Retail Electricity Research Articles

Current status and future potential of rooftop solar adoption in the United States

We utilize a dataset that measures existing rooftop solar installations and classifies rooftops in terms of insolation, azimuth angle and pitch, shading, and size, from aerial imagery last updated in 2017. Analysis of these data reveals that rooftop solar adoption, defined as the number of buildings with existing photovoltaic (PV) installations divided by the total number of eligible buildings, was on average low (mean of 0.93% for 10,417 U.S. ZIP codes). Regarding potential electricity generation, fifteen states could meet their residential electricity demand if panels were placed on all suitable buildings. We conduct a linear regression analysis to elucidate factors that positively (insolation, retail electricity price, Democratic voting fraction, net metering, fraction of science or engineering degree holders) and negatively (fraction of business or education degree holders) correlate with solar adoption. The results suggest anticipated electricity cost savings as a strong motivator for PV adoption, particularly in majority Republican areas, underscoring the importance of programs such as net metering that directly compensate homeowners for generated electricity. Knowledge and installation cost, however, remain barriers. Knowledge campaigns regarding technical aspects of installation and maintenance, as well as increased and stable financial incentives, may stimulate further PV deployment.

Закону об электроэнергетике 20 лет: итоги и новые задачи

Twenty years ago the Federal Law on “Electric Power Industry” was adopted. This act laid the legal foundations for the functioning of wholesale and retail electricity markets formed in the process of reforming the industry. Despite the fact that not all the ideas discussed during the reform were implemented, the adoption of this Law undoubtedly played an important positive role for the formation of the electricity and capacity market. The separation of competitive and naturally monopolistic types of business, the creation of commercial and technological infrastructure independent of generators, the division of the monopoly of the Russian Joint Stock Company “United Energy System of Russia” into a number of generating companies, significant changes in tariff regulation can be considered as the most important steps towards the formation of real market competitive relations in the field of electric power industry. In this article we will focus on the main provisions of the Law on “Electric Power Industry” and the changes that were made to the Law during the twenty-year period of its validity.

Examining the patterns of disaggregate energy security risk and crude oil price: the USA scenario over 1970–2040

Beyond the environmental drawback of fossil energy sources, energy security remains a salient concern for economic development and environmental sustainability. This explains why the influence of energy security and its components (economic, geopolitical, reliability, environmental) on the price of crude oil commodity, especially in the United States of America, is considered in this study up to the period 2040 (i.e., from 1970 to 2040). Using the Kernel-Based Regularized Least Squares (KRLS) approach supported by the robustness of the quantile regression, the result shows an increase in aggregate energy security risk spur crude oil price by an elasticity of ∼0.9. With a positive impact on oil price, the economic, geopolitical, and reliability perspectives of energy security risk exhibit respective elasticity of ∼2.0, ∼0.6, and ∼0.7, thus confirming that a positive shock in each aspect aggravates the oil price hike in the country. Contrarily, an increase in environmental risk could spiral a decline and an inelastic (∼−1.5) change in crude oil price, thus suggesting a desirable net zero future and a significant crash in oil price arising from clean and alternative energy source adoption. Furthermore, retail electricity price and energy expenditures are used as control variables, and crude oil prices respond positively and negatively to the increase in energy expenditures and electricity price, respectively. Several accounts of policy insights are highlighted in these results.

Examining crude oil price outlook amidst substitute energy price and household energy expenditure in the USA: A novel nonparametric multivariate QQR approach

The outlook of crude oil prices has sparsely been empirically examined especially from the critical perspectives of energy expenditure per household, retail electricity prices, and environmental indicators. Given the enormous macroeconomic and socioeconomic effects of crude oil price amidst the fundamentals, this study examines the dynamics of the oil price outlook amidst energy demand (measured by energy expenditure per household), retail electricity price i.e., substitute price, and carbon dioxide (CO2) emissions in the United States of America (USA) over the period 1970 to 2040. This study offers two main innovations: first, it extends the bivariate nonparametric Quantile-on-Quantile Regression (QQR) to the multivariate case. Second, the analysis incorporates projected data series, which provides useful policy insights. The empirical results show evidence of time-varying effects of energy expenditure per household, retail electricity price, and CO2 emissions across the quantiles of crude energy prices. The results further show that the effect of energy demand through household energy expenditures is positive and stronger at the lower quantiles of crude oil price, which corresponds to periods of low crude oil prices. Furthermore, the effects of retail electricity price and CO2 emissions are negative and stronger in the mid-quantiles of crude oil price. This suggests that retail electricity prices and environmental indicator dampen crude oil prices during periods of low crude oil prices. These findings are robust to multivariate Quantile regression and Kernel-based Regularized Least Squares (KRLS) estimates. Therefore, our study suggests time-varying policies to dampen the effects of energy demand, retail electricity price, and environmental indicator on crude oil prices in the USA.

