures and renewable energy use, describe the roles of increased electrification of the final energy demand and synthetic fuels, and quantify the resulting electricity load increases for 72 sub-regions. Non-energy scenarios include a phase-out of net emissions from agriculture, forestry, and other land uses, reductions in non-carbon greenhouse gases, and land restoration to scale up atmospheric CO2 removal, estimated at −377 Gt CO2 to 2100. An estimate of the COVID-19 effects on the global energy demand is included and a sensitivity analysis describes the impacts if implementation is delayed by 5, 7, or 10 years, which would significantly reduce the likelihood of achieving the 1.5 °C goal. The analysis applies a model network consisting of energy system, power system, transport, land-use, and climate models.

Abstract. Water scarcity conditions over the 21st century both globally and regionally are assessed in the context of climate change, by estimating both water availability and water demand within the Global Change Assessment Model (GCAM), a leading community integrated assessment model of energy, agriculture, climate, and water. To quantify changes in future water availability, a new gridded water-balance global hydrologic model – namely, the Global Water Availability Model (GWAM) – is developed and evaluated. Global water demands for six major demand sectors (irrigation, livestock, domestic, electricity generation, primary energy production, and manufacturing) are modeled in GCAM at the regional scale (14 geopolitical regions, 151 sub-regions) and then spatially downscaled to 0.5° × 0.5° resolution to match the scale of GWAM. Using a baseline scenario (i.e., no climate change mitigation policy) with radiative forcing reaching 8.8 W m−2 (equivalent to the SRES A1Fi emission scenario) and a global population of 14 billion by 2095, global annual water demand grows from about 9–10% of total annual renewable freshwater in 2005 to about 32–37% by 2095. This results in more than half of the world population living under extreme water scarcity by the end of the 21st century. Regionally, the demand for water exceeds the amount of water availability in two GCAM regions, the Middle East and India. Additionally, in years 2050 and 2095 36% (28%) and 44% (39%) of the global population, respectively is projected to live in grid cells (in basins) that will experience greater water demands than the amount of available water in a year (i.e., the water scarcity index (WSI) > 1.0). This study implies an increasingly prominent role for water in future human decisions, and highlights the importance of including water in integrated assessment of global change.

In this article, a systematic literature review of 419 articles on energy demand modeling, published between 2015 and 2020, is presented. This provides researchers with an exhaustive overview of the examined literature and classification of techniques for energy demand modeling. Unlike in existing literature reviews, in this comprehensive study all of the following aspects of energy demand models are analyzed: techniques, prediction accuracy, inputs, energy carrier, sector, temporal horizon, and spatial granularity. Readers benefit from easy access to a broad literature base and find decision support when choosing suitable data-model combinations for their projects. Results have been compiled in comprehensive figures and tables, providing a structured summary of the literature, and containing direct references to the analyzed articles. Drawbacks of techniques are discussed as well as countermeasures. The results show that among the articles, machine learning (ML) techniques are used the most, are mainly applied to short-term electricity forecasting on a regional level and rely on historic load as their main data source. Engineering-based models are less dependent on historic load data and cover appliance consumption on long temporal horizons. Metaheuristic and uncertainty techniques are often used in hybrid models. Statistical techniques are frequently used for energy demand modeling as well and often serve as benchmarks for other techniques. Among the articles, the accuracy measured by mean average percentage error (MAPE) proved to be on similar levels for all techniques. This review eases the reader into the subject matter by presenting the emphases that have been made in the current literature, suggesting future research directions, and providing the basis for quantitative testing of hypotheses regarding applicability and dominance of specific methods for sub-categories of demand modeling.

The energy conversion units and energy storage equipment connected to the multi-energy system are becoming diversified, and the uncertain factors brought by distributed wind power and photovoltaic power generation make the system energy flow structure more complex, which brings great difficulties to the modeling and application of traditional energy hub modeling methods. This study deeply analyzes the multi-energy flow coupling structure and operation mechanism of multi-energy systems, and carries out the power flow calculation and analysis of multi-energy systems based on an energy hub, so as to ensure the safe and stable operation of regional energy. Based on the physical characteristics of energy systems such as power systems, thermal systems, and gas systems, this article studies the comprehensive power flow model including the electric-gas-thermal multi-energy coupling network and proposes the power flow decomposition of the energy supply subsystem and its applicable equation based on Newton–Raphson method. The effectiveness of the proposed method under different operation modes is verified by case studies. The calculation results show that under constant load, the energy hub running in fixing thermal by electricity (FEL) and fixing electricity by thermal (FTL) mode has little influence on the voltage of each node in the power sub-network. Within the constraint range, the natural gas flow obtained from the natural gas subsystem is coupled with the power subsystem to meet the load demand. The influence on the power flow at each node of the heat network is not obvious.

