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Global energy consumption is growing rapidly, with the frequency and intensity of extreme events constantly increasing, posing a long-term threat to power supply and consumption. Therefore, analyzing the spatiotemporal characteristics of electricity consumption and quantitatively assessing the impact of extreme events on electricity consumption are of great significance. Based on fine-grained electricity consumption data from Europe for the years 2019–2022, this paper employs a data mining perspective and four methods including Z-score, Isolation Forest, Local Outlier Factor, and Autoencoder to detect abnormal electricity consumption during extreme events. Additionally, it combines indicators such as elastic loss, vulnerability, and duration to measure the impact of extreme events on electricity consumption. It is found that low temperatures could lead to abrupt changes in electricity consumption, with Northern Europe being more significantly affected by low temperatures. The COVID-19 pandemic had the most significant impact on electricity consumption in Europe, with the middle part of Europe being the hardest hit during the first wave of the pandemic. Electricity anomalies during the pandemic period were related to national pandemic control policies and exhibited some lag. High temperatures persisted for a longer duration in the middle part of Europe. [ABSTRACT FROM AUTHOR]

Energy efficiency programs funded by utility customers provide an electricity resource in most U.S. states, but their scale and cost of saving electricity varies significantly by state. In this paper, we explore the drivers of the cost of saved electricity in these programs with an econometric model and nearly a decade of data reported by efficiency program administrators. We found strong evidence for economies of scale and weak evidence for diseconomies of scale, which suggests that states with low levels of efficiency savings relative to retail sales can increase the size of their efficiency programs without large increases to the cost of saved electricity. We discuss examples of energy efficiency forecasting and potential modeling in light our econometric analysis and identify methodological improvements relevant to utilities and grid operators. This paper provides insights into the economics of customer-funded efficiency programs that will support regulators, utilities, and policymakers to utilize energy efficiency as a resource. [ABSTRACT FROM AUTHOR]

The energy use of residues from agriculture, forestry, and solid waste can foster the transition towards a more renewable energy supply. This paper analyzes the energy potential of the above-mentioned sources for energy applications in Kosovo. The analysis is based on statistical data from different studies and reports, analyzing and calculating them to determine the theoretical and energy biomass potential. Kosovo can increase its self-sufficiency by taking advantage of its rich but under-utilized potential of biomass energy sources. This is a novelty study in this area, considering Kosovo lignite-dominated heat energy and electricity consumption and the available special literature. According to our estimates, the theoretical potential is 6.13 million tons/year, while the biomass energy potential should be around 4.57 million tons/year, including approximately 74.6% of biomass, which can be used for energy needs (heating and electricity). Based on the data and calculations, the available and usable potential shows biomass as an energy source with high potential in Kosovo; its share is very low, but it is reasonable to grow for both environmental and economic reasons. [ABSTRACT FROM AUTHOR]

Background: The transition to carbon neutral mobility will require a lot of carbon neutral energy, but a lot of space as well. In many countries, it will be a challenge to find this space or to import enough energy. Land use indicators related to sustainable mobility usually focus on space for transport infrastructure and parking, i.e. direct land use, and do not include energy supply. Existing literature on the emerging research field of 'energy landscapes' has not covered the transport sector. Objective: The aim of this paper is to estimate the order of magnitude of land or sea area required for carbon neutral mobility. Method: In a well-to-wheel analysis, we investigate the land use for the production, transport, storage, distribution, and charging/refuelling of carbon neutral energy carriers for various modes of transport. The analysis focuses on the Netherlands, but part of the results are expected to be broadly applicable to other countries as well. Findings: The results show that electricity from wind or solar energy supplied to electric vehicles is the most space efficient. Use of hydrogen and synthetic fuels in vehicles takes 2–5 times more land, while use of biofuels from energy crops takes 100 times more land compared to the electricity route. We also conclude that the indirect land use for energy supply for carbon neutral road transport in the Netherlands is in the same order of magnitude as the current direct land use of road mobility. [ABSTRACT FROM AUTHOR]

The purpose of the following article is to present the situation of the energy market from a household perspective between 2010 and 2020 in selected EU countries (the group of member states which joined EU after 2004). The selected countries when joining the EU had similar economic indicators and to some extent were similar in other macro-economic situations (personal income, unemployment rate, GDP level and annual growth). This article analyzes the past and current situation of the household ability expenditure on electricity and energy resources (petrol—eurosuper 95 and diesel and natural gas), taking into account price, tax conditions and the real possibility to purchase the analyzed energy sources (based on annual net salaries). The paper includes the conclusions and prospects for the future. The main objective of the study is to determine the ability amount of expenditure on electricity, natural gas and liquid fuels by household in the countries that joined the European Union after 2004. The specific objectives of the work include: the evolution of retail prices of energy sources in those countries and prices of electricity, natural gas and liquid fuels—petrol and diesel oil—in the research period from 2010 to 2020. The element that influences the final price, as assessed in this paper, is the share of taxes and compulsory charges imposed by the EU countries covered in this study. The result of the study presented inter alia that energy consumption structure did not change significantly, electricity prices were steadily growing in the countries under assessment, the use of liquid fuels—petrol and diesel oil—in the countries under study, grew over the study period. Furthermore, prices of fuel fluctuated over the period from 2010 to 2020 and during the COVID-19 pandemic, which broke out in March 2020, but did not cause any significant changes in the prices of energy carriers in the analyzed period, apart from the declines in the prices of eurosuper 95 and diesel. [ABSTRACT FROM AUTHOR]

