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Accurate load forecasting, especially in the short term, is crucial for the safe and stable operation of power systems and their market participants. However, as modern power systems become increasingly complex, the challenges of short-term load forecasting are also intensifying. To address this challenge, data-driven deep learning techniques and load aggregation technologies have gradually been introduced into the field of load forecasting. However, data quality issues persist due to various factors such as sensor failures, unstable communication, and susceptibility to network attacks, leading to data gaps. Furthermore, in the domain of aggregated load forecasting, considering the potential interactions among aggregated loads can help market participants engage in cross-market transactions. However, aggregated loads often lack clear geographical locations, making it difficult to predefine graph structures. To address the issue of data quality, this study proposes a model named adversarial graph convolutional imputation network (AGCIN), combined with local and global correlations for imputation. To tackle the problem of the difficulty in predefining graph structures for aggregated loads, this study proposes a learnable adjacency matrix, which generates an adaptive adjacency matrix based on the relationships between different sequences without the need for geographical information. The experimental results demonstrate that the proposed imputation method outperforms other imputation methods in scenarios with random and continuous missing data. Additionally, the prediction accuracy of the proposed method exceeds that of several baseline methods, affirming the effectiveness of our approach in imputation and prediction, ultimately enhancing the accuracy of aggregated load forecasting. [ABSTRACT FROM AUTHOR]

This research leverages bibliometric methodologies, enhanced by the visual analytics capabilities of CiteSpace, to meticulously examine the evolution and current trends in energy trading within power markets, analyzing 642 scholarly articles from the Web of Science Core Collection spanning from 1996 to 2023. The study aims to illuminate the prevailing research landscape, growth patterns, and future directions in energy trading dynamics. Key findings include: (1) A noticeable escalation in the volume of publications, especially from 2021 to 2023, indicating a burgeoning interest and rapid evolution in this research area; (2) The author and institutional collaboration networks are in a nascent stage, with a predominantly China-centric international collaboration pattern, including significant partnerships with the United States, Australia, and the United Kingdom; (3) The focal points of research are centered around themes such as "energy management", "demand-side innovation", "decentralized energy trading", and "strategic optimization", covering areas such as intelligent grid technologies, energy market dynamics, and sustainable energy solutions. The study recommends enhancing collaborative networks, fusing technological and strategic dimensions in research, increasing focus and funding for emerging technologies, and promoting wider international and cross-disciplinary collaborations to enrich the understanding of energy trading dynamics in the context of electricity markets. [ABSTRACT FROM AUTHOR]

The mass introduction of renewable energy sources (RESs) presents numerous challenges for transmission system operators (TSOs). The Italian TSO, Terna S.p.A., aims to assess the impact of inverter-based generation on system inertia, primary regulating energy and short-circuit power for the year 2030, characterized by a large penetration of these sources. The initial working point of the Italian transmission network has to be defined through load flow (LF) calculations before starting dynamical analyses and simulations of the power system. Terna 2030 development plan projections enable the estimation of active power generation and load for each hour of that year in each Italian market zone, as well as cross-zonal active power flows; this dataset differs from conventional LF assignments. Therefore, in order to set up a LF analysis for the characterization of the working point of the Italian transmission network, LF assignments have to be derived from the input dataset provided by Terna. For this purpose, this paper presents two methods for determining canonical LF assignments for each network bus, aligning with the available data. The methodologies are applied to a simplified model of the Italian network, but they are also valid for other transmission networks with similar topology and meet the future needs of TSOs. The methods are tested at selected hours, revealing that both approaches yield satisfactory results in terms of compliance with the hourly data provided. [ABSTRACT FROM AUTHOR]

This research incorporates an electricity market model based on a stochastic allocation of distributed resources and the analysis of an optimal demand response for a smart microgrid. This research develops a methodology that allows the application and comparison of various demand-response mechanisms and the analysis of the differences between them and the case of no-demand response, emphasizing economics, environmental care, demand curves, and other factors. By enabling more active participation by residential users of the smart microgrid, these demand-response methods help to flatten the demand curve and support the goals set by the electricity market model. Both conventional and non-conventional generators compete in the electricity market, with renewable energy sources preferred to encourage green generation. Conventional generators are required to supply electricity gradually, starting with the lowest pollution level. In addition, conventional generators are compensated for dispatch, system reliability, and availability. In addition, random variables are used in this study to predict initial load, solar radiation analysis, and biomass input before resources are optimized to meet demand. [ABSTRACT FROM AUTHOR]

P2P power trading is necessary for efficiently using consumer electricity not subject to FIT. However, the execution rules for P2P power trading do not include restrictions on voltage, and there is a trade-off between the activation of the P2P power trading market through the mass introduction of PV and the optimization of the voltage of the power distribution system. In addition, there is a tendency for output curtailment to be biased toward consumers connected to the end of the grid. Since consumers cannot choose the interconnection location, there are concerns about unfairness. In this study, we investigate a new P2P model that includes voltage constraints for the execution rules of P2P power trading to avoid voltage deviation while ensuring benefits and fairness for the participants. In the proposed model, to increase the incentive to participate in the P2P power trading market, we consider compensating consumers who receive output curtailment signals due to voltage constraints. In addition, the profit is secured by differentiating the compensation cost unit price depending on the contract's availability. A case study was conducted on this model using the IEEE 33 bus system. The results show that the proposed model is superior. [ABSTRACT FROM AUTHOR]