The economic impacts of the German Renewable Energy Act (EEG) are of considerable importance for the discussion of the energy transition in Germany (Energiewende). The Energiewende implies structural changes of the energy system by deploying Renewable Energy (and energy efficiency) Technologies (RET), but it also may induce structural changes for the overall economy, with uneven effects on a sub-national level. North-Rhine Westphalia (NRW) is an ideal case to study such regional disparities, since this federal state has scarce per-capita renewable energy sources, whereas it stands out for its energy intensive industry and fossil-fuel based power plants. In order to support renewable energy policies, mostly gross impact assessments of RET deployment have been carried out both on national and regional levels. By definition, such analyses result in positive assessments, since only expansionary effects resulting from additional demand for RET are accounted for. This paper, in contrast, presents a net impact assessment of the EEG on the NRW economy of both expansionary and contractionary effects. The latter consist of negative income effects, increased production costs and, the crowding-out of conventional energy due to the renewable energy financing mechanism (i.e., electricity surcharge), as well as its preferential status for feed-in. Our findings show how North-Rhine Westphalia, with regard to the operation of RET, suffers disproportionally from negative effects in relation to the value addition of its economy in comparison to the rest the country, whereas it benefits marginally from the production of such facilities.

Abstract. Water scarcity conditions over the 21st century both globally and regionally are assessed in the context of climate change and climate mitigation policies, by estimating both water availability and water demand within the Global Change Assessment Model (GCAM), a leading community-integrated assessment model of energy, agriculture, climate, and water. To quantify changes in future water availability, a new gridded water-balance global hydrologic model – namely, the Global Water Availability Model (GWAM) – is developed and evaluated. Global water demands for six major demand sectors (irrigation, livestock, domestic, electricity generation, primary energy production, and manufacturing) are modeled in GCAM at the regional scale (14 geopolitical regions, 151 sub-regions) and then spatially downscaled to 0.5° × 0.5° resolution to match the scale of GWAM. Using a baseline scenario (i.e., no climate change mitigation policy) with radiative forcing reaching 8.8 W m−2 (equivalent to the SRES A1Fi emission scenario) and three climate policy scenarios with increasing mitigation stringency of 7.7, 5.5, and 4.2 W m−2 (equivalent to the SRES A2, B2, and B1 emission scenarios, respectively), we investigate the effects of emission mitigation policies on water scarcity. Two carbon tax regimes (a universal carbon tax (UCT) which includes land use change emissions, and a fossil fuel and industrial emissions carbon tax (FFICT) which excludes land use change emissions) are analyzed. The baseline scenario results in more than half of the world population living under extreme water scarcity by the end of the 21st century. Additionally, in years 2050 and 2095, 36% (28%) and 44% (39%) of the global population, respectively, is projected to live in grid cells (in basins) that will experience greater water demands than the amount of available water in a year (i.e., the water scarcity index (WSI) > 1.0). When comparing the climate policy scenarios to the baseline scenario while maintaining the same baseline socioeconomic assumptions, water scarcity declines under a UCT mitigation policy but increases with a FFICT mitigation scenario by the year 2095, particularly with more stringent climate mitigation targets. Under the FFICT scenario, water scarcity is projected to increase, driven by higher water demands for bio-energy crops.

Abstract As regional grids increase penetrations of variable renewable electricity (VRE) sources, demand-side management (DSM) presents an opportunity to reduce electricity-related emissions by shifting consumption patterns in a way that leverages the large diurnal fluctuations in the emissions intensity of the electricity fleet. Here we explore residential precooling, a type of DSM designed to shift the timing of air-conditioning (AC) loads from high-demand periods to periods earlier in the day, as a strategy to reduce peak period demand, CO2 emissions, and residential electricity costs in the grid operated by the California Independent System Operator (CAISO). CAISO provides an interesting case study because it generally has high solar generation during the day that is replaced by fast-ramping natural gas generators when it drops off suddenly in the early evening. Hence, CAISO moves from a fleet of generators that are primarily clean and cheap to a generation fleet that is disproportionately emissions-intensive and expensive over a short period of time, creating an attractive opportunity for precooling. We use EnergyPlus to simulate 480 distinct precooling schedules for four single-family homes across California’s 16 building climate zones. We find that precooling a house during summer months in the climate zone characterizing Downtown Los Angeles can reduce peak period electricity consumption by 1–4 kWh d−1 and cooling-related CO2 emissions by as much as 0.3 kg CO2 d−1 depending on single-family home design. We report results across climate zone and single-family home design and show that precooling can be used to achieve simultaneous reductions in emissions, residential electricity costs, and peak period electricity consumption for a variety of single-family homes and locations across California.