Current power systems face significant challenges in supporting large-scale access to new energy sources, and the potential of existing flexible resources needs to be fully explored from the power supply, grid, and customer perspectives. This paper proposes a multi-objective electricity consumption optimization strategy considering the correlation between equipment and electricity consumption. It constructs a multi-objective electricity consumption optimization model that considers the correlation between equipment and electricity consumption to maximize economy and comfort. The results show that the proposed method can accurately assess the potential for electricity consumption optimization and obtain an optimal multi-objective electricity consumption strategy based on customers' actual electricity consumption demand. [ABSTRACT FROM AUTHOR]

This work presents Combined Heat and Power (CHP) gas engine factory as one of the possible solutions for cogeneration in the industry which has high values of electrical and total efficiency, and the electrical efficiency relatively changes little with the change in power of the plant. The cost‐effectiveness of such a plant is significant to the supply of industrial consumer electricity from the grid, and heat from the factory boiler. A problem in assessing the cost‐effectiveness of using such a plant is that it uses more fuel here than in the case of energy supply from the boiler room factory and electrical distribution networks. In this case, the price of fuel and electricity as well as the level of placement of thermal energy, as shown here, determines the cost‐effectiveness of the plant. The final decision on the application of the CHP plant must be preceded by a careful technical analysis of the plant and energy system as well as a financial analysis of the selected case. Due to errors that occurred in practice, this paper aimed to point out the basic problems in choosing the power and mode of operation of these plants. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks (WSNs) have been employed in various real-time applications and addressed fundamental issues, such as limited power resources and network life. Several sensor nodes in a WSN monitor the actual world and relay discovered data to base stations. The biggest issue with WSN is that the sensors have a limited lifetime and use much electricity to relay data to the base station. This paper proposes an improved PSO-based Enhanced Distributed Energy Efficient Clustering (EDEEC) algorithm to extend the network's life and reduce power consumption. Clustering is the process of forming groups of sensor nodes. The cluster aims to improve the network's scalability, energy efficiency, and other characteristics. The particle swarm optimization algorithm is modified to obtain energyefficient WSNs. The assessment is based on the essential WSN characteristics, including network lifetime and energy efficiency (power consumption). Compared to LEACH, HEED, and DEEC, our proposed IPSO-EDEEC uses less energy. [ABSTRACT FROM AUTHOR]

The introduction of the new round of electricity reform policies has made the electricity sales companies' trading environment increasingly complex. In the medium- and long-term market and spot market, following the new policy-oriented optimization of trading decisions is the focus of electricity sales companies. The main objective of this study is to consider the impact of the latest policies of China's current electricity reform on each subject of electricity trading and to propose a method for electricity sales companies to make optimal decisions on renewable energy source (RES) power and conventional energy source (CES) power mixed with power trading in the medium- and long-term and spot markets to improve the efficiency of electricity market trading, promoting the consumption of renewable energy and helping the synergistic development of the electricity market and the tradable green certificate (TGC) market. This paper first discusses the impact of the new electricity reform policies on the transactions of various subjects in the electricity market and constructs the model of the consumer utility function, the profit model of an electricity sales company, and the profit model of power generators with energy storage. Considering the complex power supply and demand relationship among the various subjects of the electricity market, a game model is established for the decision on mixed trading between the medium- and long-term market, the spot market, and the tradable green certificate market to minimize the comprehensive power purchase cost of an electricity sales company. To reduce the decision-making risk caused by the uncertainty of spot price, the prophet model is used to predict the spot price; finally, through the analysis of the decision-making model of the electricity sales companies, the optimal transaction decisions of the electricity sales companies in different trading periods and different scenarios are solved. The test results show that the proposed model can significantly improve the profitability of the electricity sales companies and provide a decision-making reference for electricity sales companies to participate in the medium- and long-term market and spot market. [ABSTRACT FROM AUTHOR]

Renewable energy resource utilisation is becoming more prevalent in society and can be a sustainable method to meet rising energy demand and consumption. The International Renewable Energy Agency reports that presently, approximately 33% of total electricity output around the world is from renewable energy sources. However, in Nigeria, the World Bank reported this figure as 18.2% in 2015. It is important to understand how Nigeria can raise this average as the world moves towards less use of fossil fuels. Therefore, the aim of this work was to provide a review of the established literature, which can then be used to support the development of renewable energy systems in Nigeria. The methodology employed for the study of the literature involved a systematic review method, including identification, screening, eligibility and inclusion criterium steps. Understanding the national energy landscape is essential to support potential projects, and consequently, energy supply, demand and consumption in Nigeria are observed. The review examined renewable energy sources in Nigeria with a focus on solar and biomass/bioenergy. The levelised cost of electricity from renewable technologies was analysed, and the paper identified and evaluated past projects centered on solar and biomass, presenting three main case studies. The results indicate that solar and biomass have the most potential for energy generation in Nigeria, with 4–6.5 kWh/m2 of solar irradiation available per day and approximately 2.3 × 109 GJ bioenergy potential per year. However, solar PV is currently of most interest in Nigeria due to the lower cost of on-grid solar PV electricity, which can comfortably compete with fossil fuels. Nevertheless, costs still need to be lowered to compete fully. Finally, the findings also indicate that there is an omission in the literature surrounding the existing renewable projects and technologies in Nigeria. [ABSTRACT FROM AUTHOR]

