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One of the secrets for China's economic growth miracle is continuous investment in infrastructure, and the role of power infrastructure is irreplaceable. However, previous studies mostly focused on generation-side indicators rather than grid-side indicators, ignoring the importance of the mega-grid established in China. As a result, this paper is committed to exploring the economic growth pulling effect of power grids with different voltage levels in the nonlinear framework. On the premise of determining the robustness of estimation parameters by instrumental variable method, the panel smooth transition regression (PSTR) model is used to capture panel heterogeneity. To be exact, the regional economic growth driven by extra-high voltage (EHV) and ultra-high voltage (UHV) power grids presents a regime transition accompanied by the growth of regional power generation and electricity consumption per capita. This means that the mega-grid is more conducive to the economic growth of energy bases and load centers. To further build and improve the state-leveled mega-grid into a nationwide basic platform for trans-regional renewable energy transmission and distribution is a key measure to enhance China's sustainable economic growth under the constraints of carbon peak and carbon neutrality targets. [ABSTRACT FROM AUTHOR]

This paper examines the effects of time-of-use (TOU) pricing on distributed renewable energy (DRE) investment for a non-power generating firm. We develop an electricity consumption cost-minimization model by considering the intermittent generation as well as the firm's electricity consumption. It has been found that implementing full retail prices compensation for the surplus renewable electricity is probably not good as it may lead to DRE over-investment. Moreover, we find that the firm's optimal investment strategy is not necessarily sensitive to the price signal of TOU pricing (i.e., the ratio of peak to off-peak price). Particularly, when the service-level difference in meeting a firm's electricity consumption between peak and off-peak periods by adopting DRE technology is above a critical threshold in relation to the peak time, a strong price signal will not promote the firm's optimal DRE capacity investment. This paper yields a policy insight that "getting the time right" may be more important than "getting the price right" in terms of enabling DRE investment for TOU pricing design. [ABSTRACT FROM AUTHOR]

The globe is now in ecological turmoil as a result of the unrelenting increase in global warming. As a result, governments worldwide are committing to decarbonizing the environment, with the United Arab Emirates (UAE) and the Kingdom of Saudi Arabia (KSA) playing an important role in this effort. Hence, this paper evaluates the nonlinear (asymmetric) impact of natural gas consumption on renewable energy consumption and economic growth in the KSA and the UAE utilizing data stretching from 1990 to 2020. The study also considers other drivers of renewable energy consumption and economic growth, such as trade openness and CO2 emissions. The study utilizes nonlinear autoregressive distributed lag (ARDL) to evaluate these associations. The outcomes of bounds nonlinear ARDL (NARDL), affirm the long-run association between the variables in both countries. The nonlinear results show that positive and negative shocks in natural gas consumption have a negative impact on renewable energy in both UAE and KSA. In contrast, positive and negative shocks in natural gas consumption impact economic growth positively. The study proposed vital policy recommendations based on these results. [ABSTRACT FROM AUTHOR]

Investigating the current and future dynamics of energy consumption in modern economies such as the UK is crucial. This paper predicts the UK's energy consumption using data spanning January 1995 to March 2022 by comparing and evaluating the forecast performance of machine learning, dynamic regression, time series and combination modelling techniques. The analysis reveals that the seasonal ARIMA and TBATS hybrid models yield the lowest forecast errors in predicting the UK's electricity and gas consumption. Although the combination forecasts performed poorly relative to other models, machine learning techniques such as neural network and support vector regression produced better results compared to the dynamic regression models, whereas the seasonal hybrid model performed better than the machine learning and time series models. The results indicate that the UK's electricity consumption would either stabilise or decline over the forecast horizon, suggesting that it will take some years for electricity consumption to attain pre-2019 levels. For gas consumption, the results indicate that consumption would either maintain current levels or increase over the forecast period. We also show that combination forecasts do not often generate the best predictions, and therefore, choice of methodology matters in energy consumption forecasting. Overall, changing seasonal patterns, energy efficiency improvements, shift to renewable sources and uncertainties due to the COVID-19 pandemic, Brexit, and the Russia–Ukraine crisis appear to be significant drivers of energy consumption in the UK in recent times. These findings are expected to help in designing more effective energy policies as well as guide investor decisions in the energy sector. [ABSTRACT FROM AUTHOR]

The combination of demand response as demand side management together with energy management system has become essential to minimize energy cost, to maintain continuous supply of electricity, and to improve the safety of power system operation. This paper studies the optimal energy dispatch of connected microgrid units containing photovoltaic panels, wind turbine generators, diesel generators, and the main grid. The optimal set point of microgrid's units is determined to satisfy the required load demand for a day-ahead horizon time. As the demand response is an important way of demand side management, this paper proposes as the main contribution the implementation of demand response cost as one of the objective functions to be maximized to view its effect on load demand consumption, on MG energy production and on MG energy cost. The demand response is implemented by using an incentive based demand response program in the optimization model in addition to the fuel cost of diesel generators and the transfer cost of transferable power. The incentive payment offered by utilities is used to motivate consumers to change their energy consumption behavior and thus to reduce their power consumption and maintain the system reliability during on-peak periods. Thus the objective function is formulated to maximize microgrid operator's demand response benefit, and to minimize both the fuel cost of diesel generators, and the transfer cost of transferable power. For this purpose, the defined objective function is solved by a Hybrid Particle Swarm Optimization with Sine Cosine Acceleration Coefficients (H-PSO-SCAC) algorithm for an optimal energy management system of the connected microgrid. For the simulation tests, different algorithms are examined in order to validate the effectiveness of the H-PSO-SCAC algorithm. The impact of demand response program is analyzed on the load demand consumption, on the microgrid energy production and its influence on the optimized microgrid cost function. The results demonstrate that the implementation of demand response has changed the previous situation that costumers do not participate in the operation of the power system. And it enables microgrid to decrease load consumption, microgrid energy production, as well as energy cost. [ABSTRACT FROM AUTHOR]