Climate change as a challenge we all are facing, varying degree of economic development as a result of COVID-19, the volatility in energy prices and political as well as other factors, most countries have restructured their electricity markets in order to facilitate the use of green renewable energy. The right energy mix in a period of energy transformation is the best strategy for achieving reduction of carbon emissions. Bulgaria is a special case because it has expanded the use of solar and wind energy exponentially, without conducting an adequate preliminary forecast analysis and formulating a parallel strategy for the development and expansion of the energy storage infrastructure. In this regard, the article is focused on how the power energy market is structured with the increasingly large-scale and global penetration of renewable energy sources as primary energy sources, observing several key factors influencing the energy transition. Due to the cyclical nature of energy production and the necessity for a smooth and efficient transition, a long-term seasonal storage plan should be considered. Furthermore, solar energy production facilities have a greater share of installed power, but wind power facilities generate a roughly equivalent amount of electric energy over the course of a year. One of the aims of this research is to discover an appropriate model for predicting the electricity output of wind and solar facilities located in Bulgaria that can be used to ease the transition process. Based on thorough data analysis of energy production over the past 11 years and 5 months, our findings suggest that a SARIMA model might be appropriate, as it takes into account the seasonal cycles in the production process. [ABSTRACT FROM AUTHOR]

In order to accelerate the construction of a clean, low-carbon, safe and efficient energy system, China set the provincial weight of responsibility for renewable energy power consumption and established a renewable energy power absorption guarantee mechanism in 2019. As a market incentive policy, it has enduring effect on the low-carbon transformation of the power industry. Firstly, the operation mechanism of the renewable energy consumption guarantee mechanism is analyzed. The general framework, core elements and supporting measures are clarified. Secondly, a stock-flow diagram is constructed based on the system dynamics method. It contains the green electricity market sub-module, the green-certificate market sub-module and the excess power absorption market sub-module. Finally, multiple scenarios are set up to simulate the impact of the green-certificate market and excess power absorption market improvements on the installed capacity and tariff of China's green power market. The renewable energy guarantee mechanism is an effective means to promote the consumption of green electricity in China. In addition, in the short term the cost of electricity for users has increased, but in the long term the cost of electricity shows a fluctuating downward trend. This study provides theoretical references for the formulation of clean and low-carbon policy objectives in the power industry and the optimization of market mechanisms. [ABSTRACT FROM AUTHOR]

Rising shares of variable wind and solar generation in decarbonized electricity systems motivate the development of novel power cycles employing unconventional fuels. Innovative designs must be highly flexible and profitable at low capacity factors, requiring a simple process layout and low capital costs. Fuel supply infrastructure represents a significant additional capital cost, which is often ignored in economic assessments of gas-fired power plants. When these capital costs are included, liquid fuels such as NH3 or MeOH gain relevance despite their high production costs because they are cheap to store and distribute. In addition, chemically recuperated power cycle designs upgrade these fuels with waste heat from the gas turbine exhaust, avoiding a capital-intensive bottoming cycle while achieving high thermal efficiencies. This work presents an exergoeconomic benchmarking of different large-scale power plants and their fuel supply infrastructure. The results show that chemically recuperated cycles using MeOH become competitive relative to natural-gas-fired combined cycles with fuel storage in salt caverns at capacity factors below 32% if seven-day storage is required and plants are located 500 km from the fuel source. NH3 can compete with H2 at a higher capacity factor of 47% because of the high cost of storing H2, while a CO2 price of 140 EUR/ton is required for NH3 to outperform MeOH as a fuel. In cases where salt cavern storage is unavailable, or the energy security of multi-week fuel storage is highly valued, liquid fuels present a clearly superior solution. [ABSTRACT FROM AUTHOR]

This paper aims to reconsider prosumers' role in the power markets in the early stages of their decentralization, accounting for rising self-supply trends, security threats, and economic and regulatory barriers. The development of prosumerism envisages finding the ratio between retail market sales under the feed-in tariff and the net billing mechanism. Within the methodology section, the indicator of prosumer efficiency for electricity generation (EUR/kWh) is proposed based on average consumption/production ratios and consumption/delivery incentives. To support household prosumers, the mentioned incentives on the renewable energy market consider the self-supply cost of electricity, the levelized cost of electricity for small-scale green energy facilities (solar photovoltaic and wind), and transaction costs. This paper evaluates prosumer efficiency under three consumption/production ratio scenarios for Ukrainian households (self-consumption of 40%, 20%, and 100% of green electricity annually generated by a household and selling the leftovers via the feed-in tariff) for 2023. The gradual movement from fixed tariffs for households toward market-based prices promotes the emergence of new related market players and their consolidation in the market. Participation in the organized power market segments is relevant for day-ahead market prices above 130 EUR/MWh, disregarding the households' tariff rate. The low price caps inhibit the prosumer's participation in the market, while the transition from the feed-in tariff to net billing significantly promotes their development only under high price caps. [ABSTRACT FROM AUTHOR]

The consequences of the liberalisation of electricity markets have been widely discussed in the literature emphasising the successes or failures of privatisation and deregulation. While most developed power systems have undergone a form of economic transformation, they still require to be monitored and analysed to assess market power. The Polish power system is an example wherein the potential of market power examined fifteen years ago was summarised as significant. Since then, the transformation process and changes in the ownership structure have taken place. This study focuses on the assessment of the potential of market power in the Polish electricity market. For this purpose, statistics on power companies were collected and processed. Then, structural and behavioural measures were applied, including concentration ratios, the entropy coefficient, the Gini coefficient, the Herfindahl–Hirschman Index (HHI), the Residual Supply Index (RSI), and the Lerner Index. The results reveal that, despite a dynamic increase in renewable capacity, market concentration has increased in recent years, achieving an HHI of 2020.9 in 2021. An increase in the Lerner Index of lignite and hard coal-fired units is also observed, indicating high mark-ups by the key market players. Based on quantitative analysis, policy recommendations are outlined to reduce the negative impact of market power on consumers. [ABSTRACT FROM AUTHOR]