Rural and remote regions of developing economies face a serious scarcity of reliable energy supply. Focus on providing electricity through renewable and off grid energy resources is becoming increasingly popular. Off the grid or decentralized renewable energy typically considers either solar or small hydro power to fill the supply deficit and increase in demand with time is generally ignored. This paper proposes a hybrid technology mix of various renewable energy options for two remote villages located in Darma valley of Uttarakhand state in the Indian Himalayan Region. Since the villages are at an average height of 3500 m amsl, they are inaccessible during winters due to heavy snowfall. Therefore, decentralized energy could be the most cost effective solution to provide electricity. This paper estimates the energy demand of these villages and identifies the most optimum off the grid solutions, and compares it with grid connected electricity supply using hybrid optimization model for electric renewables. Micro hydro energy generation was found to be the most cost effective and techno-economically viable solution. This paper also evaluates the barriers faced by remote Himalayan villages so as to achieve reliable application of the results of this study. [ABSTRACT FROM AUTHOR]

Purpose – This paper aims to detect abnormal energy uses which relate to undetected consumption, thefts, measurement errors, etc. The detection of irregular power consumption, with variation in irregularities, helps the electric utilities in planning and making strategies to transfer reliable and efficient electricity from generators to the end-users. Abnormal peak load demand is a kind of aberration that needs to be detected. Design/methodology/approach – This paper proposes a Density-Based Micro Spatial Clustering of Applications with Noise (DBMSCAN) clustering algorithm, which is implemented for identification of ranked irregular electricity consumption and occurrence of peak and valley loads. In the proposed algorithm, two parameters, a and ß, are introduced, and, on tuning of these parameters, after setting of global parameters, a varied number of micro-clusters and ranked irregular consumptions, respectively, are obtained. An approach is incorporated with the introduction of a new term Irregularity Variance in the suggested algorithm to find variation in the irregular consumptions according to anomalous behaviors. Findings – No set of global parameters in DBSCAN is found in clustering of load pattern data of a practical system as the data. The proposed DBMSCAN approach finds clustering results and ranked irregular consumption such as different types of abnormal peak demands, sudden change in the demand, nearly zero demand, etc. with computational ease without any iterative control method. Originality/value – The DBMSCAN can be applied on any data set to find ranked outliers. It is an unsupervised approach of clustering technique to find the clustering results and ranked irregular consumptions while focusing on the analysis of and variations in anomalous behaviors in electricity consumption. [ABSTRACT FROM AUTHOR]

A linear function submission-based double auction (LFS-DA) mechanism for a regional electricity network is proposed in this paper. Each agent in the network is equipped with a battery and a generator. Each agent simultaneously becomes a producer and consumer of electricity, i.e., a prosumer, and trades electricity in the regional market at a variable price. In the LFS-DA, each agent uses linear demand and supply functions when they submit bids and asks to an auctioneer in the regional market. The LFS-DA can achieve an exact balance between electricity demand and supply for each time slot throughout the learning phase and was shown capable of solving the primal problem of maximizing the social welfare of the network without any central price setter, e.g., a utility or a large electricity company, in contrast with conventional real-time pricing (RTP). This paper presents a clarification of the relationship between the RTP algorithm derived on the basis of a dual decomposition framework and LFS-DA. Specifically, we proved that the changes in the price profile of the LFS-DA mechanism are equal to those achieved by the RTP mechanism derived from the dual decomposition framework, except for a constant factor. [ABSTRACT FROM AUTHOR]

Many countries have some kind of energy-system transformation either planned or ongoing for various reasons, such as to curb carbon emissions or to compensate for the phasing out of nuclear energy. One important component of these transformations is the overall reduction in energy demand. It is generally acknowledged that the domestic sector represents a large share of total energy consumption in many countries. Increased energy efficiency is one factor that reduces energy demand, but behavioral approaches (known as “sufficiency”) and their respective interventions also play important roles. In this paper, we address citizens’ heterogeneity regarding both their current behaviors and their willingness to realize their sufficiency potentials—that is, to reduce their energy consumption through behavioral change. We collaborated with three Swiss cities for this study. A survey conducted in the three cities yielded thematic sets of energy-consumption behavior that various groups of participants rated differently. Using this data, we identified four groups of participants with different patterns of both current behaviors and sufficiency potentials. The paper discusses intervention types and addresses citizens’ heterogeneity and behaviors from a city-based perspective. [ABSTRACT FROM AUTHOR]

To analyze the operational efficiency of Chinese power sector at the provincial level, this paper studies the convergence of technical efficiency and productivity growth of electricity across 29 Chinese provinces during the period 1996-2008 using several convergence models. Depending on the model being employed, we find evidence of convergence of operational efficiency towards either a national steady state or towards their own steady states, with the latter process occurring more rapidly. In essence, our study provides evidence of negative effects of government intervention. Additionally, we use the nonparametric distribution dynamics approach to analyze intra-distributional dynamics of technical efficiency and productivity. We find some support for productivity convergence while technical efficiency does not converge for provinces with relatively low levels. We discuss policy implementations based on our model results and highlight several aspects for policy making in the power sector reforms currently being undertaken. [ABSTRACT FROM AUTHOR]