This paper uses data from the 2015 Residential Energy Consumption Survey to explore the extent to which renters' electricity use in the United States exceeds that of otherwise similar non-renters. Renting households are found to use approximately 9% more electricity than non-renters when controlling for location, socioeconomic, and many appliance-quantity controls. There are multiple factors that explain this extra electricity use, including inferior energy efficiency of appliances, behavioral factors, differences in bill payment responsibilities, and additional reliance by renters on electric space and water heaters. The paper finds that none of these factors are dominant. The phenomenon of renters' (conditionally) higher electricity use is thus best understood as one that emerges from multiple sources. [ABSTRACT FROM AUTHOR]

For a few decades, factors affecting environmental deterioration have been at the center of much interest This paper examines the impact of income level, disaggregated energy consumption, types of globalization level, and urbanization on per capita ecological footprint by utilizing novel machine learning techniques (tree regression, boosting, bagging, and random forest) for 27 OECD countries during 1971–2016. It is found that the random forest algorithms best fit the dataset. The empirical results exhibit that oil product consumption, electricity consumption, and gross domestic product are the most significant variables for our model. Besides, the partial dependence plots results show that economic growth and especially fossil fuel energy consumption damage the environment. These findings have important implications for both developed and developing countries for designing proper energy and environmental policies. Especially, policymakers should focus on sustainable development instead of plain economic growth. [ABSTRACT FROM AUTHOR]

This paper takes Jiangsu as an example to measure the carbon emissions from the electric power industry from 2002 to 2017, builds an extended STIRPAT model to quantify its driving factors, and uses the Monte Carlo method to simulate the evolution of carbon emissions in multiple scenarios from 2018 to 2030. The results show that: (1)Population scale, urbanization level, GDP per capita, industrial added value, and electricity consumption intensity promote the increase of carbon emissions in the electric power industry. (2)Trade openness and the transmission level of other provinces play a role in reducing carbon emissions. (3)Under the baseline scenario and the green development scenario, the carbon emissions of the electric power industry have shown a continuous growth trend, but the growth rate of carbon emissions has slowed down significantly under the green development scenario. [ABSTRACT FROM AUTHOR]

Many economists and psychologists have studied the impact of nudges on households' pro-environmental behaviors. Interestingly, "private nudges" can be imagined for companies. Yet, studies focusing on nudging employees' energy use are rare. The objective of our paper is to explore this issue with the help of a field experiment conducted at 47 French companies' sites. Using a difference-in-difference methodology, the effects of three nudges on employees' energy conservation are tested. The first nudge, "moral appeal", stresses the responsible use of energy. The second one, "social comparison", informs employees on the energy consumption of other firms participating in the experiment. Finally, the third nudge, "stickers", alerts employees about good energy conservation practices. Our results stress the complementarity of these nudges. When implemented alone, the three nudges have no significant effects on energy consumption. However, when the moral appeal and social comparison nudges are combined with the stickers nudge, they become effective. [ABSTRACT FROM AUTHOR]

The global rise in energy consumption makes managing energy demands a priority. Here, the potential of Information and Communication Technology (ICT) in controlling energy consumption is still debated. Within this context, the main objective of the current study is to measure the impact of ICT, its potential benefit, and environmental factors on household electricity demand in Taiwan. A panel of data from 20 cities in Taiwan was collected during the period 2004–2018. We adopted PMG estimation and applied the DH-causality test for analysis. The estimation results show that ICT, carbon emissions, and climate change will drive household electricity demand in Taiwan in the long term. However, ICT has a higher potential to reduce electricity demand in the short-term period. In addition, the results of the causality test reveal a two-way interrelationship between ICT and electricity demand. Our study also found that climate change indirectly affects the use of electricity through household appliances. We also presented several policy implications at the end of this paper. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid approach for the optimal design of electric vehicle (EV) home energy management. The proposed hybrid system combines the execution of the Lichtenberg optimization algorithm and the heap-based optimizer; hence, it is named as LAHBO method. The main purpose of the proposed system is the reduction of costs and improvement of the power factor. Thus, two phases of optimization, such as Lichtenberg optimization algorithm–based cost minimization and heap-based optimizer–based power factor improvement. At initial phase, power conversation, and operating time of the smart home components are decided using the Lichtenberg optimization algorithm method. It is categorized into four groups, such as interruptible, uninterruptible, thermostatically controlled, and non-programmable loads. In second phase, the residential power factor at grid connection point is improved using the heap-based optimizer approach. Finally, the proposed system is carried out on MATLAB platform related to several existing approaches. The proposed method enhances the power factor and diminishes the cost than the existing method. The cost of proposed method is 0.16$ and existing approaches such as CGO, SMO, and SOA cost become 0.2, 0.3, and 0.35$, respectively. [ABSTRACT FROM AUTHOR]