The penetration of power generations from renewable energy sources into the power market has a significant impact on the capacity factor of existing power generations. This is because power producers cannot recover a capital cost of power generations with high operating cost possibly due to underinvestment. One solution to address this problem includes a capacity mechanism; that is, the capacities of the power generations can be sold through a market or a bilateral contract. Many schemes of the capacity mechanism have been used worldwide. In this study, we examine an investment in a power plant in both the electricity and capacity markets. The effect of investment opportunity on uncertainty and risk aversion is analyzed by a real options approach that is one of analytical methods for investment decisions under uncertainty. The investment timing for the standard energy-only market is compared with that for the capacity market. When the risk averse for the power producer is relatively small, the income in the energy-only market is obtained whereas, when the risk averse is relatively high, the income is gained in both the electricity and capacity markets for the sake of enough profit. [ABSTRACT FROM AUTHOR]

This paper proposes a novel approach to optimizing the structure of the electricity market by mitigating market power through the use of forward contracts. The IEEE 30 node test system is used as a case study for the paper, which employs nodal pricing and a Cournot model with recursive optimization. The findings show that forward contracts can reduce market power and lead to a more competitive market structure with fewer participants. The study emphasizes the importance of successor companies having a well-balanced mix of generation technology. Six players with a different generational mix are optimal in the constrained nodal pricing scenario, while five players with slightly different mixes are optimal in the Cournot case study. These findings have important implications for policymakers and industry stakeholders involved in the design and implementation of efficient electricity markets. Market power can be reduced by using forward contracts and establishing an appropriate number of market participants, resulting in more efficient and sustainable electricity markets. Overall, this study provides useful insights for improving electricity market structures and increasing competition in the electricity sector. [ABSTRACT FROM AUTHOR]

The increasing limitations in the use of fossil fuels due to their limited availability and pollution have increased the use of renewable energies and storage systems for electricity generation. To achieve the goals of the integration of renewable energy, sizing and management methods for hybrid plants are needed to make investments profitable and attractive in these resources. This work presents an optimization method for the sizing and operation of hybrid plants with storage, choosing the best combination of technologies based on resource availability, installation costs and market prices, maximizing an economic index such as the net present value. One of the main contributions of this work is to reduce the oversizing that occurs in traditional methods through a penalty term for lost energy, encouraging investment in batteries to store excess energy above the point of interconnection (POI). In addition, it is intended to cover gaps such as the operation in coupled markets with different execution periods to maximize the benefits of the investment made and to contemplate different generation alternatives together with storage. The presented method is tested through sizing and operation simulations to demonstrate its potential. The presented method is tested through sizing and operation simulations to demonstrate its potential. In scenario A, the best combination of solar energy, photovoltaic energy and storage, is chosen. In scenario B, it is shown how the curtailment of the oversizing is reduced in some months by more than 5%. In scenario C, for daily operation in coupled markets, it is possible to improve the benefits from 0.7% to 37.04% in the days of the year. [ABSTRACT FROM AUTHOR]

Market power, defined as the ability to raise prices above competitive levels profitably, continues to be a prime concern in the restructured electricity markets. Market power must be mitigated to improve market performance and avoid inefficient generation investment, price volatility, and overpayment in power systems. For this reason, involving market power in the transmission expansion planning (TEP) problem is essential for ensuring the efficient operation of the electricity markets. In this regard, a methodological bilevel stochastic framework for the TEP problem that explicitly includes the market power indices in the upper level is proposed, aiming to restrict the potential market power execution. A mixed-integer linear/quadratic programming (MILP/MIQP) reformulation of the stochastic bilevel model is constructed utilizing Karush−Kuhn−Tucker (KKT) conditions. Wind power and electricity demand uncertainty are incorporated using scenario-based two-stage stochastic programming. The model enables the planner to make a trade-off between the market power indices and the investment cost. Using comparable results of the IEEE 118-bus system, we show that the proposed TEP outperforms the existing models in terms of market power indices and facilitates open access to the transmission network for all market participants. [ABSTRACT FROM AUTHOR]

Virtual power plants (VPPs) are an effective platform for attracting private investment and customer engagement to speed up the integration of green renewable resources. In this paper, a robust bidding strategy to participate in both energy and ancillary service markets in the wholesale electricity market is proposed for a realistic VPP in Western Australia. The strategy is accurate and fast, so the VPP can bid in a very short time period. To engage customers in the demand management schemes of the VPP, the gamified approach is utilized to make the exercise enjoyable while not compromising their comfort levels. The modelling of revenue, expenses, and profit for the load-following ancillary service (LFAS) is provided, and the effective bidding strategy is developed. The simulation results show a significant improvement in the financial indicators of the VPP when participating in both the LFAS and energy markets. The payback period can be improved by 3 years to the payback period of 6 years and the internal rate of return (IRR) by 7.5% to the IRR of 18% by participating in both markets. The accuracy and speed of the proposed bidding strategy method is evident when compared with a mathematical method. [ABSTRACT FROM AUTHOR]

In recent years, algorithmic-based market manipulation in stock and power markets has considerably increased, and it is difficult to identify all such manipulation cases. This causes serious challenges for market regulators. This work highlights and lists various aspects of the monitoring of stock and power markets, using as test cases the regulatory agencies and regulatory policies in diverse regions, including Hong Kong, the United Kingdom, the United States and the European Union. Reported cases of market manipulations in the regions are examined. In order to help establish a relevant digital regulatory system, this work reviews and categorizes the indicators used to monitor the stock and power markets, and provides an in-depth analysis of the relationship between the indicators and market manipulation. This study specifically compiles a set of 10 indicators for detecting manipulation in the stock market, utilizing the perspectives of return rate, liquidity, volatility, market sentiment, closing price and firm governance. Additionally, 15 indicators are identified for detecting manipulation in the power market, utilizing the perspectives of market power (also known as pricing power or market structure), market conduct and market performance. Finally, the study elaborates on the current challenges in the regulation of stock and power markets in terms of parameter performance, data availability and technical requirements. [ABSTRACT FROM AUTHOR]

