Electric Power Market Research Articles

Research on time-of-use compensation pricing strategies for load aggregators based on user demand response

As the electric power market reform deepens, the strategic role of load aggregators in demand-side response becomes increasingly important. The inherent variability of distributed renewable energy generation and user demand response often leads to a mismatch between the purchased electricity and the market bid volume, resulting in punitive costs for companies. To address this issue, this study treats demand-side controllable loads as dispatchable resources and proposes a tiered pricing strategy to adjust power distribution. By establishing a Stackelberg leader-follower game model, the study promotes a mutually beneficial relationship between load aggregators and controllable load users. Through case studies, this paper examines the operational profits of load aggregators and the power adjustment behaviors of controllable load users under tiered and fixed compensation pricing schemes. The results indicate that tiered compensation pricing significantly reduces punitive costs and enhances user participation in demand response.

Energy sales activities development in electric power market

The energy sales activities development processes in the electric power industry have been studied. The factors determining the infrastructural nature of activity in the modern market, aimed at supporting opportunities for implementing competitive transactions of electric power purchase and sale, have been formulated. The process of planning to implement in 2005–2008 a “resale” scheme for organizing energy sales activities in the course of developing a new market model has been assessed. The choice of such a scheme is not simple and not the best of possible solutions. The problems arising for economic entities in the modern Russian electric power market under the conditions of the “resale” scheme for organizing energy sales activities have been characterized. Mechanisms and procedures of the market do not provide its subjects with acceptable competition conditions. This is largely due to the fact that energy sales companies, seeking to preserve and expand the monopoly sale of electricity, suppress the possibility of competitive choice of its suppliers and consumers, creating conditions of entrepreneurship low efficiency in the market. The article proposes approaches to improving energy sales activities based on the implementing the “agency” scheme within the framework of the electric power market digital model with the solution of tasks to provide its subjects with opportunities for competitive choice, ensuring fair competition conditions for detecting and implementing opportunities to obtain entrepreneurial benefits.

Development prospects for the common electric power market of the Eurasian Economic Union

Subject. The article considers the process of integration of member States of the Eurasian Economic Union in the field of electric power. Objectives. The focus is on the analysis of the organizational and economic mechanism of the functioning of the common electric power market of the Eurasian Economic Union, taking into account the adopted regulatory legal acts. Methods. The study draws on general scientific research methods. Results. The paper determines foundations of the functioning, condition and development prospects for the common electric power market of the Eurasian Economic Union. It establishes that the possibility for participants from different countries to obtain access to the purchase (sale) of electricity within the framework of the Eurasian Economic Union contributes to increased competition, and the variety of methods of electricity trade enables to ensure transparency of pricing in interstate supplies. Conclusions. The functioning of the common electricity market of the Eurasian Economic Union, which complements the domestic markets of Russia, Belarus, Armenia, Kazakhstan, and Kyrgyzstan, will be regulated by supranational rules for electricity trade, taking into account the specifics of the economic development of each country.

Scientific support of competition development processes in power market

The article studies the issues of competition development processes scientific support in the Russian power market. Based on the study results and the Russian electric power market current model experience evaluation, conclusions have been drawn about the need for additional research into the competition development in the market with the subsequent development and a new set of scientifically sound measures implementation to create acceptable conditions for competition of its subjects. The market properties in many respects diverge from the properties of markets with developed competition. The market has not yet managed to create any acceptable competition conditions, forming systemic conditions for a noticeable increase in the entrepreneurship efficiency. It is characterized by the presence of serious systemic problems that have a significant negative impact on its subjects functioning efficiency and require solutions. The article analyzes the directions and areas of insufficient scientific study on the issues of market interaction between consumers and electric power producers as important reasons for the the modern Russian power market problems persistence. The paper characterizes the complex of research and design developments for a new package of interrelated science-based measures implementation for competition conditions development in the power market, aimed at bringing its properties closer to the properties of markets with developed competition.