By comparison with cool roofs, the cooling energy produced by radiative cooling can be stored in hybrid radiative cooling air conditioning (HRcAc) systems, which is more feasible for the application of radiative cooling. A thermosyphon mainly relies on buoyancy to drive the water circulating in a pipe without a pump and has been widely used in solar thermal collectors. Thus, more cooling benefits can be achieved by integrating a thermosyphon with HRcAc. This paper investigated the cooling performance of a thermosyphon-based radiative cooler (STRC). The STRC was modelled by using OpenModelica to derive the effects of structure parameters on the cooling performance. The optimized structure was determined according to the proposed optimization process. Finally, the cooling energy saving potential and economics for the application of the STRC in a single-floor family house in five climate zones of China were evaluated. The results show that the annual cooling electricity consumption can be reduced by 41%–56% and that the simple payback period for a single-floor family house with an optimized STRC in all five climate zones of China is between approximately 8.4 years and 10.5 years. [ABSTRACT FROM AUTHOR]

This special issue considers the relationship between energy, capitalism, and space through the lens of electricity capital. Electricity capital is the nexus of state, regulatory, and financial relationships that shape private accumulation through electricity provision. Although electricity provision is marked by immense historical and geographical diversity, the papers in this special issue work to theorize it as a core fraction of capital to draw into focus continuities and disruptions in capital flows amid the transition from fossil fuels to a diversity of clean sources. This special issue bridges debates in critical energy studies, economic geography, and political ecology on the possibilities of economic transformation through clean energy infrastructure by examining the dialectic between private accumulation through electrification and labor, environmental, and environmental justice organizing for "energy justice." This special issue sheds light on the contradictory social relations that shape electrical power provision. We understand that electricity is seen not only as an energy source but also as an investment opportunity, a climate change mitigation strategy, an employment prospect, a component of economic development, and a site of democratic, community organizing. In so doing, we analyze the regulatory, financial, and infrastructural impediments to energy justice and international struggles to decarbonize the power sector to address climate change and to achieve universal and equitable electricity service. [ABSTRACT FROM AUTHOR]

Utility-scale renewable electricity generation is essential to decarbonisation as well as to ensuring affordable and secure electricity supplies around the world. Yet thus far there has been limited critical thinking dedicated to the complexities behind the finance and ownership of this new infrastructure and how national and local stakeholders should participate in and benefit from its development, particularly in contexts of high inequality in low- and middle-income countries. As the global renewable energy industry becomes increasingly consolidated and financialised, evidence from a number of countries suggests that despite the pro-environmental outcomes of utility-scale renewable electricity generation, the processes and institutions that procure and finance it have often failed to include or benefit individuals and communities living in the national and local vicinity. This paper therefore sets two key competing objectives of renewable electricity generation in context: as a predictable, long-term revenue stream for investors, and as a mechanism for socio-economic development and community empowerment. Building on scholarship from human geography, development studies and sustainability transitions, my analysis takes forward understandings of the role of finance in utility-scale renewable electricity generation as a key aspect of the political economy of the energy transition. In exploring the evolution of renewable electricity as a new and rapidly emerging asset class I consider how its development is increasingly determined by the frameworks and logics of finance and investment. Drawing on examples from South Africa and Mexico, I address the following questions: What are the evolving configurations and processes of finance and investment in utility-scale renewable electricity generation? How have they been facilitated? And what tensions have arisen from their implementation at the national and local level? [ABSTRACT FROM AUTHOR]

In this paper, I bring together scholarship on racial capitalism and critical energy studies to investigate how electrification contributes to racialized uneven development. I work toward a theory of racialized electricity capital as a state-supported circuit of accumulation through corporate provision of electricity, which is basic need essential to everyday life. I develop a case study of the electrification of Atlanta, Georgia to examine the historical–geographical formation of the relationship between the city's electric utility, Georgia Power, and the state agency that regulates the Company, the Georgia Public Service Commission. I ask how regulation functioned simultaneously to expand and differentiate electricity consumption across Atlanta and in so doing reinforce a racialized labor hierarchy and unequal access to affordable electricity. This case study emphasizes the importance of analyzing the central role of the state in allowing and perpetrating systems of energy provision that create racialized and gendered poverty. Drawing from the most recent hearings regulating electricity rates before the Commission in 2019, I bring to the fore the work of energy equity activists leading a campaign to Fight the Hike who enact demands for racial justice and a democratic energy system. [ABSTRACT FROM AUTHOR]

The U.S. electricity sector has undergone a series of technological and political economic transformations between 1995 and 2020. Some, but not all, states have moved toward the provision of electricity through wholesale electricity markets, while others have remained traditionally regulated. In addition, electricity is increasingly generated from natural gas and renewable energy, and while total electricity consumption is stagnant in the United States, electric utility revenues have continued to grow. In combination with a growing emphasis on increasing shareholder value, the result of these changes has been the entry of a range of new electricity industry, finance, and regulatory actors, as well as a shift in the ways in which existing actors are seeking to realize surplus value. In light of these changes, in this paper, I outline the contemporary contours and contradictions of the U.S. electricity industry and detail five accumulation strategies being used in the industry. Building on scholarship in energy geography and geographies of finance, and based on the analysis of industry documents and financial analyst reports, I detail how the U.S. electricity has been reshaped by the introduction of new types of technologies, financial risk and investment opportunities, and changing modes of regulation. The resulting accumulation strategies are contested, partial, and incomplete, and are therefore a messy set of overlapping and at times contradictory strategies being deployed in an industry in flux. [ABSTRACT FROM AUTHOR]

Wind speed forecasting, a time series problem, plays a vital role in estimating annual wind energy production in wind farms. Calculation of wind energy helps to maintain stability between electricity production and consumption. Deep learning models are used for predicting time series data. However, as wind speed is non-stationary and irregular, pre-processing of these data is necessary to get accurate results. In this paper, static normalization techniques like min–max, z -score, and adaptive normalization are used for pre-processing wind datasets, and further, their forecasting results are compared. Adaptive normalization increases the learning rate and gives better forecasting results than static normalization. The RMSE value was reduced by 9.18% for the NREL dataset when adaptive normalization was used instead of z -score normalization and by 23.58% for the Weather dataset. The datasets used are taken from National Renewable Energy Laboratory (NREL) and Kaggle's Dataset. [ABSTRACT FROM AUTHOR]