Smart grids provide great opportunities for design and implementation of sustainable and efficient electricity supply chains that are more resilient to disruptions. The problem with electricity supply chain network design (ESCND) using smart grid has not been broadly explored by researchers. This paper aims to approach this problem using a multiobjective robust optimization method. The three objectives are economic (profit maximization), environmental (greenhouse gas emissions minimization), and resilience (network resilience maximization). Efficiency maximization—power loss minimization—has also been taken into account using its corresponding cost element in the economic objective function. The proposed approach accounts for different unique smart grid components such as demand side management programs, microgrid structure, two-way distribution lines, and supplier–consumer nodes, while incorporating different interrelated decisions including facility location, capacity expansion, load allocation, and pricing. To solve the resultant model, a hybrid multiobjective robust optimization technique is proposed based on cutting plane and AUGMECON2 algorithms. The proposed model and solution approach are then applied to an actual case study and the produced results are thoroughly analyzed. We find that while economic and environmental objectives can be strictly conflicting, the implementation of smart grids can result in concurrent boost in both environmental performance and network resilience. [ABSTRACT FROM AUTHOR]

To ensure the use of energy produced from renewable energy sources, this paper presents a method for consumer planning in the consumer–producer–distributor structure. The proposed planning method is based on the genetic algorithm approach, which solves a cost minimization problem by considering several input parameters. These input parameters are: the consumption for each unit, the time interval in which the unit operates, the maximum value of the electricity produced from renewable sources, and the distribution of energy production per unit of time. A consumer can use the equipment without any planning, in which case he will consume energy supplied by a distributor or energy produced from renewable sources, if it is available at the time he operates the equipment. A consumer who plans his operating interval can use more energy from renewable sources, because the planning is done in the time interval in which the energy produced from renewable sources is available. The effect is that the total cost of energy to the consumer without any planning will be higher than the cost of energy to the consumer with planning, because the energy produced from renewable sources is cheaper than that provided from conventional sources. To be validated, the proposed approach was run on a simulator, and then tested in two real-world case studies targeting domestic and industrial consumers. In both situations, the solution proposed led to a reduction in the total cost of electricity of up to 25%. [ABSTRACT FROM AUTHOR]

The potential of solid waste as an energy source is clear, owing to its wide availability and renewable properties, which provide a critical answer for energy security. This can be especially effective in reducing the environmental impact of fossil fuels. Countries that rely heavily on coal should examine alternatives such as electricity from solid waste to provide a constant energy supply while also contributing to atmospheric restoration. In this regards, Low Emissions Analysis Platform (LEAP) is used for simulation the entire energy system in Pakistan and forecasted its capital cost and future CO2 emissions in relation to the use of renewable and fossil fuel resources under the different growth rates of solid waste projects like 20%, 30% and 40% for the study period 2023–2053. The results revealed that, 1402.97 TWh units of energy are generated to meet the total energy demand of 1193.93 TWh until 2053. The share of solid waste based electricity in total energy mix is increasing from a mere 0.81% in 2023 to around 9.44% by 2053 under the 20% growth rate, which then increase to 39.67% by 2053 under the 30% growth rate and further increases to 78.33% by 2053 under the 40% growth rate. It is suggested that 40% growth rate for solid waste based electricity projects is suitable for Pakistan until 2053 because under this condition, renewable sources contributes 95.2% and fossil fuels contributed 4.47% in the total energy mix of Pakistan. Hence, CO2 emissions are reduced from 148.26 million metric tons to 35.46 million metric tons until 2053 but capital cost is increased from 13.23 b$ in 2023 to 363.11 b$ by 2053. [ABSTRACT FROM AUTHOR]

Private households are an important group of energy consumers. Based on Eurostat data, their energy consumption constituted 30% of the final consumption of energy use across the European Union in 2021. The cost of energy is one of the main components of household budgets; thus, the prices provided by energy carriers have a significant impact on energy consumption. The price offered to the final consumer consists of three components: the price of energy and its supply, network costs, and taxes and levies. The values of the three components, however, depend on several factors, among which the structure of the energy markets and energy policies in individual EU countries play a key role. This work aimed to analyze and assess the structure of electricity prices offered to households across EU countries in the years 2019–2021. The differences and similarities between the pricing policies of selected products in the EU and their impacts on households' purchasing capacity were captured and a non-pattern classification method (k-means) was applied as a research tool. The results indicated that the heterogeneity of the electricity price structure increased significantly over the period analyzed. This may be a consequence of the use of strongly differentiated tools to mitigate electricity price increases and the steps being taken towards low-carbon economies. [ABSTRACT FROM AUTHOR]

Highlights • Parameters of 60 electricity-saving measures and 16 abatement measures are compiled. • Synergies of electricity use in China's chemical sector at grid level are assessed. • Efficient use of power can cut 154 Mt CO 2eq , 295 kt SO 2 , 322 kt NO x and 64 kt PM 2.5. • North and Northwest grids have the largest economic benefits on emissions reduction. • Grid with high electricity price is more sensitive to price change than other grids. Abstract Industry is a large electricity user. China's chemical industry (globally the largest based on sales) contributes 7% to China's GDP, while it consumes 11% of the total electricity consumption in industry and is responsible for 40% of total CO 2eq , 40% of SO 2 , 59% of NO x and 18% of PM-emissions of the chemical industry emissions. The heterogeneity of GHG and air pollutant emissions across electricity grids (within a country) is rarely included in analyses. In this paper, electricity conservation supply curves are developed (distinguishing the grids) to estimate the cost-effective and technical potentials of electricity conservation in China's chemical industry. The emission factors per grid for GHG (i.e. CO 2 , CH 4 and N 2 O) and air pollutants (i.e. SO 2 , NO x and PM 2.5) are calculated and used to quantify the emissions mitigation achieved by electricity saving technologies in the chemical industry for the period 2012–2035. Results show that significant multiple benefits can be obtained by implementing electricity efficiency measures. There are large differences among the six grids in terms electricity savings and emissions abatement of GHG and air pollutants. 83% of the total electricity saving potential is contributed by the North, Northwest and Central grids, equal to 32% of baseline electricity consumption in 2035. In 2035, 129 Mt of CO 2 , 33 kt CO 2eq of CH 4 , 571 kt CO 2eq of N 2 O, 235 kt of SO 2 , 275 kt of NO x and 52 kt of PM 2.5 in these three grids can be avoided as a result of electricity savings (a reduction of 31–33% compared to baseline emissions). When decision-makers set targets for energy saving and emission reduction, the multiple benefits and grid heterogeneity should not be ignored. [ABSTRACT FROM AUTHOR]

