Retail Energy Research Articles

Clean Energy Challenges and Innovation Opportunities in Kazakhstan

Abstract Kazakhstan has pledged to transition to a low-carbon economy by implementing national policies and strategies that promote clean energy innovation. However, Kazakhstan is still falling short of its expected targets for energy transition, and there is a lack of knowledge regarding the country's challenges and opportunities for clean energy development. Towards this end, the current study identifies and assesses the enablers and barriers related to clean energy innovation in Kazakhstan. Using the combination of SWOT analysis, survey data from 41 experts and the DEMATEL decision support tool, we evaluated the key factors affecting Kazakhstan's clean energy innovation and their implications for energy transition. Assessment results show that the immature business environment, underpinned by technological, institutional, and socioeconomic factors, is perceived as a high-impact constraint for clean energy innovation and green finance deployment in Kazakhstan. Skilled labour shortages, high reliance on hydrocarbons and low retail energy prices are significant challenges to Kazakhstan's clean energy innovation. The low-profit margin and high investment risk in clean energy projects are identified as transition barriers in the power and energy-intensive industries. In contrast, Kazakhstan's endowments of resources critical for developing clean energy technologies (rare earth metals, uranium, gas) and the potential of low-carbon investments (e.g. carbon storage) are perceived as prominent enablers of clean energy innovation. Results are consistent across expert subgroups (academia, industry, NGOs, etc). Findings call for policy support to modern and attractive business environments, capacity, and human capital development. The findings can provide helpful insights for countries in Central Asia and beyond with similar socioeconomic structures that aim for a timely energy transition.

Determinants of the Relationship between Wholesale and Retail Energy Prices in the Czech Republic

Rising energy prices have become a focus of interest for politicians at the international, European, and national levels. Energy prices are the main determinant of profitability or even the existence of the industrial sector. So, it is accepted that energy policy aims to ensure a secure, sustainable, competitive, and affordable energy supply for households and businesses. However, the recent geopolitical situation has significantly affected the energy policy of the European Union, raising concerns about energy security and an energy crisis. This crisis has had social, economic, and political consequences, including energy poverty. In this context, it is essential to understand the determinants of the relationship between wholesale and retail energy prices. This paper presents a model proposal to be used by the Czech Energy Regulatory Authority. The model of average retail prices depends on the type of contract - spot or forward, with the three-year forward contract having the largest weight on the retail price. Therefore, our study shows that long-term contracts significantly impact retail energy prices, highlighting the importance of regulatory monitoring of market strategies. Methodologically, the model is based on a multivariate regression analysis solved with the least absolute deviations and data for the period 2012 to 2023. The findings of the study contribute to a better understanding of the complexity of the dynamics of energy prices and support policymakers while attempting to ensure energy affordability and sustainability.

Optimal Energy Management System in Thailand Convenience Stores

The purpose of this research is to study and investigate the energy consumption and reduction of convenience stores. There is one retail building that is increasing rapidly in Thailand every year, and almost all of them operate 24 hours per day. There is a significant amount of energy consumption. This research is to present an updated energy portion of convenience stores through sampling at 13 stores. These stores have a sales area of 153 to 311 m2 and operating hours of 16 to 24 hours per day. We found that energy consumption recorded from the Digital Energy Meter shows that all of them have cooling systems that use a huge portion of energy (refrigeration and air conditioning systems, 48% and 24%, respectively). Moreover, this research aims to develop a Retail Energy Management System (REMS) to increase the energy efficiency of air conditioning systems at convenience stores in Thailand while still maintaining comfort for occupants by keeping the required temperature at 26 degrees Celsius. We selected 3 of 13 stores that have the same sales area of 280 m2 but different operating hours and numbers of air conditioners. We optimized the operating air conditioning system by data-driven with the Internet of Things system concept, which manages and controls the air conditioning system through the Programmable Logic Control (PLC) program. REMS can reduce energy consumption by 24 and 15 kWh/day, or 14.5% and 8.3%, at operating hours of 24 and 16 hours per day, respectively. There is an average return on investment (ROI) of 3-5 years, depending on the operating hours of the store. In the future, regarding the infrastructure of energy management systems, that can extend to finding some opportunity to save energy consumption in another system, for example, the refrigeration system of their convenience stores.