In this paper we analyze a uniform price day-ahead electricity spot market that is followed by redispatch in the case of network congestion. We assume that the transmission system operator is incentivized to minimize redispatch cost and compare cost-based redispatch (CBR ) to market-based redispatch (MBR) mechanisms. For networks with at least three nodes we show that in contrast to CBR, in the case of MBR incentives to minimize redispatch cost are in general not efficient in the context of our short-run analysis. This obtains both for pay-as-bid as well as locational marginal prices used for MBR compensation. As we demonstrate, moreover, in case of MBR the possibility of the transmission system operator to inefficiently reduce redispatch cost at the expense of decreased overall welfare can be driven both by the electricity supply side and the electricity demand side. Our results highlight a novel and important aspect regarding the design and the desirability of congestion management regimes in liberalized electricity markets. [ABSTRACT FROM AUTHOR]

The study represents a new approach of analyzing energy poverty using an intelligent method based on social factors. Energy poverty represents one of the most vital problems, especially in recent years, with serious implications in the social, economic, environmental, political, and health sphere. Identifying and measuring social energy parameters represents a challenge not only on the national, but also on the regional level. This research represents a new approach to neural network application in energy systems and energy resource planning activities with the aim of analyzing energy poverty with real socio-economic data. The analyzed data are associated with social factors within one country. The newly developed model includes a new data optimization framework for pre-processing and selecting the most important parameters from a raw dataset. In analyzing energy poverty, it is concluded that its weakness is based on the actual energy consumption of households (both electricity and heat consumption). The model presented in this paper uses 15 influential parameters in energy prediction. [ABSTRACT FROM AUTHOR]

How does temperature affect household energy demand in low-income countries? This paper uses 132,375,282 hourly electricity consumption observations from 5,975 households in South Africa to estimate the causal effects of short-term temperature changes on household electricity consumption. The estimates flexibly identify a constant log-linear temperature response--for every 1°C increase in temperature, electricity consumption decreases by 4.1% among temperatures below the heating threshold but increases by 8.1% among temperatures above the cooling threshold. This relationship is driven more strongly by seasonal than hourly temperature changes. Holding all else constant, a 3.25°C increase in temperatures would reduce electricity consumption by 1,093.4 kWh (6.2%) per year per household. Widespread use of electric heating due to limited residential gas heating infrastructure likely drives this. These results point to important regional heterogeneity in how temperature increases may affect household energy demand in the coming decades. [ABSTRACT FROM AUTHOR]

The objective of this paper is to explain the relationship between high frequency electricity demand, intra-day temperature variation and time. Using the Generalised Additive Model (GAM) framework we link high frequency (5-minute) aggregate electricity demand in Australia to the time of the day, time of the year and intra-day temperature. We document a strong relationship between high frequency electricity demand and intra-day temperature. We show a superior model fit when using Daylight Saving Time (DST), or clock time, instead of the standard (solar) time. We introduce the time weighted temperature model that captures instantaneous electricity demand sensitivity to temperature as a function of the human daily activity cycle, by assigning different temperature signal weighting based on the DST time. The results on DST and time weighted temperature modelling are novel in the literature and are important innovations in high frequency electricity demand forecasting. [ABSTRACT FROM AUTHOR]

The mushroom growth of universities in the developing economies, in particular, is believed to be a key contributor to the relentless aggravation in the overall demand for electricity. Moreover, the large university campuses are often compared to cities whereby the associated electricity-consumption within these campuses are also referred to account for a bulk of the total urban electricity consumption. Thus, conservation of electricity within the campus has become a core agenda of universities in quest of ensuring respective campus sustainability. Against this backdrop, this paper aims to highlight and recommend the cost-effective and best-practiced techniques applied to conserve electricity within the private universities in Bangladesh. As part of the methodology, a cost–benefit analysis of electricity conservation is put forward in the context of a case study of the North South University, the largest private university in Bangladesh. The results from the analyses imply that proper implementation of the electricity conservation and efficiency enhancement techniques within the campus can effectively cut down the total electricity bills by almost one-third and simultaneously account for a 5% reduction in the total electricity demand within the campus. [ABSTRACT FROM AUTHOR]

Ambitious energy efficiency goals constitute an important roadmap towards attaining a low-carbon society. Thus, various building-related stakeholders have introduced regulations targeting the energy efficiency of buildings. However, some countries still lack such policies. This paper is an effort to help bridge this gap for Northern Cyprus, a country devoid of building energy regulations that still experiences electrical energy production and distribution challenges, principally by establishing reference residential buildings which can be the cornerstone for prospective building regulations. Statistical analysis of available building stock data was performed to determine existing residential reference buildings. Five residential reference buildings with distinct configurations that constituted over 75% floor area share of the sampled data emerged, with floor areas varying from 191 to 1006 m2. EnergyPlus models were developed and calibrated for five residential reference buildings against yearly measured electricity consumption. Values of Mean Bias Error (MBE) and Cumulative Variation of Root Mean Squared Error CV(RMSE) between the models' energy consumption and real energy consumption on monthly based analysis varied within the following ranges: (MBE)monthly from –0.12% to 2.01% and CV(RMSE)monthly from 1.35% to 2.96%. Thermal energy required to maintain the models' setpoint temperatures for cooling and heating varied from 6,134 to 11,451 kWh/year. [ABSTRACT FROM AUTHOR]