In Nigeria, the rapid population increase and the overreliance on fossil fuel have created significant environmental, health, political, and economic consequences leading to severe socio-economic drawbacks. These factors have developed a wide gap between energy demand and supply due to insufficient local production, necessitating a clean energy supply for all. The photovoltaic device's economic and environmental merits have made it the most suitable clean energy alternative to help developing countries such as Nigeria achieve the SDG-7. However, apart from the device's low efficiency, which is undergoing intensive study globally, other factors affect the penetration of the technology in developing countries, particularly Nigeria. This report systematically reviews the literature on the country's energy crisis and renewable energy potential, leading to an overview of solar energy potential and penetration. The potential of the technology and its penetration in the country were provided. A list highlighting challenges hindering technology penetration was also provided, and a solution for each was recommended. [ABSTRACT FROM AUTHOR]

This study proposes a novel integrated energy system (IES) cluster optimization structure that uses multi-energy sharing, multi-Nash games, and asymmetric profit allocation according to the energy supply demand and energy development planning for Tibet. First, it integrates clean energy units such as concentrated solar power, power to hydrogen to power, and vacuum pressure swing adsorption to build a novel IES including electricity, heat, and oxygen. Second, multiple novel IESs are combined to form an IES cluster and the IES cluster is divided into three stages of optimization: the first stage is to achieve optimal multi-energy sharing under cluster optimization, the second stage is to conduct multi-Nash games to achieve optimal sharing cost, and the third stage is to conduct asymmetric profit allocation. Finally, the case study is conducted and the results show that the multi-Nash games and asymmetric profit allocation can effectively improve the renewable energy consumption of the IES cluster, reduce the operation cost of the cluster, and reduce the cost of multi-energy sharing compared to only considering the cluster energy supply price as the sharing price, thereby improving the economy of multi-energy sharing. [ABSTRACT FROM AUTHOR]

We formulate a long run model with black, green and white certificate markets that function in conjunction with an electricity market. The markets function well together in the sense that a common equilibrium solution exists, where all targets are satisfied (e.g., the share of green electricity and share of energy saving/ efficiency increase). The equilibrium solution adapts to changing targets but it is, in general, impossible to tell whether this will lead to more, less, or unchanged consumption of "black," "green" or "white" electricity. Hence, if the long run target is to expand the capacity of green electricity generation and energy savings to certain given levels, then these markets may not be the best to use. To obtain clear results, specific parameter values and functional forms are needed. An example based on Norwegian data is provided. In addition, gains and losses in terms of consumers' and producers' surpluses are calculated. [ABSTRACT FROM AUTHOR]

Distributed energy resources present opportunities to serve grid and customer need through two-way power flow. New values, methods, and planning are required to efficiently interconnect and utilize DERs. This paper analyzes New York’s and California’s DER proceedings to provide a comparison of the similarities and differences between these and other states that will result in different levels of deployments and valuations of DERs. [ABSTRACT FROM AUTHOR]

Increasing access to power, enhancing clean cooking fuels, decreasing wasteful energy subsidies, and limiting fatal air pollution are just a few of the sustainable development goals that all revolve around energy (E). Energy-specific sustainable development objectives were a turning point in the global shift towards a more sustainable and just system. By understanding energy resources, markets, regulations, and scientific studies, the country can progress more quickly towards a sustainable economy (SE). Investment in renewable energy industries is hampered by institutional obstacles such as market-controlled procedures and inconsistent supporting policies. Power plant building is currently incompatible with existing transmission and distribution networks, posing significant risks to investors. Deep neural networks (DNN) are specifically investigated in this article for energy demand forecasting at the individual building level. Other relevant information is supplied into fully connected layers along with the convolutional output. A single customer's power usage data were used and analyzed for the final fuel and electricity consumption by various energy sources and consumer groups to test the DNN-SE technique. The energy intensity and labor productivity indexes for several economic sectors are displayed. A wide range of economic activities are examined to determine their impact on environmental pollution indicators, greenhouse gas emissions, and other air pollutants. A more effective and comprehensive energy efficiency strategy should be implemented to lower emission levels at lower prices. Research-based conclusions must be enhanced to help policymaking. The results of the experiment using the proposed method show that it is possible to predict 98.1%, grow at 96.8%, meet 98.5% of electricity demand, use 97.6% of power, and have a renewable energy ratio of 96.2%. [ABSTRACT FROM AUTHOR]