Blockchain Enabled Decentralized Local Electricity Markets With Flexibility From Heating Sources

Electric power systems are transitioning towards a decentralized paradigm with the engagement of active prosumers (both producers and consumers) through using distributed multi-energy sources. This paper proposes a novel Blockchain based peer-to-peer trading architecture which integrates negotiation-based auction and pricing mechanisms in local electricity markets, through automating, standardizing, and self-enforcing trading procedures using smart contracts. The negotiation of the volume and price of the peer-to-peer electricity trading among prosumers is modeled as a cooperative game, and the interaction between a retailer and its ensemble of prosumers is modeled as a Stackelberg game. The flexibility provision from residential heating systems is incorporated into the energy scheduling of prosumers. Case studies demonstrate that the proposed architecture in local electricity markets helps improve local energy balance. Flexibility from the residential heating systems enables prosumers to be more responsive to the variation of retail electricity prices. The proposed model reduces 41.24% of average daily electricity costs for individual prosumers or consumers compared to the case without the peer-to-peer electricity trading.

Economic Implications of the Climate Provisions of the Inflation Reduction Act

ABSTRACT: The Inflation Reduction Act (IRA) represents the largest US federal response to climate change to date. We highlight the key climate provisions and assess the act's potential economic impacts. Substantially higher investments in clean energy and electric vehicles imply that fiscal costs may be larger than projected. However, even at the high end, IRA provisions remain cost-effective. The IRA has large impacts on power sector investments and electricity prices, lowering retail electricity rates and resulting in negative prices in some wholesale markets. We find small quantitative macroeconomic effects, including a small decline in headline inflation, but macroeconomic conditions—particularly higher interest rates and materials costs—may have substantial negative effects on clean energy investment. We show that the subsidy approach in the IRA has expansionary supply-side effects relative to a carbon tax but, in a representative-agent dynamic model, is preferable to a carbon tax only in the presence of a strong learning-by-doing externality. We also discuss the economics of the industrial policy aspects of the act as well as the distributional impacts and the possible incidence of the different tax credits in the IRA.

Relationship between intrinsic motivation and gender in the context of x and y leadership styles in the macedonian electrical appliances sector

Leadership is one of the most researched topics in the contemporary business organisations. Over the decades, leadership and various leadership styles have proven to be key to successful organisations. As the world is currently experiencing many transformations and new generations of employees take over, the leadership styles evolve and leaders seek for new approaches to motivate and inspire employees in achieving growth both on individual and organisational level. Accordingly, this paper explores two distinctive leadership styles, more specifically, democratic or transformational and autocratic or transactional. The research is based on the McGregors’Theory X and Theory Y of leadership. As such, X Theory argues that employees avoid tasks and responsibility, desire to be controlled and lack ambition, while Y Theory assumes that employees are creative and positive about their work, and take actions to accomplish the organisational goals. Furthermore, the paper builds upon the theoretical concept of the previous research body on leadership styles and the importance of intrinsic motivation. The concept of intrinsic motivation is further enriched with the gender perspective. The analysis anticipates quantitative research based on a previously validated instrument that was implemented among 187 employees in the biggest Macedonian electrical appliances retail company. Findings suggest that there is positive relationship between Y leadership styles and intrinsic motivation. In addition, it was identified the both male and female demonstrate similar behavior relative to Intrinsic motivation. This research endeavour, shall contribute towards understanding the current practices and desired leadership styles in a dynamic organizational setting that seeks physical interaction with the customers in a highly competitive setting such as the electric appliances retail industry in the Republic of North Macedonia. It offers grounds for further research to overcome the limitations of this paper such as the sample size, male gender prevalence and generalisation for retail industry of electrical appliances as a whole given the administration of the instrument in a single company.