Based on existing pollution emission policies, this study addresses the relationship between innovation and energy input along with energy price. Both energy demand and innovative investment are characterized in this work. First, this paper argues that higher energy prices results in lower innovation investment in reduction of emission, higher innovation in production, lower energy demand and lower consumer surplus. Second, the increased effects of emissions on consumers yield lower innovation investment, lower energy demand and lower consumer surplus. Finally, policies for controlling emissions are also discussed in this study. Stricter policies for controlling emissions yield more innovative investments to reduce emissions and less investment to improve production efficiency, resulting in lower demand for energy and lower demand for and higher prices of products. In theory, this study develops the theory about multi-dimensional innovations and captures the relationship between innovative investments to reduce emissions and innovation to improve production efficiency. [ABSTRACT FROM AUTHOR]

The choice of fuels has frequently been at the center of debates about how a future low-carbon mobility system can be achieved. This paper introduces two visions of biogas fuels and electricity using material from interviews and documents in Swedish transport. These visions are analyzed as interrelated sociotechnical imaginaries. To better understand the way visions of biogas and electric vehicles (EVs) dynamically shape and condition each other, four dimensions of sociotechnical imaginaries are further developed: spatial boundedness, temporality, coherence and contestation, and the socio-material relations they are associated with. Imaginaries of biogas and EVs differ with respect to these characteristics. The biogas imaginary is made up of locally bounded visions of the desirable future, showing how imaginaries can be fragmented and contested, often because of their embeddedness in local socio-material systems of resource use. This local boundedness is exemplified by contrasting cases of contested biogas imaginaries in the Swedish municipalities of Linköping and Malmö. The imaginary of EVs, in contrast, is more uniform nationally and even influenced by international expectations that in the future vehicles will be shared, electric, and autonomous. The qualities of these imaginaries shape the way they interrelate and coevolve as sociotechnical changes of the transport system unfold. [ABSTRACT FROM AUTHOR]

This paper estimates household electricity demand using data from the Energy Information Administration's (EIA) 2015 Residential Energy Consumption Survey (RECS). Previous research has focused on estimating price elasticities, and we contribute to this literature by examining how price elasticity is impacted by household income and the appliance stock. Results show that as income increases, households rely less on electricity for space and water heating, but the number of electronic appliances increases with income. The changing stock suggests that the mechanism through which energy reduction occurs differs across income levels. The results can aid policymakers concerned about electricity demand, rising electricity rates, and the impact on low-income households. The results can also inform the design of demand response and demand side management programs. [ABSTRACT FROM AUTHOR]

The decisions made on the urban planning level could influence the building design at later stages. Many studies have shown that the utilisation of daylight in buildings would result in significant savings in electricity consumption for lighting, while creating a higher quality indoor environment. The surroundings of a building have a great influence on the indoor environment of that building. A major factor is the shading that the surrounding buildings could provide, blocking and diminishing the available amount of daylight in nearby buildings. This paper reports a study that combine the effect of the exterior illuminance levels on façades with the interior illuminance levels on the working plane. The paper also explains an easy to use tool (EvUrban-plan) developed by the authors, which was applied to their findings in the early stages of urban planning to ensure daylight optimisation in the buildings. [ABSTRACT FROM PUBLISHER]

The energy rebound effect is a potential threat to energy-saving targets based on energy efficiency improvements. This paper employs a stochastic energy demand frontier model to analyze the energy demand and rebound effect in China's urban residential sector. Using a panel data set of 30 Chinese provincial-level regions over the period 2001-2014, for the first time, we investigate the degrees and determinants of China's urban residential energy demand and energy rebound effect. The results show that residents' income level, energy price, temperature deviation, population scale, household size, and district heating system are significant influencing factors of residential energy consumption. Regarding the energy rebound effect, we find that energy price is negatively correlated with the rebound effect, and an inverted U-shaped relationship between residents' income level and rebound-effect size exists. The magnitude of the rebound effect varies across regions, with an average of 65.4%. The main policy implication generated by this study is that it should be in urgent need of energy pricing reform to mitigate the rebound effect in China. [ABSTRACT FROM AUTHOR]

This paper is one of the limited studies to investigate rebound effects in sectoral electricity consumption and the specific case of New Zealand. New Zealand, like other OECD economies, has aimed for energy efficiency improvements and reduced electricity consumption from 9.2 MWh per capita in 2010 to 8.6 MWh per capita in 2015. However, following a significant decline since 2010, electricity consumption in the main New Zealand sectors is increasing. Energy conservation could play an important role in meeting the growing demand for electricity but rebound effects can affect the effectiveness of conservation policies. We decompose the sectoral electricity prices to capture the asymmetric demand response to electricity price changes and estimate electricity demand elasticity during 1980 and 2015 to estimate the sectoral rebound effects. We find partial rebound effects of 54% and 23% in the industrial and commercial sectors respectively while we find no rebound effect at the aggregate level. The rebound effect is insignificant in the residential sector. These findings lead to policy recommendations for sector specific energy conservation measures and policies. [ABSTRACT FROM AUTHOR]

Capacity mechanisms are increasingly used in electricity market design around the world yet their role remains hotly debated. This paper introduces a new benchmark model of a capacity mechanism in a competitive electricity market with many different conventional generation technologies. We consider two policy instruments, a wholesale price cap and a capacity payment, and show which combinations of these instruments induce socially-optimal investment by the market. Our analysis yields a rationale for a capacity mechanism based on the internalization of a system-cost externality--even where the price cap is set at the value of lost load. In extensions, (i) we show how increasing variable renewables penetration can enhance the need for a capacity payment under a novel condition called "imperfect system substitutability", and (ii) we outline the socially-optimal design of a strategic reserve with a targeted capacity payment. [ABSTRACT FROM AUTHOR]