Recent economics literature emphasises the inextricable link between economic prosperity and efficient energy supply and consumption, arguing vehemently that much of today's prosperity is predicated on secure and reliable energy use and that modern industry would grind to a halt without the necessary energy infrastructure. France is an example of an advanced country with enormous energy infrastructure. The country's economic growth has been rather sluggish in recent years, despite its robust and efficient energy production and consumption. The current study analyses empirically whether France's current sustainable electricity use defies the theoretical and empirical literature. To achieve this objective, the standard tools of growth empirics were used over the period 1961–2015. The Zivot–Andrews trended and de-trended structural break tests, as well as Autoregressive Distributed lag (ARDL) bounds testing were employed to analyse the data. The findings of this study demonstrated that France's economic growth is stimulated by electricity usage, financial development, capital, import, and export. The study sheds light on the feedback impact between economic growth and power usage as well as capital and economic growth. With these findings, we argue that it is not electricity that has ceased to serve a functional purpose in France, rather there is a need for entrepreneurial innovative capacity to create factors that require an infinite horizon for the continued use of electricity, which seems to be impeding the country's economic growth potential, among other things. [ABSTRACT FROM AUTHOR]

Regional integrated energy systems (IESs) have emerged to satisfy the increasing diversified energy demand in Tibet. However, limited resource allocation of a given IES can occur because of the uncertainty in the output and prediction error of distributed renewable energy (DRE). A distributionally robust optimization (DRO) model was proposed for the joint operation of multiple regional IESs, and multi-energy sharing and multi-energy flow coupling of electricity, heat, and oxygen were considered. The probability distribution of the DRE output was described using 1 − norm and ∞ − norm constraints, and the minimum operating cost under adverse scenarios was determined through DRO. Furthermore, on the premise of ensuring cluster profit, a pricing mechanism of the energy supply within the cluster was proposed. Finally, a typical model involving eight cases was established and analyzed. The results revealed that multi-energy sharing and multi-energy flow coupling improved the economy of IES cluster operation and realized the coordination of robustness and economy. The energy supply price within the cluster enhanced enthusiasm on the demand side. [ABSTRACT FROM AUTHOR]

Electric and hydrogen vehicles can help decarbonize heavy duty vehicles (HDV). Few studies examine how to meet energy requirements of decarbonized HDVs, and all assume electricity will come from centralized systems. However, decarbonized HDVs could significantly increase energy demands in areas with limited transmission access, potentially favoring deployment of distributed energy resources (DERs). In this paper, we develop an optimization-based techno-economic model that minimizes costs of meeting HDV energy demands by optimizing investments in and operations of DERs, investments in transmission interconnections, and wholesale electricity purchases. We apply it to a modeled U.S. dataset of electric HDV charging demands to quantify the deployment and value potential of three DERs — solar, batteries, and nuclear small modular reactors (SMRs) in the year 2040. For fleets of 100% electric HDVs to 60% electric and 40% hydrogen HDVs, DERs are deployed at 78% to 95% of all charging stations and meet between 24% to 30% of total HDV energy demand. Investments in DERs reduce annual costs by $647 million to $1.9 billion across all stations, while individual stations can save $20 million to over $100 million annually. SMRs make up over 99% of total deployed DER capacity, indicating significant potential for SMR deployment in this emerging market. Widespread DER deployment is robust to capital cost uncertainty in SMRs and transmission lines, wholesale electricity prices, and other factors. [Display omitted] • We create a model to quantify the value of distributed energy resources for meeting decarbonized heavy duty vehicle energy demand. • Distributed energy resources are deployed at 78% to 95% of all charging stations. • Annual cost savings from distributed energy resources investments can be as high as $1.9 billion nation-wide, and $104 million at an individual station. • Small modular microreactors supply approximately between 24% and 30% of heavy duty vehicle energy demand annually. [ABSTRACT FROM AUTHOR]

Electricity markets are characterised by high sensitivity to variations in supply and demand conditions. However, they also exhibit a number of specific characteristics, including large daily, weekly, and seasonal price fluctuations. The aim of this article is to assess the impact of fluctuations in the industry's output on wholesale electricity prices. Results were compared for the Nord Pool markets, with a high share of renewable energy supply, and the HUPX markets, where fossil fuel and/or nuclear energy supply dominates. The results obtained generally indicate the positive impact of changes in the industry's output on wholesale electricity prices. This impact was stronger in the HUPX markets and for periods in daily and weekly cycles with higher energy demands. The results indicate that the sensitivity of electricity prices to fluctuations in the industry's output is lower in markets with a higher share of renewable energy, especially for periods with higher energy demands. [ABSTRACT FROM AUTHOR]

The demand of electricity keeps increasing in this modern society and the behavior of customers vary greatly from time to time, city to city, type to type, etc. Generally, buildings are classified into residential, commercial and industrial. This study is aimed to distinguish the types of residential buildings in Singapore and establish a mathematical model to represent and model the load profile of each type. Modeling household energy consumption is the first step in exploring the possible demand response and load reduction opportunities under the smart grid initiative. Residential electricity load profiling includes the details on the electrical appliances, its energy requirement, and consumption pattern. The model is generated with a bottom-up load model. Simulation is performed for daily load profiles of 1 or 2 rooms, 3 rooms, 4 rooms and 5 rooms public housing. The simulated load profile is successfully validated against the measured electricity consumption data, using a web-based Customer Energy Portal (CEP) at the campus housings of Nanyang Technological University, Singapore. [ABSTRACT FROM AUTHOR]