Performance analysis of a robust and multi-approach model in retail electricity market achieving efficient contracts between retailer, end users and wholesalers

Performance analysis of a robust and multi-approach model in retail electricity market achieving efficient contracts between retailer, end users and wholesalers

A deterministic bounding algorithm vs. a hybrid meta-heuristic to deal with a bilevel mixed-integer nonlinear optimization model for electricity dynamic pricing

In the electricity retail market, the retailer company aims to determine the optimal time-of-use (ToU) prices to maximize profits resulting from buying energy in organized (long-term, day-ahead, balancing) markets and selling it to consumers. Therefore, the retailer should take into account the consumer’s demand response actions to minimize the electricity bill in face of time varying prices. In this paper, this problem is formulated as a bilevel mixed-integer nonlinear programming model in which the retailer is the leader and the consumer is the follower. The consumer’s problem encompasses the integrated optimization of all home energy resources, considering re-scheduling appliance operation, charging/discharging of electric vehicle and stationary batteries, local microgeneration and (buying and selling) exchanges with the grid. The accurate physical modelling of appliance operation to generate effective load scheduling solutions imposes a high computational burden. Two algorithms are proposed to address this problem: a deterministic bounding algorithm (DBA) using an optimal-value-function approach for bilevel optimization, and a hybrid meta-heuristic using a particle swarm optimization algorithm to tackle the upper-level problem that calls an exact mixed-integer linear programming solver to deal with the lower-level problem. In the framework of the DBA, three different techniques were implemented to deal with the nonlinearities arising from the products of integer and continuous variables (bilinear terms): 1) solving the (non-convex) subproblems of DBA using a mixed-integer nonlinear solver, 2) using the McCormick envelopes to approximate the bilinear terms by linear ones, and 3) expressing the integer variables by binary ones and linearizing the bilinear terms using an exact form. Computational experiments are presented and discussed for real data settings of the problem under study considering a computational budget to compare the different algorithms and techniques employed. The results showed that the DBA with the approximate linearization technique (2) leads to the best solutions.

New Business Models in the Energy Sector in the Context of Revolutionary Transformations

The relevance of the problem of improving business models in the energy industry has become especially acute in recent years due to the energy transition, the emergence of new energy production and consumption technologies, and the increase in environmental requirements for energy companies’ performance. The purpose of the study is to form recommendations for creating business models in energy companies that meet modern realities and ensure the sustainable development of the energy business in an environment that is characterized by increased uncertainty and aggressive competition. Based on the analysis of scientific publications and the systematization of industry cases, it is proved that business models in the energy sector are likely to transform in the following three aspects: implementation of green technologies as a response to the public demand for clean energy; spatial organization of production based on platforms and digital tools; and active implementation of customized knowledge-intensive services. This article discusses the development of the social investment concept, the key factors affecting its implementation in the energy sector and related industries, and its risks and limitations in the times of energy crises. It is justified that new business models require changes in energy market infrastructure and strategic management principles. In this regard, the authors developed recommendations for the adaptation of the wholesale and retail electricity and power market to the structural, technological, and economic transformations in the energy production and consumption areas. The main advantages, barriers, and ideas for the effective implementation of innovative business models in energy companies are verified through an expert survey.

Exploring the value of electric vehicles to domestic end-users

Owing to the recent ban on the sales of new petrol and diesel cars in the United Kingdom (UK) by 2030, combined with the UK’s commitment to net-zero emission of greenhouse gases by 2050, a projected increase in the growth rate of electric vehicles (EVs) is inevitable. In recent years, there has been an increase in the adoption of EVs, but not at a rate sufficient to meet net-zero targets. Although benefits do exist for current EV owners, barriers such as the availability of charging infrastructure, total cost of ownership, battery costs, amongst others still present a challenge for the required adoption rate. In this work, we therefore aim to address some of these barriers, specifically the total cost of ownership and battery costs, by exploring the value a range of EVs on the market give to domestic end-users with different usage classes. Using a techno-economic-environmental mixed integer linear optimisation model which considers local energy demands, retail electricity tariffs, local renewable energy generation and battery degradation, potential benefits for EVs adopters are analysed from a cost or Carbon dioxide (CO2) minimisation objective. This model adopted considered a range of vehicle types – EVs and non-EVs – and properties, installed PV sizes, and user travel behaviour classes, and results showed that although EVs have a relatively higher purchase costs, total cost values are comparable, in some cases cheaper, when compared with conventional non-EVs. EV users further gain from environmental benefits through a reduction in the CO2 emitted irrespective of the user’s desired goal. A dominance analysis was also carried out to determine the order of importance of key input variables to the optimisation model in predicting costs and CO2 emission quantities. The results obtained are helpful to end-users in prioritising EV features during purchase based on personal goals of cost or carbon emissions reduction.