The national carbon emission trading mechanism is an important policy tool for the Chinese government to control and reduce greenhouse gas emissions by using the market mechanism. The Beijing–Tianjin–Hebei power market is the focus of energy conservation and consumption reduction in China. Problems have already existed in the synergic development of the Beijing–Tianjin–Hebei power market and carbon trading market. In this article, the development status of the Beijing–Tianjin–Hebei power market is analyzed and the coupling mechanism between the carbon market and power market is combed out to build a synergism model of the carbon market and the Beijing–Tianjin–Hebei power market based on the system dynamics. From the research results, firstly, the Beijing–Tianjin–Hebei power market comes with a high energy consumption intensity and a high proportion of carbon emissions. The coupling of carbon market and power market forces the power industry to reduce carbon emissions through the effective transmission of carbon costs to power prices. Secondly, carbon price shows an upward trend in the context of the current policy scenario, which can give play to the role of price signal in the future. The revenue of thermal power plants, which are the carbon emission right sellers, with new technologies, has increased significantly, while the revenue of carbon emission right buyers, which are the manufacturers of undeveloped units, has increased less. Finally, the technical progress of thermal power plants, the introduction of auction mechanism, the increase in initial carbon price settings and the direct transmission of carbon costs are all factors that promote the effectiveness of carbon trading policy tools in the Beijing–Tianjin–Hebei power market. This study provides theoretical guidance for the synergic development of the "power-carbon" market. [ABSTRACT FROM AUTHOR]

Although many countries prefer deregulated power markets as a means of containing power costs, a monopoly may still exist. In this study, an agent-based bidding simulation framework is proposed to detect whether there will be a monopoly in the power market. A security-constrained unit commitment (SCUC) is conducted to clear the power market. Using the characteristics that the agent can fully explore in a certain environment and the Q-learning algorithm, each power producer in the power market is modeled as an agent, and the agent selects a quotation strategy that can improve profits based on historical bidding information. The numerical results show that in a power market with monopoly potential among the power producers, the profits of the power producers will not converge, and the locational marginal price will eventually become unacceptable. Whereas, in a power market without monopoly potential, power producers will maintain competition and the market remains active and healthy. [ABSTRACT FROM AUTHOR]

By studying M&A deals completed by European energy and power companies between 2002 and 2021, the paper inquires into the impact of corporate consolidation on the competitive positioning of individual energy firms and the concentration of market power on the national energy markets in the EU countries. Our evidence suggests that the European energy market may be moving towards a greater concentration of market power as market leaders are shown to primarily acquire their peers from national markets, while outsiders are more likely to diversify into non-energy sectors, which may further endanger their competitive positioning in the future. We also find that M&As allow energy and power companies to substantially increase their market share within national markets. The said impact is stronger in case of cross-border deals, including those within and outside of the EU. At the same time, only cross-border deals are associated with sufficiently strong revenue growth to advance firms' relative positioning within national markets. The relative positioning of firms in the EU market remains unaffected by M&A activities, which may be indicative of extreme rigidity and segmentation of the EU market. While at the country level, M&As are found to contribute to a reduction in market concentration measured by a number of indicators, this negative link is documented to be entirely driven by non-core acquisitions involving targets from non-energy industries. [ABSTRACT FROM AUTHOR]

The energy transition requires significant volumes of minerals of which the Global South holds large reserves. This context revives hopes and fears that producing countries in the Global South might hold sufficient market power to demand above market prices, technology transfers and even migration of productive processes to their countries. Our research question is what determines the effectiveness of states' collusion on natural resource exploitation and how does that affect the probability of Latin American collusion regarding lithium. The study utilizes Social Science methods for developing frameworks of analysis and comparative case studies. Following an overview of what is required for effective cartels, the study focuses on characteristics of the six primary lithium producers and potential producers in Latin America: Chile, Argentina, Bolivia, Brazil, Mexico, and Peru. Theory and empirical evidence indicate that Latin American lithium producers should be very cautious in assessing their bargaining power vis a vis the market. More focus should be put on how best to utilize market determined profits to support sustainable national development. The conclusion highlights limitations of Latin American countries' capacities and suggests future lines of research regarding potential commodity cartels for resources essential to the energy transition. [ABSTRACT FROM AUTHOR]

The effective identification of the economic withholding behavior of the generators can help ensure the fair operation of the electricity market. A SCAD-logit model is proposed to improve the performance of the logit model for the massive data of electricity market. First, a social network analysis method is used to construct an equity relationship graph of the generators to obtain a set of key monitoring generators. An indicator system for identifying the economic withholding behavior of the generators is constructed based on structure conduct performance (SCP) theory. The indicators are screened by the smoothed clipped absolute deviation (SCAD) penalty regression method to reduce the collinearity and improve identification efficiency. Then, a SCAD-logit model is established to identify the economic withholding of key monitoring generators, so that the boundary contributions of each indicator to the economic withholding behavior are obtained. The confusion matrix, ROC curve, and AUC values are used to evaluate the model's performance. Finally, the model is applied to the electricity spot market, and the method can identify the generators that exercise economic withholding behavior with a correct rate of 96.83%. Indicators such as market share, quotation fluctuation degree, high quotation index, and volume price index can be used as important indicators for identifying the economic withholding behavior. [ABSTRACT FROM AUTHOR]