As the multi-daily electricity consumption behaviors have the strong characteristics of dynamicity, nonlinearity and locality caused by temporal manifold structure, the existing methods are difficult to fine-grained and accurately classify it. To solve this problem, this paper proposes a hierarchical classification method based on the temporal extension of the neighborhood preserving embedding algorithm (TNPE) and Bayes. The input data are multi daily-load curves of a single consumer, including power-hour-day three dimensions, which contains the full information of the user's consumption behaviors not only in hours, but also in days. Firstly, electricity consumption behaviors are divided into routine and non-routine types by k -means clustering algorithm. Secondly, the load feature mapping matrix of different industries is extracted through the TNPE, and each TNPE model can regard as one binary classifier, so the multi-classifier is constructed through multiple TNPE models. Finally, by converting the feature similarity between samples into probabilities, a Bayesian model is established to realize which the power consumption type belongs to. The case results show that this method can effectively recognize the local dynamic features in the temporal load data, and obtain a higher classification accuracy through a smaller number of training samples. [ABSTRACT FROM AUTHOR]

In this paper, a stochastic frontier analysis approach is applied to estimate energy demand functions in the transport sector. This approach allows us to obtain energy efficiency measures at country level that are a robust alternative to the energy intensity indicators commonly used for international comparisons. A transitive multilateral price index is constructed for aggregating the diverse energy components employed in the sector. Due to the likely unobserved heterogeneity among countries, the use of a random parameters model is proposed to accommodate these differences and to obtain different income and price elasticities per country. The estimated model is compared with alternative approaches of addressing this issue such as latent class, true fixed effects or true random effects models. This study is the first to use a random parameters stochastic frontier approach in the estimation of energy demand functions. The proposed procedure is applied to Latin America and the Caribbean, where the transport sector represents a large share of total energy consumption. [ABSTRACT FROM AUTHOR]

We analyze the impact of the COVID-19 pandemic on electricity consumption patterns. We highlight the importance of decomposing total electricity consumption into consumption by firms and by households to better understand the economic and social impacts of the crisis. While electricity demand by firms has fallen substantially, the demand by households has gone up. In particular, our focus is on Spain where, during the total lockdown, these effects reached –29% and +10% respectively, controlling for temperature and seasonality. While the electricity demand reductions during the second wave were milder, the demand by firms remained 5% below its normal levels. We also document a change in people’s daily routines in response to the stringency of the lockdown measures, as reflected in their hourly electricity consumption patterns. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to estimate lost consumer values due to various restrictions on household electricity use involving behavior adaptation. To do this, we conduct a choice experiment where households choose between hypothetical electricity contracts including various restrictions on the use of high-power household appliances. In addition, we use a contingent valuation question related to complete blackouts to study a restriction on other types of electricity usage (heating, lighting, TV, etc.). The results indicate a significant difference between the value lost due to the soft control, and the blackouts. Furthermore, policies aiming at stimulating behavioral changes are costly and it is far from obvious that demand response requiring behavioral adaptation is more cost effective than supply response (i.e., increased production of electricity). [ABSTRACT FROM AUTHOR]

Capacity mechanisms are increasingly used in electricity market design around the world yet their role remains hotly debated. This paper introduces a new benchmark model of a capacity mechanism in a competitive electricity market with many different conventional generation technologies. We consider two policy instruments, a wholesale price cap and a capacity payment, and show which combinations of these instruments induce socially-optimal investment by the market. Our analysis yields a rationale for a capacity mechanism based on the internalization of a system-cost externality--even where the price cap is set at the value of lost load. In extensions, (i) we show how increasing variable renewables penetration can enhance the need for a capacity payment under a novel condition called "imperfect system substitutability", and (ii) we outline the socially-optimal design of a strategic reserve with a targeted capacity payment. [ABSTRACT FROM AUTHOR]

This paper examines how rising temperatures due to climate change will affect electricity consumption patterns through mid- and end-century. We extend recent literature in two important ways. First, we directly incorporate adaptation in the form of increased air conditioner penetration, resulting in heightened responsiveness to hot temperatures. Second, we go beyond average effects to consider how higher temperatures will change the intraday and seasonal shape of consumption. This is found to be of greater importance in colder countries, where the average effect is dampened by reductions in heating demand from warmer winters. Seasonal peaks are projected to shift from winter to summer and the diurnal range of hourly consumption expands, exacerbating an increasing need for flexibility coming from the supply side due to a growing share of renewable energy. [ABSTRACT FROM AUTHOR]

Since the 1990s, electricity distribution networks in many countries have been subject to incentive regulation. The sector regulators aim to identify the best performing utilities as frontier firms to determine the relative efficiency of firms. This paper develops a nested latent class (NLC) model approach where unobserved differences in firm performance are modelled using two 'zero inefficiency stochastic frontier' (ZISF) models nested in a 'latent class stochastic frontier' (LCSF) model. This captures the unobserved differences due to technology or environmental conditions. A Monte Carlo simulation suggests that the proposed model does not suffer from identification problems. We illustrate the proposed model with an application to Norwegian distribution network utilities for the period 2004-2011. We find that the efficiency scores in both LCSF and ZISF models are biased, and some firms in the ZISF model are wrongly labelled as inefficient. Conversely, inefficient firms may be wrongly labelled as being fully efficient by the ZISF model. [ABSTRACT FROM AUTHOR]