The Cost Efficiency of the Electricity Retailers with the Integration of the Cloud Energy Storage

As a result of market liberalisation, a large number of electricity retailers have emerged in the electricity market. Acting as the intermediaries between the electricity producers and the customers, the electricity retailers aim to balance the supply and demand and shoulder substantial risks generated from both sides. Due to the randomness of the electricity load, it is difficult for electricity retailers to make an accurate electricity purchasing plan in advance to meet customer demand. This deviation leads to a proportion of spot electricity purchases that require a higher purchase cost. As a result, one of the most serious concerns facing electricity retailers is how to improve their balancing abilities and reduce power purchase deviation. In contrast to previous research, which has generally recommended that electricity retailers invest in energy storage systems or develop optimised purchasing strategies, this paper proposes a new strategy for the electricity retailers, which is renting external flexible resources to solve the market uncertainty of the electricity retailers, thereby lowering purchase costs and increasing profits. The proposed business model makes use of the cloud energy storage to solve the supply-demand imbalance issue of electricity retailers. The cost calculation model and decision optimisation model have been established in the process of renting cloud energy storage. Charging and discharging cloud energy storage have been separately rented to deal with different positive and negative load deviations, which can simplify the optimisation model. As an experimental paper, the proposed model has been tested in the PJM power market in the United States and the New South Wales power market in Australia. The findings confirm that renting the cloud energy storage capacities can significantly reduce costs and maximise profits for the electricity retailers when compared to the situation without the cloud energy storage. The biggest saving can reach 24.5% in the PJM market. With the rapid fall of battery prices, the advantage of the proposed strategy will be more obvious.

An incentive mechanism to promote residential renewable energy consumption in China's electricity retail market: A two-level Stackelberg game approach

This paper proposes an incentive mechanism considering three different participants: the government, retailers and residents. To comprehensively understand the impact factors contributing to renewable energy consumption, the incentive mechanism is conducted in two forms, monetary incentive and price incentive, under the regulation of government and retailers. A two-level Stackelberg game is formulated to operate the proposed incentive mechanism. In the upper-level game, the government first sets the optimal monetary incentive to minimize its cost and then retailers determine the optimal incentives to maximize their profits. Similarly, in the lower-level game, the retailers send the incentive signals to residents, directing them choose the optimal renewable energy consumption ratios to maximize their welfare. The existence and uniqueness of Stackelberg Equilibrium are proved and the optimal strategies for each participant are given. To better describe the characteristics of residents, the seasonal variation of power demand and renewable energy, such as photovoltaic and wind power, is taken into consideration in the case study. The results indicate that, first, the cooperation of government and retailers raises the consumption ratio by 51.80% compared with 26.03% of individual participation of retailers in the winter typical day, which is the most effective seasonal day to operate the proposed incentive mechanism. Second, monetary incentive and price incentive can both promote renewable energy consumption, but the enhancement with price incentive is 77.04%, which is more than 51.80% with monetary incentive, in the winter typical day as well. The results also suggest that the proposed incentive mechanism should be applied to strengthen the electricity retail market position and achieve the carbon reduction goals.

Alert the Inert? Switching Costs and Limited Awareness in Retail Electricity Markets

We quantify how switching costs and limited awareness affect consumer inertia in liberalized retail electricity markets by developing and estimating a structural demand model using a novel dataset on electricity contract choices in Belgium. Our data allow us to disentangle different sources of inertia by using a rich combination of macromoments and micromoments. We find that consumers perceive contracts as differentiated and both limited awareness and switching costs hinder efficient choices. Our counterfactuals reveal substantial welfare gains from alleviating both frictions, in particular switching costs, and that a well-regulated monopoly can generate similar consumer surplus as the current deregulated market. (JEL D12, D83, L13, L43, L94, L98)

Pass-through in residential retail electricity competition: Evidence from Pennsylvania

Pass-through in residential retail electricity competition: Evidence from Pennsylvania

Analysis and optimisation of collective self-consumption in residential buildings in Spain

Studies on self-consumption in residential use are constantly evolving, and society claims new solutions in response to changes to new paradigms. This paper aims to optimise the sizing of a self-consumption installation for collective self-consumption in a residential building under the Spanish regulatory framework. The study considers the current price volatility in the retail electricity Spanish market and focuses on the techno-economic analysis of self-consumption in a building consisting of 12 dwellings using photovoltaic energy and the possible support of a storage system. The three aspects analysed are the sizing of the self-consumption facility, the use of smart appliances to shift their consumption to more cost-effective times and the sharing of the renewable energy generated by the facility among the consumers participating in the collective self-consumption. This study employs two models, an average-day model and a whole-year model. The techno-economic analysis yields that between the two self-consumption modalities for residential consumption, the modality with surplus simplified compensation is more profitable than the one without surpluses. Finally, the study focuses on sharing the total renewable energy generated among the participants. The results indicate that both ex-ante and ex-post dynamic sharing brings few benefits.