Cette thèse explore le rôle de la complémentarité éolienne dans la gestion de l'intermittence à l'échelle infrarégionale en France. À travers une approche empirique et statistique, ce travail examine la manière dont la distribution géographique des parcs éoliens peut contribuer à atténuer les fluctuations de production dues au caractère variable et volatile du vent, afin de favoriser une couverture plus stable de la demande électrique. La première contribution de cette recherche réside dans l'utilisation de données réelles de vitesse du vent, offrant une meilleure précision par rapport aux données satellitaires et permettant une identification fine des sites complémentaires au sein de la France. En exploitant des méthodes de classification des séries temporelles, cette thèse a permis de déterminer des clusters de sites éoliens négativement corrélés, indiquant un potentiel de complémentarité qui améliore la disponibilité de l'énergie éolienne et réduit les épisodes d'intermittence. Ensuite, l'étude intègre une analyse des contraintes techniques, environnementales et économiques des parcs éoliens, soulignant la faisabilité de cette complémentarité. L'évaluation économique des combinaisons de sites montre que ces configurations sont non seulement viables mais aussi abordables en termes de coût actualisé de l'électricité (LCOE). Les résultats démontrent que les parcs éoliens complémentaires augmentent la couverture de la demande d'au moins 10 % par rapport à un site unique, allant jusqu'à un taux de couverture de 30%. Enfin, l'analyse de séries temporelles est utilisée pour quantifier les effets dynamiques de la complémentarité sur la production et la demande résiduelle, en intégrant des tests de causalité de Granger dépendant du temps (TVGC). Cette approche révèle que la complémentarité spatio-temporelle du vent réduit la demande résiduelle, en particulier lors des périodes de forte demande, comme en hiver, et souligne l'importance d'une prise en compte saisonnière, dans la perspective, d'une planification éolienne efficace. En somme, ce travail de recherche démontre que la complémentarité éolienne infrarégionale, fondée sur une analyse fine des sites et intégrant des données empiriques, peut jouer un rôle stratégique dans la gestion de l'intermittence. Ces résultats apportent un éclairage pertinent pour l'élaboration de politiques énergétiques locales, voire globales, notamment dans le cadre des Zones d'Accélération des Énergies Renouvelables en France
This thesis explores the role of wind complementarity in managing intermittency at the sub-regional level in France. Through an empirical and statistical approach, this work examines how the geographical distribution of wind farms can help mitigate production fluctuations due to the variable and volatile nature of wind, thus promoting a more stable coverage of electricity demand. The first contribution of this research lies in the use of real wind speed data, offering greater precision compared to satellite data and enabling a fine-tuned identification of complementary sites within France. By leveraging time series classification methods, this thesis identified clusters of negatively correlated wind sites, indicating a complementarity potential that enhances wind energy availability and reduces intermittency events. The study then incorporates an analysis of the technical, environmental, and economic constraints of wind farms, highlighting the feasibility of this complementarity. The economic evaluation of site combinations shows that these configurations are not only viable but also affordable in terms of the levelized cost of electricity (LCOE). The results demonstrate that complementary wind farms increase demand coverage by at least 10% compared to a single site, reaching up to a 30% coverage rate.Finally, time-series analysis is used to quantify the dynamic effects of complementarity on production and residual demand, integrating time-varying Granger causality tests (TVGC). This approach reveals that the spatio-temporal complementarity of wind reduces residual demand, especially during periods of high demand, such as in winter, and underscores the importance of seasonal consideration in effective wind planning. In summary, this research demonstrates that sub-regional wind complementarity, based on a refined site analysis and empirical data, can play a strategic role in managing intermittency. These findings provide relevant insights for developing local, and potentially global, energy policies, especially within the framework of Renewable Energy Acceleration Zones in France