Having a well-adapted transmission network is key for reaching a sustainable energy system, where generators and consumers participate in an efficient market. The purpose of the present research is to estimate the impact on the final prices of the interconnection of the two largest electrical systems in Chile. To this end, an econometric model is used in which prices, among other variables, are explained by the level of marginal costs in the system (opportunity cost), the degree of concentration in the market (market power), and the variability of marginal costs projected by the agents (risk). The data corresponds to bilateral contracts between generators and major clients, from 2006 to 2014. The basic results indicate that the interconnection would benefit final customers by reducing equilibrium contract prices, as a result of the decreased variability of expected marginal costs and a lower concentration of existing generating companies. This study's main contribution is to focus on the benefits of electricity interconnection under conditions of competition and risk, instead of using the simple estimation of direct costs, as has traditionally been done. [ABSTRACT FROM AUTHOR]

State and regional governments in the U.S. and abroad are looking to market-based approaches to mitigating greenhouse gas emissions from the electric sector, and in the U.S. as a compliance approach to meeting the aggressive targets of the Environmental Protection Agency (EPA)'s Clean Power Plan. Auction-based approaches, like those used in the Northeast U.S. and California, are both recommended strategies under the Plan and attractive to state governments because they can generate significant revenue from the sale of emissions permits. However, given the nature of imperfect competition in existing electricity markets, particularly at the state and regional level, the issue of market power is a concern at the forefront. This paper provides the results from a controlled laboratory experiment of an auction-based emissions market in the electricity sector. The results show that government revenue from auctioning emissions permits is substantially lower when market concentration is only moderately increased. The results hold significant implications for states and other subnational governments that have high revenue expectations from the auctioning of emissions permits. [ABSTRACT FROM AUTHOR]

In a deregulated market, independent system operators meet power balance based on supply and demand bids to maximize social welfare. Since electricity markets are typically oligopolies, players with market power may withhold capacity to maximize profit. Such exercise of market power can lead to various problems, including increased electricity prices, and hence lower social welfare. Here we propose an approach to maximize social welfare and prevent the exercising of market power by means of interruptible loads in a competitive market environment. Our approach enables management of the market power by analyzing the benefit to the companies of capacity withdrawal and scheduling resources with interruptible loads. Our formulation shows that we can prevent power companies and demand-resource owners from exercising market powers. The oligopolistic conditions are described using the Cournot model to reflect the capacity withdrawal in electricity markets. The numerical results confirm the effectiveness of proposed method, via a comparison of perfect competition and oligopoly scenarios. Our approach provides reductions in market-clearing prices, increases in social welfare, and more equal distribution of surpluses between players. [ABSTRACT FROM AUTHOR]

In the medium- and long-term market, the power generation side and the power purchase side ensure to avoid the fluctuation of delivery prices through the medium- and long-term power contract, to avoid some market risks. This paper combines virtual power plants to aggregate distributed renewable energy to participate in market transactions. Firstly, this paper analyzes the two operation modes of power markets and combs the transaction varieties and modes in the medium- and long-term market. Secondly, the common contract power decomposition methods in the medium- and long-term market are analyzed, and the revenue model of virtual power plants is established. Then, combined with the renewable energy quota system and the green certificate trading mechanism, this paper constructs an optimization model of medium- and long-term contract trading of virtual power plants considering renewable energy derivatives. Finally, different renewable energy output scenarios are designed to analyze the benefits of virtual power plants in centralized and decentralized power markets. The example analysis shows the effectiveness of price difference contract for virtual power plants to ensure the renewable power revenue, which provides a certain reference for virtual power plants to participate in the power market. [ABSTRACT FROM AUTHOR]

Power markets are becoming increasingly complex as they move towards (i) integrating higher amounts of variable renewable energy, (ii) shorter trading intervals and lead times, (iii) stronger interdependencies between related markets, and (iv) increasing energy system integration. For designing them appropriately, an enhanced understanding of the dynamics in interrelated short-term physical power and energy markets is required, which can be supported by market simulations. In this paper, we present an agent-based power market simulation model with rule-based bidding strategies that addresses the above-mentioned challenges, and represents market participants individually with a high level of technical detail. By allowing agents to participate in several interrelated markets, such as the energy-only market, a procurement platform for control reserve and a local heat market representing district heating systems, cross-market opportunity costs are well reflected. With this approach, we were able to reproduce EPEX SPOT market outcomes for the German bidding zone with a high level of accuracy (mean absolute percentage error of 8 €/MWh for the years 2016–2019). We were also able to model negative market prices at the energy-only market realistically, and observed that the occurrence of negative prices differs among data inputs used. The simulation model provides a useful tool for investigating different short-term physical power/energy market structures and designs in the future. The modular structure also enables extension to further related markets, such as fuel, CO 2 , or derivative markets. [ABSTRACT FROM AUTHOR]

Europe's initiative to reduce the emissions of harmful gases has significantly increased the integration of renewable sources into power networks, particularly wind power. Variable renewable sources pose challenges to sustain the balance between generation and demand. Thus, the need for ancillary services to cope with this problem has increased. In this regard, the integration of larger shares of wind generation would have a clear system benefit when wind generators are able to provide these ancillary services. This would also have implications for electricity markets, enabling these services from wind power plants. This article gives an overview of several European markets for frequency support (FS) services, also referred to as FS markets. It identifies the changes in national regulations of 10 European countries to standardize these services based on the ENTSO-E guidelines. However, most of the countries still use their national service definitions, which presents a problem for researchers to understand the national regulations in relation to the ENTSO-E guidelines. This article provides a classification of the national FS services under the definitions of the ENTSO-E guidelines to facilitate research on this topic. Furthermore, it highlights the main requirements for the market practices that would encourage the participation of wind power generation in the provision of these services. An estimation of the economic benefits for wind producers from the provision of FS services is provided as well to show a possible outcome if changes are not made in national policies. [ABSTRACT FROM AUTHOR]