Willingness-to-pay for low-carbon residential heating systems: A discrete choice experiment among Dutch households

Most studies on decarbonizing space and water heating focus on the potential of low-carbon heating technologies from a top-down perspective, while there has been limited research on consumer preferences for low-carbon heat. To address this gap, we conduct a discrete-choice experiment among 1797 individuals in the Netherlands to estimate the willingness-to-pay (WTP) for residential-heating systems. Our results from the latent-class logit (LCL) model indicate that, on average, Dutch households are willing to pay a premium on their current monthly energy bill of 33% for electricity and 29.4% for hydrogen relative to using gas for heat production, 15.3% for reducing the amount of CO2 emissions per kWh of heat with 100 g and 16% for having the option to switch between energy retailers. In contrast, they require a discount of 28.4% for district-heating systems relative to standalone home appliances. Additionally, the class-profiling analysis indicates that individuals with higher education and income levels in the Northern Netherlands have the highest WTP for low-carbon electricity and hydrogen. These findings suggest that policymakers should favor decentralized heating solutions over district-heating systems to facilitate an energy transition in the residential sector. If district-heating systems are implemented, combining them with electricity or hydrogen instead of natural gas is recommended to realize higher consumer welfare.

System dynamics model for analysis of demand response on incorporating autoswitch in the Colombian electrical sector

This study investigates the potential outcomes of transforming the Colombian electricity market—70% of which is regulated—into a deregulated market. Given the impact of climate change and the need for greater control over the Colombian retail energy sector, it is crucial to examine future scenarios where two policies, successful in other countries, could improve market management. A simulation was conducted using a system dynamics model to analyze residential user behavior by manipulating demand response and implementing an autoswitch policy. The results validate the effectiveness of regulating electricity consumption through price management and the autoswitch policy, where customers can automatically switch suppliers. By 2033, these policies could reduce electricity prices by 11%–14%, depending on weather and user behavior changes, leading to significant customer savings, especially for higher-income groups, while ensuring suppliers' profitability. Although the conclusions suggest a positive outlook, the implementation of these policies requires regulatory changes and the adoption of smart energy meters. he proven policies could help Colombian government in managing consumption during energy crises.

The Optimization of Chillers Air-Conditioning in Thailand Supermarkets using a Retail Energy Management System (REMS)

Supermarkets in Thailand continue to grow and there will be more than 1500 branches by 2023 open 18-24 hours a day. In this research, we will present how to increase energy efficiency in retail stores by reducing the energy consumption of compressors of chiller air conditioning systems by using energy management systems in retail stores. Retail energy management systems in retail stores use the Internet of Things to connect to a device to store data and analyze and process from big data, then Artificial Intelligence controls and commands to make the air conditioning system energy efficient. Controlling 10 AHUs using central sensors at the sales area instead of return sensors allows us to save 25% of energy or 12,886 kWh/Year. As for the cold-water pump, it is controlled by an inverter. By using sensors to measure the water flow rate, we save 33% of energy or 19,755 kWh/Year. When controlling the water pump and AHU, the chiller compressor will save energy because when the air handling unit and the water pump have reduced work, the work of the compressor to cool water is reduced as well, resulting in energy savings of 12% or 25,211 kWh/Day. Using such a system reduces the overall energy consumption of the chiller air conditioning system. 17% or 57,852 per year has a payback period of 3 years and can also be extended to other systems within the store or other stores.

Decentralized energy trading framework with personalized pricing for energy community embedded with shared energy storage

Decentralized energy trading techniques are promising to become the next-generation scheme for energy management with the transformation of energy systems. Influenced by the sharing economy principle, the deployment of shared energy storage (SES) can mitigate the investment of storage devices and facilitate the construction of decentralized energy trading. Under such circumstances, this paper proposes a comprehensive energy trading framework for the energy community constituted of SES, prosumers, and retail energy providers. A Stackelberg game method is utilized to depict the interactions between prosumers and SES, where SES is performed as a leader and prosumers are followers. Besides, prosumers participate in the market to optimize social welfare via peer-to-peer (P2P) energy sharing with other prosumers or energy trading with SES and the main grid. We prove the existence and the uniqueness of the Stackelberg equilibrium (SE). Considering the supply and demand ratio and market contribution, a personalized pricing approach is presented for prosumers and SES to promote market competitiveness. We leverage the fully decentralized algorithm based on the fast alternating direction method of multiplier (ADMM) to solve the model of prosumers. Finally, numerical simulation demonstrates that the proposed transactive framework is economically beneficial for all participants, including SES and prosumers.