The agricultural operations in India are suffering from a serious problem of shortage of electrical power on one side and economic and effective disposal of agriwaste stuff on the other. India being agriculture based country, 70% of its main income (share in GDP) comes from agriculture sector. Any enhancement of income from this sector is based upon adequate supply of basic inputs in this sector. Regular and adequate power supply is one such input. But, the position of power supply in our country defies both these characteristics. With a major portion of power produced being sent to the industrial and urban consumers, there is a perennial shortage of power in the agriculture sector. Consequently, there is an emergent need to produce more power in order to fulfil the needs of this sector effectively. One way of accomplishing this is setting up captive, preferably rural based, small power generation plants. In these power plants, instead of water-head, diesel oil or coal, we can use agri-residue to produce electricity. One such power plant (1–2 MW capacity) can satisfy the power need of 25 to 40 nearby villages. The agriwaste like rice straw, sugarcane-trash, coir-pith, peanut shells, wheat stalks & straw, cottonseed, stalks and husk, soyabean stalks, maize stalks & cobs, sorghum. Bagasse, wallnut shells, sunflower seeds, shells, hulls and kernels and coconut husk, wastewood and saw dust can be fruitfully utilized in power generation. This stuff is otherwise a waste and liability and consumes a lot of effort on its disposal; in addition to being a fire and health hazard. Agriwaste stuff which at present is available in abundance and prospects of its utilization in producing energy are enormous. This material can be procured at reasonably low rates from the farmers who will thus be benefited economically, apart from being relieved of the responsibility of its disposal. Agri-residue has traditionally been a major source of heat energy in rural areas in India. It is a valuable fuel even in the sub-urban areas. Inspite of rapid increase in the supply of, access lo and use of fossil fuels, agri-residue is likely to continue to play an important role, in the foreseeable future. Therefore, developing and promoting techno-economically-viable technologies to utilize agri-residue efficiently should be a persuit of high priority. Though there is no authentic data available with regard to the exact quantity of agricultural and agro-industrial residues, its rough estimate has been put at about 350 mt per annum. It is also estimated that the total cattle refuse generated is nearly 250 mt per year. Further, nearly 20% of the total land is under forest cover, which produces approximately 50 mt of fuel wood and with associated forest waste of about 5 mt.(1). Taking into account the utilization of even a portion (say 30%) of this agri-residue & agro-industrial waste as well as energy plantation on one million hectare (mha) of wastelands for power generation through bioenergy technologies, a potential of some 18000 MW of power has been estimated. From the foregoing, it is clear that there is an enormous untapped potential for energy generation from agri-residue. What is required is an immediate and urgent intensification of dedicated efforts in this field, with a view to bringing down the unit energy cost and improving efficiency and reliability of agri-waste production, conversion and utilisation, leading to subsequent saving of fossil fuels for other pressing applications. The new initiatives in national energy policy are most urgently needed to accelerate the social and economic development of the rural areas. It demands a substantial increase in production and consumption of energy for productive purposes. Such initiatives are vital for promoting the goals of sustainability. cleaner production and reduction of long-term risks of environmental pollution and consequent adverse climatic changes in future. A much needed significant social, economic and industrial development has yet to take place in large parts of rural India; be it North, West, East or South. It can be well appreciated that a conscious management of agri-residue, which is otherwise a serious liability of the farmer, through its economic conversion into electric power can offer a reasonably viable solution to our developmental needs. This vision will have to be converted into a reality within a decade or so through dedicated and planned R&D work in this area. There is a shimmering promise that the whole process of harvesting, collection, transport and economic processing and utilisation of agri-waste can be made technically and economically more viable in future. Thus, the foregoing paras amply highlight the value of agri-residue as a prospective source of electric power, particularly for supplementing the main grid during the lean supply periods or peak load hours and also for serving the remote areas in the form of stand-alone units giving a boost to decentralised power supply. This approach and option seems to be positive in view of its potential contribution to our economic and social development. No doubt, this initiative needs to be backed and perused rigorously for removing regional imbalances as well as strengthening National economy. This paper reviews the current situation with regards to generation of agriwaste and its prospects of economic conversion into electrical power, technologies presently available for this purpose, and the problems faced in such efforts. It emphasizes the need for an integrated approach to devise ways and means for generating electrical power from agriwaste; keeping in mind the requirements of cleaner production and environmental protection so that the initiative leads to a total solution.