Regulatory control over the electricity market in Ukraine: the problem of duplication of powers

The purpose of this article is to substantiate the existence of the problem of duplication of powers in the system of regulatory control over the electricity market in Ukraine and to determine ways to solve it. This research task should be carried out using, first of all, the formal-dogmatic method within the framework of a critical assessment of the relevant legislative provisions, perceiving them being detached from the environment of their application, as well as relying on the method of legal and institutional modeling to outline the organizational and legal contours of the system of regulatory control over the electricity market in Ukraine. Results: the subject matter of regulatory control (supervision) over the electric power industry carried out by the State Energy Supervision Inspectorate of Ukraine covers the production, transmission, distribution of electric energy, energy storage, as well as the use of energy for their own needs by market participants in part of technical operation of power plants and networks, energy equipment, testing and repair of power plants and networks, performance of works on the design of power plants and networks, while the National Energy and Public Utilities Regulatory Commission carries out regulatory control over compliance by economic entities carrying out activities in the fields of energy with legislation in this area as well as with the licensing conditions by conducting scheduled and unscheduled on-site, as well as off-site inspections in accordance with the control procedures approved by this commission. Conclusions: the optimal institutional reform designed to ensure the exclusivity and indivisibility of powers regarding regulatory supervision (control) over the electric power market appears to be the concentration of these powers in the field of competence of the National Energy and Public Utilities Regulatory Commission as an independent market regulator with a complete and self-sufficient complex of control and supervision measures, which can be enriched with the prepared proposals on reforming the procedures of activity of the State Energy Supervision Inspectorate of Ukraine.

A game theory-based pricing model for ancillary services in electricity markets

Abstract Amidst the ongoing evolution and substantial reforms within the electric power market, the development of an auxiliary service pricing model grounded in game theory emerges as crucial. This study delineates the construction of an electricity auxiliary service pricing model, utilizing a dual mechanism approach: a cooperative game-based electricity price formation mechanism and a Stackelberg game-based time-sharing pricing mechanism. Furthermore, it incorporates demand response technology to conduct a detailed analysis of optimization results and the applicability of the proposed electricity service pricing model. The pricing scheme designated as Scheme 4, derived from the proposed model, demonstrates notable superiority in terms of economic efficiency and environmental sustainability when juxtaposed with three alternative schemes. Specifically, Scheme 4 yields a net profit of $13,267.6, achieves clean energy utilization amounting to 89.67 MWh, and minimizes wind abandonment to 17.35 MWh, outperforming all other considered scenarios in these metrics. Operational analysis reveals that the model's execution time varies between 15 and 50 seconds across different sample sizes, exhibiting minimal fluctuations. Additionally, the Monte Carlo simulations consistently produce values inferior to the objective function value of the developed model, with the discrepancy narrowing from 38 to 20, indicating the model's robust adaptability.

Research on Image Analysis and Dynamic Early Warning Mechanism of Power Marketing Operation Site Based on SSD Networks

Abstract Safety production is an important way to ensure the personal safety of workers and the safety of national property. This project focuses on addressing the safety generation problem in the power marketing profession, designing a set of intelligent dynamic warning systems for power marketing operations. MobileNetV1 is used as the backbone feature extraction network of SSD to create a lightweight target detection network, and it is combined with OpenVINO and NCS2 neural computation bars to construct an image analysis and dynamic warning model for power operation based on the SSD MobileNetV1 algorithm. We use the images of power marketing operation sites in a city as a dataset to test and compare the constructed model with other target detection algorithms, analyzing its dynamic warning effect on power operations and exploring the effectiveness of the model’s practical application. The results show that the SSD network model can significantly improve the detection efficiency and accuracy of the dynamic early warning system for electric power operations, and its accuracy is 15.15% and 18.82% higher than that of the Faster⁃RCNN algorithm and the YOLO algorithm, respectively. The early warning system reduced the irregular behavior of electric power marketing operations by 135.71%, demonstrating the effectiveness of the SSD model in detecting and warning electric power targets. This model not only meets practical requirements but also effectively reduces the irregular production behaviors of electric power marketing operations, thereby enhancing the safety coefficient of marketing field operations.

RPA-supported digital workforce in the field of statistical work in the electricity market

Abstract How to count a large amount of data and information more efficiently in electric power statistics has become the main problem that electric power enterprises should pay attention to. For this reason, this paper proposes a study on the application of digital employees using RPA technology in the statistical analysis of the electric power market. Optimizing power market statistics is achieved by using the improved particle swarm algorithm SN-PSO, which is based on the fitness function and particle coding strategy to address the unbalanced load phenomenon. In AI-related technology, we create digital employees and conduct case studies on electricity market statistics by combining RPA technology with image recognition technology, NLP, and knowledge graph technology. The results show that the customers of the power supply company that show negative growth in electricity are mainly concentrated in the manufacturing industry (average value of 21.44) and the mining industry (average value of 7.36). In contrast, from the perspective of regional distribution, the negative growth rate of the customers in the large customers is mainly concentrated in the region of E and the remaining region of the large customers, which indicates that these two regions need to strengthen tracking management. This study improves the statistical work mode of electrical enterprises in the information age so that electric power enterprises and China’s market economy can develop better.