Looking Beyond Power Generation to Achieve Electricity Sector Net‐Zero Goals

It has long been accepted that decarbonization of the electric power sector is critical for achieving the reduction in greenhouse gas (GHG) emissions necessary for combatting the worst impacts of climate change. Electricity generation is one of the main sources of global carbon dioxide (CO2) emissions and reducing the carbon intensity of electricity production can increase the efficacy of other decarbonization efforts, such as electrification of transportation or heating. Due to the importance of electricity decarbonization, there has been increasing public and regulatory pressure for retail electricity providers—including distribution utilities—to decarbonize, resulting in 29 of the 30 largest utilities in the United States committing to a net‐zero goal by 2050 at the latest, with some committing to the landmark as early as 2030. To achieve these net‐zero goals, load serving utilities will need to reduce emissions across their Scope 1, 2, and 3 emissions as illustrated in Figure 1. Historically, utilities have primarily focused on their Scope 1 emissions, transitioning their generation and market purchases of electricity away from fossil fuels. While decarbonization of the energy generation mix is critical to achieving the reduction of emissions necessary to achieve net‐zero goals, utilities also need to make investments to decarbonize other areas of their operations if they want to make meaningful claims of achieving net‐zero.

Residential electricity package model considering load difference penalty in China

The increasing load difference between peak and off-peak seasons has led to the unstable operation of China’s power systems in recent years. In addition, the current electricity package structure system of China, which is gradually liberalizing its electricity market, remains imperfect. This paper establishes a model of residential electricity packages that considers load difference penalty during peak and off-peak seasons. First, consumers’ utility of different packages is established and thus the optimal is determined by maximizing the utility function. Then, a mathematical model focusing on the minimization of load difference of retail electricity packages during peak and off-peak seasons is established. We thus design a particle-swarm based algorithm to solve the problem. Through simulation results of several numerical examples, we demonstrate that the profit of retailer is increased by 37.35% and Load difference during peak and off-peak seasons is reduced by 78.01%, improving the power demand curve of users and the operation efficiency of power systems.

Multiple dynamic pricing for demand response with adaptive clustering-based customer segmentation in smart grids

In this paper, we propose a realistic multiple dynamic pricing approach to demand response in the electricity retail market. First, an adaptive clustering-based customer segmentation framework is proposed to categorize customers into different groups to enable the effective identification of usage patterns. Second, customized demand models with important market constraints which capture the price–demand relationship explicitly, are developed for each group of customers to improve the model accuracy and enable meaningful pricing. Third, the multiple pricing based demand response is formulated as a profit maximization problem subject to realistic market constraints. The overall aim of the proposed scalable and practical method aims to achieve ‘right’ prices for ‘right’ customers so as to benefit various stakeholders in the system. The proposed multiple pricing framework is evaluated via simulations based on real-world datasets. We find that: (1) the adaptive clustering based approach can capture the dynamically changing consumption patterns of customers, and enable the dynamic group based demand modelling; and (2) the multiple pricing strategy could achieve better profit gain for the retailer compared with the uniform pricing due to its reduced electricity purchasing cost in the wholesale market.

Shaping the energy transition in the residential sector: Regulatory incentives for aligning household and system perspectives

The regulatory framework influences households’ decisions in the context of the energy transition, affecting the potential for CO2 emissions savings and the operation of the electrical network infrastructure. In this paper, the profitability and optimal operation of alternative home energy systems (HESs) consisting of photovoltaics (PV), battery energy storage (BES), and either a gas condensing boiler (GB) or an electrical air-to-water heat pump (HP) is investigated for the case of a German single-family house and across alternative regulatory scenarios. Two policy reforms are considered: (i) an alternative design of network tariffs, the objectives of which are the financial sustainability and the efficient operation of the power grid, as well as the cost reflectivity of such charges; and (ii) a CO2-oriented reform of energy taxes and surcharges on retail energy prices. For the latter, the real-time carbon intensity of grid electricity is estimated and priced in dynamic retail electricity rates. After the optimization of the operation of each alternative HES under such alternative sets of price signals, a simulation over a 20-year planning horizon is carried out in order to evaluate each option in terms of profitability, impact on CO2 emissions and grid integration. The findings show how a change of regulatory framework can foster a low-carbon-oriented and grid-friendly adoption and operation of energy technologies. In the case under analysis, a regulatory shift: (i) results in a decrease of up to 17% in the discounted lifetime costs of the HP heating, thereby steering the household’s adoption decision towards a reduction of up to 63% in CO2 emissions; (ii) induces a grid-oriented operation of the HP and the BES, reducing coincident peak demand by up to 62%. The implications of such a regulatory shift are discussed in relation to the effectiveness, cost efficiency and distributional fairness of the energy transition in the residential sector.