In the recent years, electrical, electronics, and telecommunications have far-famed a rare improvement, the quantity of nonlinear loads has inflated. Many electric power consumption devices are sensitive to magnetic attraction disturbances, created through nearby devices, which might have an effect on the power quality for several industry units or may be domestic users. Poor quality of power leads to fault of devices and instrumentation instability in a short period. Systematically, some research and analysis are required to monitor the disturbances of power quality which increases quality of power. This paper consists of power quality analysis on RLC circuits with voltage and current magnification values through Hyperspectral signal processing. The voltage changes and harmonic disturbances can be simulated finely with the MATLAB–Simulink simulation results and the theoretical analysis display. The simulated outcome and the Hyperspectral processing offer data and identification of power quality variances and additional control measures accurately. [ABSTRACT FROM AUTHOR]

This paper considers the design, incentives and effectiveness of U.S. demand side management (DSM)programs and tries to explain why this ambitious, almost unanimously embraced initiative failed. Problems on the demand side result from consumers' private information that implies that substantial principal-agent slippage must accompany any conservation incentive the utility offers to the consumer. Moreover, the regulatory incentives induce the American utility to select inefficient programs. Therefore, the utility has little to gain from deterring such strategic reactions and cheating by consumers. As a consequence, the reported conservation exists largely on paper but not in reality. This ex-post assessment is important for two reasons. First, European countries (Scandinavia, Germany, Austria and others) have been eager to repeat this American regulatory 'success'. Second, the problems addressed in this paper would apply to another round of conservation programs induced by the concern about global warming. [ABSTRACT FROM AUTHOR]

Wind power is a rapidly growing technology, with an estimated 35% of national end-use electricity demand to be met from wind by 2050 in the US. With such a projected rapid growth, it is necessary to improve and innovate relevant technological areas with due considerations of possible impacts of wind energy harnessing through wind turbines. This paper presents a systematic review of current literature on the issues of noise and vibration of wind turbines and their impact on human health and wild life. The paper reviews the literature on the issues of noise and vibration in wind turbines, the generation mechanisms, the propagation, the impact on human health and wild life. The current status of technology and future developments to mitigate the health and environmental impacts of wind turbine noise and vibration are also reviewed. The paper includes a review of current standards on measurement of acoustic noise of wind turbines and data analysis. [ABSTRACT FROM AUTHOR]

With more electricity generated from renewable sources, the importance of effective storage capacity is increasing due to its capability to mitigate the inherent variability of these sources, such as wind and solar power. However, the cost of dedicated storage is high and all customers eventually have to pay. Deferrable demand offers an alternative form of storage that is potentially less expensive because the capital cost is shared between providing an energy service and supporting the grid. This paper presents an empirical analysis to illustrate the beneficial effects of Plug-in Hybrid Electric Vehicles (PHEV) and thermal storage on the total system cost using data for a hot summer day in New York City. The analysis shows how customers can reduce total system costs and their bills by 1) shifting load from expensive peak periods to less expensive off-peak periods, 2) reducing the amount of installed conventional generating capacity needed to maintain System Adequacy, and 3) providing ramping services to mitigate the variability of generation from renewable sources. Moreover, this paper demonstrates economic benefits of different types of customers with different deferrable demand capabilities under two bill payment policies, flat price payment and optimum price payment, and it finally shows how long it takes for customers to fully pay back their initial capital costs of PHEV or thermal storage under two different policies. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to analyze and test demand behavior in the organized electricity market. According to a theoretical framework of heterogeneous agents' behavior, we estimate a complete multi-stage system weakly separable using individual demand bid data in the Italian Power Exchange. The novel contribution of this paper is twofold. Firstly, we model hourly demand of heterogeneous groups of agents acting in the Italian electricity market with a simultaneous system for all 24 hours. Secondly, we empirically measure the entire structure of expenditure elasticities and cross price elasticities for all 24 hours of the day, ascertaining whether hourly electricity demands can be considered normal or luxury goods and substitutes or complements in an organized electricity market. Econometric estimation shows that price elasticity tends to be higher when hourly price peak. Moreover, electricity exhibits both substitutability and complementarity characteristic in different hours of the day, the former during the day and the latter during the night. Electricity appears to be a normal good during nighttime and a luxury good during daytime. The demand structure has welfare improving policy implications, because appropriate regulation can favor consumer behavior adjustment to shave consumption away from peak prices, thus yielding lower aggregate equilibrium expenditures. To this end, we advocate reforming the actual administered two-price tariff structure to introduce real time pricing options for Italian final users. [ABSTRACT FROM AUTHOR]

For the purpose of effectively providing protection and utilization of historical earthen sites, the fully-enclosed exhibition halls with electricity driven air-conditioning have been successfully adopted to provide a suitable preservation air environment. However, its electricity consumption and carbon emissions are considerable due to the continuous operation of environmental control, the energy consumption of air cooling in exhibition halls can reach more than 10 times that of office buildings. To further reduce energy consumption, this current study drew on the concept of NBS (Nature Based Solution) and proposed a low-carbon environmental control system for an enclosed exhibition hall for storage of earthen relics by applying natural energy (solar photovoltaic and earth-air-cooling) and space optimization. Firstly, a numerical model was established to simulate the preservation environment in exhibition halls and the electricity consumption of each energy subsystem. Then the model was applied to optimize the design parameters (e.g. earth-air tunnel and airflow pattern) for the environmental control system. Numerical results showed that the electricity consumption was reduced by 58% by applying earth-air-cooling and solar photovoltaic. After optimization of the exhibition hall height, electricity consumption was approximately reduced by 65%. This research is of great value to mitigate energy consumption problems encountered in earthen relics museums and other similar environments. [ABSTRACT FROM AUTHOR]