Master slave game-based optimization of an off-grid combined cooling and power system coupled with solar thermal and photovoltaics considering carbon cost allocation

Analogously to power trading models used by electricity companies, the implementation of an energy retailer can address the trading challenges experienced by end-users with decentralized energy consumption patterns. This research develops an off-grid solar-gas energy system to fulfill the cooling and power needs of buildings. Upon creating thermodynamic models, an innovative energy trading mechanism is introduced through an energy retailer, followed by the application of a master-slave optimization method aimed at maximizing participants' profits while incorporating carbon trading and demand response strategies. Through a case study and comparison of four different scenarios, the findings demonstrate that integrating solar thermal and electrical systems leads to the highest profitability, with the energy system's revenues remaining below 10%. The study determines the maximum selling prices for cooling and electricity as 0.231 $/kWh and 0.232 $/kWh, respectively, and highlights that varying carbon allocation rates have minimal effects on user profits. This work sheds light on the sustainable progression of distributed energy systems and presents motivating implications for a diverse audience interested in such advancements.

How to Refine Electric Utility Compensation for Increasing DER Market Participation

As the energy sector embraces the core principles of sustainability, North America's electricity markets are experiencing a paradigm shift. The proliferation and acceptance of distributed energy resources (DERs) have fundamentally altered the dynamics of electricity generation and distribution, and how we leverage energy storage and demand response.1 This is especially true for all utility types and DER owners/representatives, on the distribution system. While many consumers with DERs have successfully navigated the wholesale and retail energy markets, many challenges still exist with traditional utility models, sparking a reevaluation of compensation mechanisms for energy providers on the distribution system.

Strategic Behavior of Competitive Local Citizen Energy Communities in Liberalized Electricity Markets

The liberalization of energy retail markets empowered consumers with the ability to be part of new emerging entities, such as Citizen Energy Communities. With the increasing penetration of decentralized variable generation, communities have the advantage of incentive local carbon neutrality and sustainability. Local generation reduces transport grid usage and costs to consumers. Furthermore, worldwide legislation incentives energy communities by providing them discounts to other fee parts of the tariff apart from wholesale prices. This paper presents a model of strategic behavior, investment, and trading of energy communities. The model comprises the investment in local renewable generation, the design of competitive tariffs, and strategic bidding on wholesale markets. Consumers have an optimization model that selects the retail tariff that minimizes their costs with energy. These models are tested using data from Portuguese consumers and the Iberian electricity market. Results from the study indicate that inflexible consumers may reduce their costs by 29% by being part of the community. Furthermore, they have the potential to reduce their costs above 50% when using demand–response, adapting themselves to local production and wholesale prices.

Dynamic pricing optimization for commercial subcontracting power suppliers engaging demand response considering building virtual energy storage

Commercial buildings have abundant flexible energy resources for demand response (DR). The electricity price for tenants in the commercial building is generally issued by a subcontracting power supplier (SPS), and the tenants cannot directly interact with the energy retailer. Therefore, the incentive for tenants to participate in DR is insufficient, and their potential is not fully explored. To address these issues, this paper proposes a dynamic pricing method based on the Stackelberg game, helping tenants actively participate in DR. Then, with the optimized energy consumption of the tenants, a virtual energy storage model of the commercial building is constructed by aggregating the adjustable capabilities of flexible energy resources such as air-conditioning (AC) and electric vehicles (EVs) in the public area. Finally, simulation tests are conducted based on a real commercial building to demonstrate the effectiveness of the game-theoretic pricing approach and validate the role of virtual energy storage of the building in DR.