Research on the Construction of Electricity Market Operation Efficiency Assessment Model and Indicator Early Warning Based on Cloud Entropy Optimization Algorithm

Abstract In this paper, we first constructed the indexes for evaluating the operational efficiency of the electric power market, and screened the indexes by using the Delphi method. Then, the basic numerical characteristics of the cloud model are explored, and the hierarchical boundaries of the power market operational efficiency assessment indexes are delineated. The market operational efficiency assessment model is established by using the cloud entropy optimization algorithm, and the objective weights are determined by the entropy weighting method. The market operation efficiency assessment model is used to analyze the operation efficiency of the power market, and targeted suggestions are made to address existing problems. Finally, the risk warning threshold of the operation efficiency of the power market is set. The risk warning of the operation efficiency of the power market is analyzed. The predicted values and expected output values are compared to validate the applicability of the model in this application. The average value of the operation efficiency of the power market is 3.3, the level of efficiency is between 2 and 3, and the power market operation efficiency is in the range of 2-3. The range is 2-3, and the grade of power market operational effectiveness is medium. This study helps improve the operational efficiency of the power industry and optimize the allocation of market resources in the power industry.

Credit ability evaluation system of power selling enterprises based on big data

With the gradual relaxation of the electricity market access threshold, the development pattern of market-oriented electricity sales has brought great challenges to the power grid business development. It is of great significance to select the right electricity selling enterprises in the market-oriented electric power marketing mode to ensure the practical demand of electricity customers and the operating efficiency of power grid enterprises. First, the basic characteristics of power big data are analyzed. Secondly, it classifies and analyzes the important factors that affect the performance credit of electricity selling enterprises under the new electricity transformation environment. By normalizing different types of key index data and assigning index weights, a credit ability evaluation model of electricity selling enterprises based on matter-element extension-TOPSIS is established. Finally, taking eight electricity selling enterprises in a province as an example, the credit ability evaluation model is applied to analyze and calculate the performance ability of different electricity selling enterprises. The results prove the practicability of the evaluation system proposed in this paper.

An Investigation of Stability Criteria for Sampled-data Control System Using New Integral Inequality for Application to Electric Power Market

An Investigation of Stability Criteria for Sampled-data Control System Using New Integral Inequality for Application to Electric Power Market

Optimal power dispatch capability and reliability analysis of hybrid renewable energy system

These days, using solar and wind energy resources is much more cost-effective and appealing. The rapid depletion and growing expense of non-renewable energy supplies resulted in the development of alternative energy sources that utilize renewable energy sources. In recent times, hybrid renewable energy algorithms have often been connected to wind and solar power systems. The primary objective of this work (PWBHPS) is to determine the power dispatch capacity of a PV-wind-battery hybrid power system. In the modern electric power market, the PWBHPS's power dispatch capacity needs to be explicitly specified at the beginning of every dispatching time interval in order to collaborate with the transmission system operator (TSO). Energy storage is a workable option for efficiently integrating renewable energy sources into the system. A recently developed storage device called the vanadium redox flow battery (VRFB) may have certain advantages in large-scale grid-connected applications. State-of-charge monitoring provides extra insights into battery performance by displaying increased capacity utilization and longer cycle times, both of which extend the life of the cells. This study looks at the minimum-max technique of individual solar energy, wind energy, and a combined PV wind battery hybrid power system to size a VRB battery for application in renewable energy systems. Individual wind and solar systems need larger battery capacities for consistent, constant power output; hybrid systems require batteries with lower ratings. An optimal charging mechanism is proposed and explored through MATLAB simulations.