In a competitive electricity market, both electricity retailers and generators predict future prices and volumes and execute electricity delivery contracts through power exchange. In such circumstances, they may suffer from uncertainties caused by fluctuations in spot prices and future demand due to their high volatility. In this study, we develop a unified approach using derivatives and forwards on the spot electricity price and weather data to mitigate the cashflow fluctuation for power utilities. We aim to clarify the applicability of our proposed methods and provide a new and useful perspective on hedging schemes involving various electricity utilities, such as power retailers, solar photovoltaic (PV) generators, and thermal generators. Moreover, we analyze the risk of risk takers (such as the insurance companies in this study) in the derivatives market. In addition, we perform empirical simulations to measure out-of-sample hedging effects on their cashflow management using actual data in Japan. [ABSTRACT FROM AUTHOR]

Chinese wind power policies have productively promoted the development of wind power and also promoted the process of wind power participation in electricity market transactions. However, with policy emphasis on investment and neglect of utilization, there have been some difficulties in the development of Chinese wind power. To highlight the guiding role of policy and improve the wind power policy system, an analysis of Chinese wind power policies is conducted in this paper. First, aiming at the main components of wind power chain, including wind power construction, grid connection, transmission, and sales, a comprehensive and systematic frame of Chinese wind power policy system is proposed from the three aspects of development planning, administrative management and market transactions. Second, the indicator system of Chinese wind power development effectiveness is extracted, including installed capacity, power generation, power utilization hours, carbon emission reduction, investment, on-grid power price, wind curtailment rate, etc., and the effectiveness of policy implementation is verified. Third, new policy recommendations are proposed from parts of transmission, consumption, and market, for the development of Chinese wind power industry in the 14th Five-Year Plan period and the goal to reach the crest value of carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. In this paper, advice to supplement and improve the Chinese wind power policy system is provided, which may it promote better development of Chinese wind power in the following decade from the policy point of view. [ABSTRACT FROM AUTHOR]

Although the Korean government plans to increase its share of variable renewable energies (VREs), the Korean power market is not sufficiently mature to accommodate a large increase in VRE generation. Thus, the Korean system operator plans to introduce a two-settlement, and an imbalance settlement is also under consideration, among several options. Therefore, this study analyzes how many incentives are given for prediction accuracy under several imbalance settlement schemes adopted from European and US power markets. Results show that the imbalance settlement consisting of threshold and penalty terms is useful for rule-makers, who can control revenue differences between the groups with different prediction accuracies by adjusting the two terms. The suggestion given in the paper will be useful for not only the Korean power market but also for the countries that plan to establish the imbalance settlement rules while increasing renewable energy. [ABSTRACT FROM AUTHOR]

Peer-to-peer (P2P) electricity sharing or trading can empower consumers and prosumers, incentivize the balancing of generation and demand locally, increase system resilience and reliability, and help in achieving societal goals, such as increasing renewable energy penetration. Nevertheless, the development of P2P trading in actual environments has been slow due to the unclear position of P2P markets in the power system. Recent developments in the European legislation are promising for the establishment of P2P markets and energy communities. Hence, the interplay between local trading and existing market structures needs to be addressed carefully. Furthermore, P2P trading with distributed resources presumes that electricity end users will become active players in the power system. This paper proposes a bidding and pricing mechanism for local markets, considering the external markets; a new approach to balance settlement and balance responsibility when local trading occurs; and an interface to promote end-user interest in, and interactions with, local energy trading. The proposed local market concept and interface solution promote the coupling between local and existing retail, wholesale and ancillary service markets, and can be seen as a step towards the establishment of local energy markets in real-life settings. [ABSTRACT FROM AUTHOR]

This research optimises the mix and structure of Generation Companies (GenCos) in the Sumatra power system, Indonesia. Market power, indicating the ability to raise prices profitably above the competitive level, tends to be a significant problem in the aftermath of electricity market restructuring. In the process of regulatory reform and the development of competitive electricity markets, it is desirable and practical to establish an efficient number of competitor GenCos. Simulations of a power system account for multi-plant mergers of GenCos subject to a regulatory measure of the Residual Supply Index and the influence of direct current load flow and the topology of the system. This study simulates the Sumatra power system in order to determine the following: optimal market structure, efficient GenCo generation mix, and the optimal number of competitive GenCos. Further, this study seeks to empirically optimise the electricity generation mix and electricity market structure of the Sumatra power system using DC load flow optimisation, market power index, and multi-plant monopoly analysis. The simulations include generation and transmission constraints to represent network constraints. This research is the first to analyse the Sumatra power system using imperfect (Cournot) competition modelling. Furthermore, this study is the first kind to optimise the mix and structure of the Sumatra generation power market. The guidelines and methodology in this research can be implemented in other countries characterised by a monopoly electricity utility company. [ABSTRACT FROM AUTHOR]

In this paper, the variations in hydropower generation are addressed considering the seasonality and ENSO (El Niño-Southern Oscillation) episodes. The dynamic hypothesis and the stock-flow structure of the Colombian electricity market were analyzed. Moreover, its dynamic behavior was analyzed by using Dynamic Systems tools aimed at providing deep insight into the system. The MATLAB/Simulink model was used to evaluate the Colombian electricity market. Since we combine System Dynamics and Dynamic Systems, this methodology provides a novel insight and a deeper analysis compared with System Dynamics models and can be easily implemented by policymakers to suggest improvements in regulation or market structures. We also provide a detailed description of the Colombian electricity market dynamics under a broad range of demand growth rate scenarios inspired by the bifurcation and control theory of Dynamic Systems. [ABSTRACT FROM AUTHOR]