In response to the objective of fully attaining carbon neutrality by 2060, people from all walks of life are pursuing low-carbon transformation. Due to the high water cut in the middle and late phases of development, the oilfield's energy consumption will be quite high, and the rise in energy consumption will lead to an increase in carbon emission at the same time. As a result, the traditional energy model is incapable of meeting the energy consumption requirement of high water cut oilfields in their middle and later phases of development. The present wind hydrogen coupling energy system was researched and coupled with the classic dispersed oilfield energy system to produce energy for the oilfields in this study. This study compares four future energy system models to existing ones, computes the energy cost and net present value of an oilfield in Northwest China, and proposes a set of economic evaluation tools for oilfield energy systems. The study's findings indicate that scenario four provides the most economic and environmental benefits. This scenario effectively addresses the issue of high energy consumption associated with aging oilfields at this point, significantly reduces carbon emissions, absorbs renewable energy locally, and reduces the burden on the power grid system. Finally, sensitivity analysis is utilized to determine the effect of wind speed, electricity cost, and oilfield gas output on the system's economic performance. The results indicate that the system developed in this study can be applied to other oilfields. [ABSTRACT FROM AUTHOR]

This paper provides an energy consumption model and explains how the operating conditions and structural parameters of a crushing chamber affect energy consumption. Energy consumption is closely related to compressive pressure and displacement. The relationship between pressure, displacement and structural parameters is discussed. The influence of operating parameters on pressure and displacement based on the law of motion of material is examined. Energy consumption can be obtained by the product of pressure and displacement. In consideration of the pressure on the liner surface, which varies according to both height and circumference, an infinitesimal method was used to solve the issue of energy consumption. We validated the predicted energy consumption during breakage with experimental data from a PYGB1821 cone crusher which was consistent with the measured results. Finally, we provide an explanation of the influence of operating parameters and structural parameters on compressive pressure and displacement as well as energy consumption. [ABSTRACT FROM AUTHOR]

This review deals with organic Rankine cycle powered by geothermal resource which is one favorable substitute for conventional fossil energy. Organic Rankine cycle power plants are suitable for utilization of low-temperature energy sources (low grade energy) such as geothermal resource having low temperature (below 150 ᵒC). The applications of organic Rankine cycle for electricity production from geothermal energy resource was reviewed first, where the choice of geothermal energy resources and organic fluids was discussed for different ORC configurations and operating conditions. Hybrid optimization approaches for the purpose of maintaining long term performance of enhanced geothermal system reservoirs were also summarized. Furthermore, an in-depth review of energy and exergy efficiencies of ORCs was conducted. Key factors that influence the energy and energy efficiencies of organic Rankine cycle were discussed in detail. Then, the economic indexes such as electricity production cost and levelized cost of electricity for different organic Rankine cycle configurations were compared with other conventional power generation systems to examine the commercialization of the Organic Rankine cycle. Finally, life cycle assessment that evaluates the whole life performance of geothermal organic Rankine cycle energy systems was reviewed. The Environmental impacts of geothermal ORC were also considered. Compared with other review papers on geothermal organic Rankine cycle s, the present review provides the latest materials for more systematically surveying the geothermal organic Rankine cycle, which will be a valuable source of guidance and directions for engineers and researchers in this field. [ABSTRACT FROM AUTHOR]

Renewable drop‐in fuels provide a short‐ to medium‐term solution to decreasing carbon dioxide emissions from the transport sector. Polyoxymethylene ethers (OME) are among interesting candidates with production pathways both from biomass (bio‐OME) as well as electricity and CO2 (e‐OME) proposed. In the present study, both bio‐ and e‐OME production via methanol are assessed for energy performance and carbon footprint. Process integration methods are applied to evaluate synergies from colocating methanol production with further conversion to OME. Even a hybrid process, combing bio‐ and e‐OME production is evaluated. The energy efficiency of bio‐OME is considerably higher than for the e‐OME pathway, and colocation synergies are more evident for bio‐OME. Carbon footprint is evaluated according to EUs recast Renewable Energy Directive (RED II). If renewable electricity and natural gas are used for power and heat supply, respectively, results indicate that all pathways may be counted toward the renewable fuel targets under RED II. The largest emissions reduction is 92.8% for colocated hybrid‐OME production. Carbon footprints of e‐ and hybrid‐OME are highly sensitive to the carbon intensity of electricity, and the carbon intensity of the heat supply has a major impact on results for all pathways except colocated bio‐ and hybrid‐OME. [ABSTRACT FROM AUTHOR]

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Pakistan is facing a serious energy supply problem due to lack of energy that results in a shortfall of power supply from 6-10 hours/day, especially outside the big cities. The energy demand is expected to increase in every sector such as industrial, agricultural, household and transport in the years ahead due to population growth, economic development and modern lifestyle. Agricultural sector plays a vital role in the country's economy contributing around 20% share in GDP. At present the direct energy consumption in the agricultural sector is 2%. To avoid a worse situation in the future years renewable energy resource potential exploitation is needed. This requires also proper planning and implementation of energy policies. In this work present and future electrical energy consumption, demand and supply gap of the country is presented. A sustainable agricultural productive system has become a major priority to maintain food security for the increasing population. Both direct and indirect electrical and energy consumption has emerged in agrifood sector with farm machinery, production, packing and transport of fertilizers, food processing and transport, crop production, animal product production, poultry production, etc. In addition to this excel based model is developed to integrate the renewable energy into the agrifood - energy nexus supply chain and to fulfil the current and future energy demand of the sector. [ABSTRACT FROM AUTHOR]