Simulating Generalised Locational Marginal Pricing for Power Markets in East Africa

There is an enormous opportunity for adopting a wholesale electricity market under locational marginal pricing. Besides ensuring competition and accounting for network congestion, the price signal reflects a space-time electricity economy. This paper examines the prospects of introducing a single East African electricity market in five selected partner states. It reports on a pioneering effort to simulate the coupling of power markets, estimate locational marginal prices, and determine the economic benefits of cross-border power trade and competition across these five countries. The nodes representing the primary power systems in these five countries are simulated in an optimal power flow model using optimisation software GAMS. The total welfare of electric power market integration is estimated at $ 4.8 million/hr, representing a welfare gain of $ 2.6 million/hr, thus, net total welfare increases by 118%. The simulation also investigates the implications for locational prices and power flows under constrained and unconstrained scenarios. To secure the benefits of an integrated electricity market, it is vital to pursue significant institutional restructuring, a robust transmission infrastructure, and the harmonisation of energy policies.

Strategic risks of reforming the energy market of Ukraine in the context of the energy security

Monopoly structures and complete control over pricing deform the electric energy environment. An example of the European model of reforming the electricity market, which is based on transparency and consumer accessibility to electricity services, is shown. On this basis, the goals, and vectors of reforming the regional markets of electric energy services have been determined. It is foreseen that the reform process should be carried out on a combination of organizational, economic, technical, social, and other goals. The advantages and disadvantages of reforming the electric power market of the region and the country were identified using the author's SWOT analysis method. The proposed closed cycle of reforming the electricity market covers an interchangeable combination of the following components: regional electricity networks, market environment, information environment, financial and credit support, integration, labor resources, and communication links. Vectors of further reform are outlined. Competitiveness presupposes the free choice of a supplier by consumers in the absence of barriers to the supply and sales market. The new European format of the electricity market model creates new challenges and threats to the operation of electricity market enterprises, which relate to transparent and objective conditions of access to consumption and operation of electricity networks, impartial accelerated development of the electricity market to the requirements of the dynamism of the economic system. Reforming the electricity market combines the processes of achieving organizational, economic, technical, social, and environmental goals. However, this combination causes various consequences and risks associated with profit maximization. One of the most critical problems of the multi-system operator's functioning is ensuring its independence and mutual respect for all market participants. For this, the following measures are legally justified: procurement of related services on a competitive basis; transparent information about the available list of related services, their volumes, costs, terms, and requirements for suppliers; formation of accounting of the expense and income component when implementing the centralization of dispatching management from other types of activity; formation of access to the capacity of interstate electrical networks by conducting electronic auctions; submission of the UES development plan to the CMU of Ukraine for consideration, even in the case of inconsistency between the interested authorities; the investment component of the region will grow only under the conditions of reforming the electricity market. However, the processes of introducing a new model of the electric power services market are being formed under tight deadlines, the introduction and adoption of legislative acts, the implementation of organizational and structural transformations, and software approvals; despite everything, the processes of reforming the electric energy services market are an integral attribute of the region's integral investment policy. Keywords: energy market, energy security system of Ukraine, energy system, energy risks, strategic risks.

Application of Data Mining Algorithms in Power Marketing Predictive Analytics

Abstract The electric power industry has accumulated a large amount of historical data, and the analysis based on data mining can provide an effective reference for the electric power marketing of enterprises. In this paper, according to the analysis architecture of electric power marketing and its functional modules, the electric power marketing analysis system based on Bayesian algorithm is constructed through data extraction and transformation, modeling of Bayesian network, and simulation operation. At the same time, for the shortcomings of Bayesian algorithm with the large error of classification results under the condition of strong sample correlation, mutual information is introduced to modify the number of Laplace smoothing. The MI-NB model predicts the probability of electricity risk for company A to be 60% and the probability of electricity risk for company B to be 40%, with an error rate of 9.65% and 8.37%, respectively. In line loss rate analysis, the MI-NB model predicts an average line loss rate of 60.46% for station 1 and 60.43% for station 2, both in the high line loss rate range. The Bayesian algorithm based on mutual information can improve the practicality and intelligence of the power marketing decision analysis system, which makes the decision management of power supply enterprises more scientific and reasonable, and is of great practical significance in reducing the operational risk of enterprises.