In 20th century, many countries have liberalized their electricity market. This power markets liberalization has directed generation companies as well as wholesale buyers to undertake a greater intense risk exposure compared to the old centralized framework. In this framework, electricity price prediction has become crucial for any market player in their decision-making process as well as strategic planning. In this study, a prototype asymmetric-based neuro-fuzzy network (AGFINN) architecture has been implemented for short-term electricity prices forecasting for ISO New England market. AGFINN framework has been designed through two different defuzzification schemes. Fuzzy clustering has been explored as an initial step for defining the fuzzy rules while an asymmetric Gaussian membership function has been utilized in the fuzzification part of the model. Results related to the minimum and maximum electricity prices for ISO New England, emphasize the superiority of the proposed model over well-established learning-based models. [ABSTRACT FROM AUTHOR]

Nord Pool is the leading power market in Europe. It has been documented that the forward contracts traded in this market exhibit a significant forward premium, which could be a sign of market inefficiency. Efficient power markets are important, especially when there is a goal to increase the share of the power mix stemming from renewable energy sources. We therefore contribute to the understanding of this topic by examining how the forward premium in the Nord Pool market depend on several economic and physical conditions. We utilise two methods: ordinary least squares and quantile regression. The results show that the reservoir level and the basis (the difference between the forward and spot price) have a significant impact on the forward premium. The realised volatility of futures prices and the implied volatility of the stock market have strong effects on both the conditional lower and upper tails of the forward premium. We also find that, as the market has matured, the forward premium has decreased, indicating an increase in market efficiency. [ABSTRACT FROM AUTHOR]

We consider strategic gas/power producers and strategic gas/power consumers operating in both gas and power markets. We build a flexible multi-period complementarity model to characterize day-ahead equilibria in those markets. This model is an equilibrium program with equilibrium constraints that characterizes the market behavior of all market agents. Using a realistic case study, we analyze equilibria under perfect and oligopolistic competition. We also analyze equilibria under different levels of information disclosure regarding market outcomes. We study as well equilibria under different ownership schemes: no hybrid agent, some hybrid agents, and only hybrid agents. Finally, we derive policy recommendations for the regulators of both the gas and the power markets. [ABSTRACT FROM AUTHOR]

As one of the most important components of power grid, a distribution network is the most vulnerable part in the face of various uncertainties, and influences the stability and economy of a power system. In this paper, the operational information, hardware information and human factors were considered, and a state evaluation model of multi-source information fusion was established. Based on big data fuzzy iteration method and a weighted expert library, a weighted distribution of multi-source information was obtained, and an equipment condition assessment was carried out reasonably. Taking the distribution transformer as an example, the assessment showed that fusion of multi-source information presented in this paper is more comprehensive, and has the ability to reflect the state of equipment. The method proposed in this paper can accurately judge the running state of distribution equipment based on all kinds of information, and provides a reference for the follow-up power marketing for the status assessment of the user equipment. [ABSTRACT FROM AUTHOR]

The massive integration of distributed energy resources in power distribution systems in combination with the active network management that is implemented thanks to innovative information and communication technologies has created the smart distribution systems of the new era. This new environment introduces challenges for the optimal operation of the smart distribution network. Local energy markets at power distribution level are highly investigated in recent years. The aim of local energy markets is to optimize the objectives of market participants, e.g., to minimize the network operation cost for the distribution network operator, to maximize the profit of the private distributed energy resources, and to minimize the electricity cost for the consumers. Several models and methods have been suggested for the design and optimal operation of local energy markets. This paper introduces an overview of the state-of-the-art computational intelligence methods applied to the optimal operation of local energy markets, classifying and analyzing current and future research directions in this area. [ABSTRACT FROM AUTHOR]

Local electricity trading is a concept that allows active electricity trading between consumers, producers and/or prosumers located in a local low voltage distribution grid. The concept should provide added value to the participants and accelerate the democratization, decarbonization and decentralization of the power sector. The effects of local electricity trading on voltage levels in distribution grids are just in the early stage of research, together with the possible means of control, market design, market-clearing approaches and integration of the local electricity trading within the electricity markets. The aim of this work is to contribute to the research by examining if near real-time local electricity trading can be implemented in a distribution grid without time-consuming security-constrained unit commitment calculations for the observed time horizon and without security-constrained economic dispatch calculations for each trading period. Moreover, this work investigates if the implementation of local electricity trading can contribute to the avoidance of unpredictable and unfavorable consumption/production patterns, which can appear in the distribution grid due to the random behavior of a large number of participants. It is analyzed if a contribution to the maintenance of the voltages and currents within limits can be achieved that way. The method for simulation of a local electricity market and analysis of power flows and voltage levels is presented. The auction-based local electricity trading is simulated and applied on the modified IEEE European Low Voltage Test Feeder where the effects of local electricity trading on power flows and voltage levels are studied for boundary elasticities and prices of demand and supply offering curves. It is shown that the local electricity trading has potential to incentivize active participation of prosumers, which can lead to better demand/supply balancing at the local level and to a decrease of voltage fluctuations. [ABSTRACT FROM AUTHOR]

The intraday cross-border project (XBID) allows intraday market participants to trade based on a shared order book independent of countries or local energy exchanges. This theoretically leads to an efficient allocation of cross-border capacities and ensures maximum market liquidity across European intraday markets. If this postulation holds, the technical implementation of XBID might mark a regime switch in any intraday price series. We present a regression-based model for intraday markets with a particular focus on the German European Power Exchange (EPEX) intraday market and evaluate if the introduction of XBID influence prices, volume or volatility. We analyze partial volume-weighted average prices and standard deviations as well as cross-border volumes at different trading times. We are able to falsify our initial hypothesis assuming a measurable influence of changes caused by XBID. Thus, this paper contributes to the ongoing discussion on appropriate modeling of intraday markets and demonstrates that XBID does not necessarily need to be included in any model. [ABSTRACT FROM AUTHOR]