The study analyzes the asymmetric nexus of coal consumption with environmental quality and economic growth. In this context, the study focuses on eight leading emerging countries that take place in BRICS, E7, and Fragile Five groups. Also, the study uses yearly data from 1989 to 2021 and performs novel quantile methods, such as Granger Causality-in-Quantiles and Quantile-on-Quantile Regression (QQR). Also, quantile regression is used for robustness check. The results present that (i) there are causalities from coal consumption to both environmental quality and economic growth at 10% significance, whereas quantile and country-based results differ; (ii) effects of coal consumption on environmental quality are much stronger in lower quantiles for Brazil, Indonesia, India, South Africa, and, Turkey, but in higher quantiles for China, Mexico, and Russia; (iii) effects of coal consumption on economic growth are much stronger in lower quantiles for Brazil, Indonesia, India, Russia, South Africa, and Turkey; in higher quantiles for China; lower and middle quantiles for Russia; and all quantiles for Mexico; and (iv) the robustness of the QQR results are validated. Hence, empirical outcomes underline the highly crucial effects of coal consumption on environmental quality and economic growth in the countries. The results imply that policymakers should focus on efforts to decrease coal consumption gradually by applying a macro transition plan to increase environmental quality without causing economic decline by considering changing effects of coal consumption at quantiles and countries. [ABSTRACT FROM AUTHOR]

A price reform in Turkey increased the residential electricity tariff by more than 50 percent in 2008. The reform, aimed at encouraging energy efficiency and private investment, sparked considerable policy debate about its potential impact on household welfare. This paper estimates a short-run residential electricity demand function to evaluate the distributional impact of the tariff increase. The analysis allows heterogeneity in households' price sensitivity and the model is estimated using a nationally representative sample of 8,572 Turkish households. The results suggest that rich households in Turkey are three times as responsive in adjusting consumption to price changes as poor households are. In addition, the welfare loss of the poorest income quintile--measured by the change in consumer surplus as a percentage of income--is 2.9 times that of the wealthiest. [ABSTRACT FROM AUTHOR]

In this paper we employ a dataset of three dimensions--state, sector, and year--to estimate the short- and long-run price elasticities of state-level electricity demand in the United States. Our sample covers the period 2003-2015. We contribute to the literature by employing instrumental variable estimation approaches, using the between estimator, and pursuing panel specifications that enable us to control for multiple dimensions of fixed effects. We conclude that state-level electricity demand is very price inelastic in the short run, with a same-year elasticity of -0.1. The long-run elasticity is near -1, larger than often believed. Among the sectors, it is industry that has the largest long-run price elasticity of demand. This appears to in part be due to electricity-intensive industrial activities clustering in low-price states. [ABSTRACT FROM AUTHOR]

Most sub-Saharan African electricity generation is through renewable energy sources. However, the pace of renewable expansion is slow, mirrored by the region's low per capita electric power consumption and electricity access. The study examines the determinants of renewable electricity generation adoption in sub-Saharan Africa (SSA) countries using content description and a panel ARDL analysis. Findings from this study show that hydroelectric power is the long-standing renewable electricity source in the region. The deployment of non-hydro renewable electricity sources is slow despite its vast potential. In most evaluated countries, renewable electricity targets are below actual realization. Also, policies are ineffective in driving renewable electricity adoption, as indicated by the negative relationship between renewable electricity generation and policy enactments in SSA. Foreign direct investment and financial development significantly negatively impact renewable electricity adoption, suggesting that both factors do not expand renewable electricity generation. Feasible strategies for increasing non-hydro renewable electricity use include activating renewable energy support mechanisms and their uptake. In addition, governments in SSA should strengthen their legal and institutional frameworks and encourage lessening bottlenecks and bureaucracies associated with renewable electricity investment. [ABSTRACT FROM AUTHOR]

This paper applies panel unit root, panel cointegration, and panel causality techniques to re-examine the total energy and electricity demand functions of 25 selected OECD countries during the 1978-2004 period. The panel results indicate that total energy demand is income inelastic and price inelastic, whereas electricity demand is income elastic and price inelastic. Based on the results of the panel causality test, there are reciprocal causal relationships among real income, real energy price, and total energy consumption. Furthermore, a uni-directional causality runs from income and electricity price to electricity consumption. The results for the panel as a whole suggest that the demand for total energy and electricity in the OECD countries is driven largely by strong economic growth, while consumers are largely insensitive to price changes. [ABSTRACT FROM AUTHOR]

This paper uses a panel data of 72 U.S. electricity distribution companies during the period 1972-2009 to estimate structural demand and reduced-form price models. I find the own-price and income elasticity of demand for residential, commercial, and industrial customers that are generally consistent with the published economics literature. While static models work well for residential demand, dynamic models are more appropriate for the larger customer classes who require more time to adjust. Conditioning on the regressors, I find that residential and commercial electricity demand has been increasing slowly while industrial electricity demand and deflated electricity prices have been decreasing. In all price models I find that total factor productivity is consistently the most significant explanatory factor with a 1% increase in total factor productivity resulting in a reduction in deflated electricity prices ranging between 0.05% and 0.30%, depending on the model. Lastly, I find that retail electricity competition is associated with lower deflated electricity prices with the mean total impact being -4.3%, -8.2% and -11.1% for residential, commercial and industrial customers, respectively and with the impact diminishing over the sample period for residential customers, remaining relatively constant for commercial customers and increasing for industrial customers. [ABSTRACT FROM AUTHOR]