Energy Community Management Based on Artificial Intelligence for the Implementation of Renewable Energy Systems in Smart Homes

The trade, control, and management of transactive energy have gained significant relevance and are receiving a lot of interest from academia and industry. New strategies for their progress and implementation are emerging. The prosumer concept involves the integration of household loads with solar PV and battery storage systems. It is suggested as a practical technique to include renewable energy sources and reduce strain on the distribution grid. This study indicates establishing a home-smart community connected to a power grid, explicitly emphasizing prosumers. The district employs cooperative game theory to enable the sharing, controlling, and coordinating of excess energy generated by distributed energy resources (DERs) with neighboring prosumers experiencing energy shortages. The energy community examined in this study comprises six identical prosumers, encompassing residential energy use, solar photovoltaic (PV) installations, and battery storage systems. Furthermore, the community consists of an energy community manager and an energy retailer, both tied to a distribution system. The intended market model assesses the economic advantages of incorporating renewable sources into a centralized transactive energy trading system This approach reduces transaction costs and power expenditures, offering cost savings to producers and consumers. The results show that the suggested intelligent method has successfully decreased consumer electricity costs in various circumstances. Indeed, the proposed approach seeks to oversee the exchange, organization, and control of the community’s household electricity consumption effectively. Furthermore, its objective is to diminish energy usage, enhance system effectiveness, and minimize operational strain and carbon emissions.

Nonzero-Sum Stochastic Impulse Games with an Application in Competitive Retail Energy Markets

We study a nonzero-sum stochastic differential game with both players adopting impulse controls, on a finite time horizon. The objective of each player is to maximize her total expected discounted profits. The resolution methodology relies on the connection between Nash equilibrium and the corresponding system of quasi-variational inequalities (QVIs in short). We prove, by means of the weak dynamic programming principle for the stochastic differential game, that the equilibrium expected payoff of each player is a constrained viscosity solution to the associated QVIs system in the class of linear growth functions. We also introduce a family of equilibrium expected payoffs converging to our equilibrium expected payoff of each player, and which is characterized as the unique constrained viscosity solutions of an approximation of our QVIs system. This convergence result is useful for numerical purpose. We apply a probabilistic numerical scheme which approximates the solution of the QVIs system to the case of the competition between two electricity retailers. We show how our model reproduces the qualitative behavior of electricity retail competition.

Risk Analysis of Transactive Energy Retail Markets

Risk Analysis of Transactive Energy Retail Markets

A robust benchmarking of direct margin in Italy's energy retail markets

In the 2000s, Italy liberalized its electricity and natural gas markets, and in 2016, it separated retail activities from other activities within these markets. Such differentiation is unique within Europe. Italy is an ideal case for investigating which operational factors may increase profit margins among electricity and gas retailers. The present analysis analyzes 120 retail operators in the Italian electricity and gas markets in 2020, using two models to assess their cost and commercial efficiencies in achieving high direct margin (defined as the difference between revenues and raw materials cost). The findings show a positive effect of size on efficiency.

A market-based real-time algorithm for congestion alleviation incorporating EV demand response in active distribution networks

The dynamic charging behavior of electric vehicles (EVs) is causing frequent line-overloading problems and serious power security issues. Controlled and smart charging mechanisms for EVs incorporating demand response (DR) may provide significant operational flexibility to the grid operators and reduce charging costs for EV users. However, controlling EV charging may cause inconvenience to individual EV users. A market-based mechanism is proposed in this research work that allows EV users and households to participate in the network congestion alleviation DR program online while maintaining the power quality. Consumers submit their charging requirements (e.g., charging power and charging deadlines) and load curtailment tolerances to the aggregator. The aggregator is an entity assumed to have a long-term contract with the distribution system operator (DSO) and regularly receives network congestion information on behalf of retail energy users. Lyapunov optimization (LO) framework is used to reschedule the EVs, and household loads using DC optimal power flow (DCOPF) to get the dynamic congestion cost signal (CCS). The developed strategy is tested on a modified IEEE 33-bus radial active distribution network (ADN). Simulation results illustrate that the designed algorithm is promising in mitigating network congestion by ensuring significantly fewer violations of network constraints (i.e., line limits) both in terms of capacity and frequency. It also results in less energy cost as compared to other benchmark algorithms, e.g., greedy algorithm, and provides a guarantee of meeting EV charging, and flexible household loads’ (FHL) delay tolerance constraints. The average curtailment ratio of FHL and the service delay for EV-charging requests are converged to the user-defined limits, i.e., 0.25 for curtailment ratio tolerance and 10 times-lots for EV service delay. Unlike other counterparts, the developed algorithm is especially suitable for real-time applications as the per-slot average computational cost is negligible, i.e., 0.55 s.