Because of the crucial implications of the market power of OPEC, the aim of this paper was to investigate the oil asymmetric market reactions, such as the price and risk reactions, to OPEC's announcements. Specifically, this paper first explored the oil price reactions to OPEC's announcements and their heterogeneity to depict the directional role of OPEC based on event study methodology. Furthermore, this paper analyzed the oil risk reactions in the framework of a linear model. Our findings reveal several key results. The oil price reactions to OPEC production decisions behave quite heterogeneously in three kinds of decisions. Specifically, the reaction to announcements of a production increase shows an invert "U" shape, whereas there is a linear effect of cut announcements. Otherwise, when a maintain decision is announced, the oil prices have no obvious change over the sample period. Additionally, the oil risk reactions to OPEC's announcements are heavily related to the interaction item between OPEC decisions and its production over full sample periods. Furthermore, OPEC's role in promoting stability in crude oil markets by changing its production shows a heterogeneous condition after global financial crisis. [ABSTRACT FROM AUTHOR]

The electricity spot market is now being implemented in China. Demand response, as a kind of flexible resource, is also being studied and explored for the constructed power market. Among the many demand response applications, the virtual power plant (VPP) as an aggregator of distributed energy resources (DERs), receives ever-increasing attention. However, the participation manner and related impacts of the VPP to the electricity spot market are still unknown within the current power market rules. Under this background, obeying the present trading rules of China's electricity spot market, a two-stage dispatching model with optimized bidding and operating strategy in the day-ahead (DA) and real-time (RT) market for the VPP is proposed. In the designed model, the conditional risk value (CVaR) is adopted to address the risk encountered by the uncertainty of the electricity spot market price. The impact of the user-side over-deviated revenue mechanism (UORM) of the China spot market on the income of the VPP in the DA and RT market is also analyzed. For a full evaluation, different coefficients for the influence of DA and RT risk, UORM, and energy storage system (ESS) are tested to investigate their respective impacts on the revenue of the VPP. The simulation cases prove that the proposed method is helpful for the VPP to optimize DERs' output in the electricity spot market according to its own risk preference. [ABSTRACT FROM AUTHOR]

Currently, the majority of world economies (even those located in the sunbelt (+/− 35 degrees of latitude with good sunshine with low seasonality) uses various types of fossil fuels as the main source of energy for their economies. However, this represents a very volatile and unsustainable strategy, since according to various estimates, the fossil fuel era will inevitably end as all carbon fuels are going to be spent in the next few centuries. Unlike traditional energy, renewable energy sources (RES) are not based on energy resources, but rather rely upon natural energy flows. With regard to its unique property, there has been an active construction of power plants of renewable energy and their gradual integration into national energy supply systems in recent decades. At the same time, the existing models of electricity markets were unprepared for their wide distribution. Hence, determination of the market value of energy generated by power plants using renewable energy sources becomes a particularly significant issue. This market value has to take into account the prevention of costs from the use of fossil fuels, as well as the resulting environmental benefits. Our paper proposes methods for solving this problem, contributing to the increase of economic efficiency of investment projects for the construction of renewable energy facilities and the formation of economic incentives for their propagation in energy supply systems. The proposed methods are based on the dynamic differentiation of tariffs for consumers with renewable energy sources depending on their structure of electricity consumption. Its effectiveness is demonstrated by calculating the cost of electricity for households located in the Krasnodar region using renewable energy sources. It is shown that this approach to the formation of tariffs for consumers allows the household to receive additional savings from the efficient use of energy installations on RES and energy storage devices in terms of alignment of the energy consumption schedule. This creates a significant incentive for households to use them and contributes to increasing the effectiveness of government renewable energy support programs, including by solving the acute problem of raising electricity tariffs from the grid. [ABSTRACT FROM AUTHOR]

One of the challenges in the transition towards a zero-emission power system in Europe will be to achieve an efficient and reliable operation with a high share of intermittent generation. The objective of this paper is to analyse the role that Demand Response (DR) potentially can play in a cost-efficient development until 2050. The benefits of DR consist of integrating renewable source generation and reducing peak load consumption, leading to a reduction in generation, transmission, and storage capacity investments. The capabilities of DR are implemented in the European Model for Power Investments with high shares of Renewable Energy (EMPIRE), which is an electricity sector model for long-term capacity and transmission expansion. The model uses a multi-horizon stochastic approach including operational uncertainty with hourly resolution and multiple investment periods in the long-term. DR is modelled through several classes of shiftable and curtailable loads in residential, commercial, and industrial sectors, including flexibility periods, operational costs, losses, and endogenous DR investments, for 31 European countries. Results of the case study shows that DR capacity partially substitutes flexible supply-side capacity from peak gas plants and battery storage, through enabling more solar PV generation. A European DR capacity at 91 GW in 2050 reduces the peak plant capacities by 11% and storage capacity by 86%. [ABSTRACT FROM AUTHOR]

The work presented in this article proposes an original method that models the medium-term market equilibrium under imperfect competition circumstances in multi-area electricity systems. It provides a system analysis considering multiple market splitting possibilities, where local market power may appear according to the status of the interconnections. As a result of new policies and regulations, power systems are increasingly integrating the existing electricity markets in unified frameworks. The integration of electricity markets poses highly challenging tasks due to the uncertainty that comes from the agents' strategic behaviors which depend on multiple factors, for instance, the state of the interconnections. When it comes to modeling these effects, the purpose is to identify each strategy by using conjectured-price responses that depend on the different states of the system. Consequently, the problem becomes highly combinatorial, which heightens its size as well as its complexity. Therefore, the purpose of this work's methodology is the reduction of the possible network configurations so as to ensure a computational tractability in the problem. In order to validate this methodology, it has been put to the test in a realistic and full-scale two-year operation planning model of the European electricity market that consists of a group of nine countries. [ABSTRACT FROM AUTHOR]