Background: The energy sector in Pakistan is facing several challenges resulting from insufficient production. The major objective of this study is to identify and forecast commercial energy consumption and supply from different sources, including oil and petroleum, gas, electricity, and coal sources.Methods: A forecasting method was utilized for investigating the future commercial energy consumption and supply from different sources.Results: Forecasting results in the study reveal that the energy sector of Pakistan needs further attention to improve this sector, including the initiation of new policies and funding schemes to fulfill the country’s demand.Conclusion: Therefore, this study suggests that the government of Pakistan pay further attention to improving commercial energy consumption and supply from different sources to solve the energy crisis in the country. [ABSTRACT FROM AUTHOR]

Many households in developing countries often engage in self-generation to mitigate the impacts of poor public electricity provision. What is less well known, however, is whether (and how) self-generation influences households' willingness to pay (WTP) for service reliability. Using data collected from a sample of Nigerian households, the results reveal that engagement in self-generation is positively correlated with WTP for reliability. This is despite the fact that self-generation reduces the negative welfare impact of unreliability. Further analyses, however, show that backup households' decisions to pay a higher amount than non-backup households are influenced by the costs of self-generation: an increase of N1 (US$0.006) in self-generation's fuel cost per-hour is associated with WTP about N5.22 (US$0.032) more in the monthly bill. However, households' WTP US$0.15-0.16/kWh of improved reliability is smaller than the marginal costs of reliability from self-generation--US$0.27-0.41/kWh. We conclude by discussing the policy implications of our findings. [ABSTRACT FROM AUTHOR]

This article provides the results of the first attempt to substantiate the rates of energy consumption and energy savings during the well-drilling process. It is proposed to accept the electrical energy consumption rate as a planned indicator of consumption of resources in the production of a unit of work of a specified quality. For a comprehensive assessment of the efficiency of use of energy resources during production of similar or substitute work, we determined specific energy consumption (designed, planned, actual), which includes direct consumption of all energy types in the production of a unit of work for basic and auxiliary production and operational needs, including from the consumption volume of mentioned resources and energy supply. Classification of consumption rates of electrical energy according to its action period and size scale has been proposed. The composition and amount of energy consumption rates during well-drilling have been described. The technological, expedition, and group rates of electricity consumption for drilling wells during design, survey, and technological work were determined. Electricity input items in drilling operations have been determined. For the first time, a set of measures to reduce energy costs during drilling is shown. The diagram developed for assessment of well performance allows prediction of technological and expedition rates of electricity consumption. Its creation, knowledge/understanding, implementation, analysis, and assessment by means of telemetry will allow evaluation of energy consumption when simulating drilling operations with varying drilling parameters. It will also provide an opportunity to select optimal technological or expedition rates of electricity consumption, taking account of drilling components at each depth: maximum drilling rate under constant weight on bit or maximum penetration. Based on the diagram, organizational and technical measures are proposed to save energy resources and reduce their consumption. The proposed measures allow saving up to 30–40% on energy costs. [ABSTRACT FROM AUTHOR]

Access to modern energy services is a precondition to improving livelihoods and building resilience against climate change. Still, electricity reaches only about half of the population in Sub-Saharan Africa (SSA), while about 40% live under the poverty line. Heavily reliant on the agriculture sector and increasingly affected by prolonged droughts, small-scale irrigation could be instrumental for development and climate change adaptation in SSA countries. A bottom-up understanding of the demand for irrigation and associated energy services is essential for designing viable energy supply options in an effective manner. Using Uganda as a case study, the study introduces a GIS-based methodology for the estimation of groundwater irrigation requirements through which energy demand is derived. Results are generated for two scenarios: (a) a reference scenario and (b) a drought scenario. The most critical need is observed in the northern and southern regions of the country. The total annual irrigation demand is estimated to be ca. 90 thousand m3, with the highest demand observed in the months of December through February, with an average irrigation demand of 445 mm per month. The highest energy demand is observed in the northern part of the study area in January, reaching 48 kWh/ha. The average energy demand increases by 67% in the drought scenario. The study contributes to current gaps in the existing literature by providing a replicable methodological framework and data aimed at facilitating energy system planning through the consideration of location-specific characteristics at the nexus of energy–water–agriculture. [ABSTRACT FROM AUTHOR]

The building sector is responsible for 43% of France's final energy consumption and is strongly associated with a high environmental impact due to its high consumption of energy and natural resources. These impacts are significant in isolated islands. Due to its geographical isolation and an area of 2512 km 2 , Reunion Island has a heavily carbon-based economy with a high import rate of raw materials for the building sector. This study aimed to investigate the effect of electricity mix decarbonization on residential house environmental impact. The methodology consists of three parts: (i) evaluating environmental impacts of Single-Family Houses (SFH) using life cyce assessment(LCA), (ii) defining SFH typologies using the K-means clustering algorithm, and (iii) implementing energy scenario in LCA of SFH to assess decarbonization effect. The environmental results were particularly sensitive in the operational phase, with a decrease of 83% between 2020 to 2040 of the global warming potential (GWP). The structural phase highlights the weight of imports in the building sector, as a decrease of only 1% is observed. This study clearly shows the necessary energy transition for Reunion Island. In the structural phase, the study recommends that stakeholders reduce imports and increase the share of recovered materials to achieve a substantial reduction in impacts. [ABSTRACT FROM AUTHOR]