Daily rolling estimation of carbon emission cost of coal-fired units considering long-cycle interactive operation simulation of carbon-electricity market

The high overlap of participants in the carbon emissions trading and electricity markets couples the operations of the two markets. The carbon emission cost (CEC) of coal-fired units becomes part of the power generation cost through market coupling. The accuracy of CEC calculation affects the clearing capacity of coal-fired units in the electric power market. Study of carbon–electricity market interaction and CEC calculations is still in its initial stages. This study analyzes the impact of carbon emissions trading and compliance on the operation of the electric power market and defines the cost transmission mode between the carbon emissions trading and electric power markets. A long-period interactive operation simulation mechanism for the carbon–electricity market is established, and operation and trading models of the carbon emissions trading market and electric power market are established. A daily rolling estimation method for the CEC of coal- fired units is proposed, along with the CEC per unit electric quantity of the coal-fired units. The feasibility and effectiveness of the proposed method are verified through an example simulation, and the factors influencing the CEC are analyzed.

Evaluation on power marketing decision evaluation based on Bayesian network

Abstract The daily production and life of human beings are inseparable from electricity. As the power supplier, electric power enterprises provide power demand for the majority of users. In the new era, electric power enterprises are also facing market-oriented reform. The focus of reform is electric power marketing. The formulation of electric power marketing strategy needs scientific decision-making analysis as guidance. With the increase of power demand, the scale of power grid is also expanding continuously. With the introduction of new energy equipment, the power system is becoming more and more complex, and it is difficult for relevant staff to effectively monitor and analyze the system. Combined with the above situation, this paper combined Bayesian network to build a power marketing decision analysis system, and combined Bayesian algorithm to test the power marketing real-time cost control system. The experimental results showed that the average judgment accuracy was 91.90 %, and the average warning time was 0.39 s. From the above data, it can be seen that this algorithm can play a good optimization effect on the performance of the system. In this paper, the elasticity test of the power system was also carried out from the aspect of wind speed, and the results showed that the maximum elasticity value can reach 0.94. It can be seen that the elasticity effect of the power system is good as a whole under different wind speeds.

A joint clearing market for coupled electricity and gas system considering bilateral energy contracts

In recent years, with the progress of new energy conversion technology, especially an increasing number of gas turbine units applied to the market, the connection between the natural gas system and the electric system has become increasingly close. Initially the gas and electricity markets operated relatively independently. Therefore, it is necessary to establish the coupling architecture of natural gas market and electricity market to meet the energy demand of users. This paper attempts to propose a power and gas coupling system based on clearing market structure. Firstly, the difference between natural gas–electricity coupling market and joint settlement market is discussed. The combined market considered in this paper is somewhat different from the associated electricity market and natural gas market. The calculations are easier and the results more reliable than those of the traditional linked gas markets and electric power market. Then, a mathematical model of joint clearing market is established based on bilateral energy contracts. Then, the piecewise linearization approximation (PLA) algorithm is proposed to solve the nonlinear problem. The locational piecewise price (LMEP) and locational marginal gas price (LMGP) are identified respectively, and the bilateral contracts are processed. The solution proposed in this paper guarantees strong duality and clear meaning of dual variables, making PLA easy to apply and solve market clearing problems based on dual variables or Lagrange multiplier pricing, as well as easy to deal with bilateral contract problems. Finally, the proposed joint clearing market is verified by an improved 3-electric bus and 6-gas node system.

CONTRATAÇÃO DE ENERGIA ELÉTRICA NO MERCADO LIVRE

Brazil, during the 90's, underwent important changes in the Brazilian Electric Sector (SEB). During the administration of President Fernando Henrique Cardoso was created the Project of Restructuring of the SEB (RE-SEB), what introduced the concept of competition and free market of electric power. This concept moved the energy market of Brazil and companies had to reinvent themselves to conform to this type of contracting in order to reduce their costs. Thus, this work has a purpose to support the decision to purchase energy for Free Consumer, which aims to invest in energy contracts to minimize costs.

A Study of Integrated Model for Electricity Supply Chain Considering Renewable Energy Fraction and Demand Variation

This paper aims to derive integrated model for electricity supply chain considering renewable energy fraction and demand variation. Currently, attention is being paid to increasing the ratio of renewable energy generation in the electric power market which called Green Energy Coefficient (GEC). This paper aims to derive an integrated model of electricity supply chain considering renewable energy fraction and demand variation using multi-agent reinforcement learning. The subjects of the models are the consumption market model, the electricity market model, and the production market model. Also, the pricing process in electricity supply chain is analyzed using the proposed multi-agent simulations.