The combined effect of regulators’ and retailers’ actions to stimulate consumer participation in retail energy markets

Active consumer participation in retail markets is crucial for an affordable and sustainable energy transition. While energy regulators encourage active consumer participation through policies which decrease consumers’ switching costs, energy retailers seek to advance customer retention to boost profits. This study investigates how these seemingly opposing goals influence consumer participation in energy retail markets. Using data on the Dutch energy markets, we combine micro-economic and marketing insights through a retailer-aggregated panel vector auto-regression (VAR) model and a market-level VAR to analyse the dynamic interactions. The results indicate that the regulator affects consumer participation both directly and indirectly through energy retailers’ actions. We conclude that energy retailers’ acquisition and retention actions do not counteract the regulator’s efforts to increase active consumer participation. While retention actions lead to decreased switching behaviour, they concurrently decrease perceived switch costs while increasing search behaviour and the consideration to switch. Therefore, retention actions may still improve consumer welfare. Our research reveals mediating relations that require comprehensive examination of the overall impacts of regulatory policies and energy retailer’s actions.

Weathering the Storm: Planning and Building Smarter

The importance and challenge of utility distribution system strategy and planning cannot be overstated in light of climate change and the increasing frequency of extreme storms. Independent power producers, distributed energy resource (DER) providers, and retail energy providers similarly face the same challenges. The United States witnessed a record‐breaking hurricane season in 2020, resulting in staggering damages of approximately $95 billion. The most recent report from the Intergovernmental Panel on Climate Change (IPCC) highlights the urgency of reducing greenhouse gas (GHG) emissions to limit global warming to mitigate the disastrous and costly effects of climate change. The report indicated that these events are likely to become the norm and will worsen if mitigation and adaptation measures aren't established. These events are becoming more frequent and severe, making it imperative to establish effective mitigation and adaptation measures.

Predictive Analytics for Enterprise Innovation of Retail Energy Market Modeling of Integrated Demand Response and Energy Hubs

Many combined heat and power (CHP) energy hubs work within the following heat load mode in the wintertime to supply the request for heat, and renewable energy has been often restricted in the unified energy network (UEN) markets. The power Internet of Things (PIoTs) has enabled UEN to transmit data increasingly frequently. As a result of flexible connections among various UEN networks, renewable energy increases its accommodation capacity considerably. Thus, the purpose of the study is to optimize UEN within the backdrop of PIoTs. According to the impact of PIoTs on UEN, this paper develops the combined demand response (DR) process and the layout of the important parts of UEN. Afterward, this study develops a bi-level economic dispatching process based on the cyber-physical systems of PIoTs and UEN. In the dispatching process, the higher level optimizes the total UEN function; the lower level optimizes the demand-side equipment output and combined DR. Then, the gray wolf optimization scheme is used to solve the bi-level dispatch. Lastly, the standard UEN and the practical network have been used to verify the efficiency of the suggested process.

Mid‐Term Bidding Strategy for an Energy Internet Zone Based on Distributionally Robust Optimization

Energy internet zones (EIZ) supply multiple energy carriers to customers in certain regions. They can achieve high energy efficiency by energy cascade utilization. In mid‐term, they participate in the wholesale market and retail market simultaneously. Customers can shift their energy use among different hours and energy carriers to satisfy demand according to the retail prices. Unfortunately, multiple energy systems and markets bring various uncertainties on demand and prices. In this paper, the weekly bidding strategy for the EIZ is proposed to determine the optimal bilateral contracts to sign and the optimal energy retail prices. In retail market, the satisfaction degree and elasticity matrix describe customers' response. Distributionally robust optimization is adopted to consider the distributional uncertainties of random variables and Worst‐case Conditional Value‐at‐Risk is employed for risk management. The distributional uncertainties of pool prices and elasticity matrix are discussed in this paper. An EIZ in Shanghai, China is adopted to illustrate the proposed strategy. The results have great resistance to distributional uncertainties. The risk aversion and satisfaction degree affect the EIZ's strategy in wholesale market and retail market, respectively. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.