Market power assessment in electricity markets: supply function equilibrium-based model

We use experiments to study market power with supply function competition, akin to the competition in electricity markets. Our treatments vary the distribution of demand levels as well as the amount and symmetry of the allocation of production capacity between different suppliers. We relate our results to a descriptive power index and to the predictions of two models: a supply function equilibrium (SFE) model and a multi-unit auction (MUA) model. Observed behaviour is consistent with the equilibria of the unrestricted SFE model and inconsistent with the unique equilibria of two refinements of the SFE model and of the MUA model.

This paper describes a new method for analyzing the bidding strategies of generating companies (GENCOs) in the independent system operator (ISO) point of view. ISO uses these results to detect the participants that have the potential for market power or actual exercise of market power. ISO models all GENCOs with perfect information. The proposed methodology uses the marginal cost of GENCOs as an initial point for bidding strategies of GENCOs and improves bidding strategies based on the objective function of GENCOs, the state of them in each hour of the day and with regard to ISO's market clearing problem. ISO tries to maximize the social welfare or minimize consumer's payments. The model presented in this paper simulates the energy market and the behavior of participants to obtain Nash equilibrium point of their bidding strategies for detecting the participants that have the potential for market power or actual exercise of market power. GAMS (general algebraic modeling system) language has been used to solve the profit maximization and social welfare maximization modules of this model using DICOPT optimization software with mixed integer non-linear programming.

Market power assessment is an important aspect of electric market analysis and operation. Market power problems are more complicated in an electric market than those in other markets due to the specific properties of electricity. A comprehensive and dynamic market power assessment has been proposed in this paper to protect and improve the open electricity market. This paper proposes a multi output fuzzy neural network (FNN) for market power assessment and for finding the on line market power ranking status of GENCOS in a competitive power system using a fuzzy composite market index (FCMI). This index is formulated by combining (i) Lerner Index, (ii) Relative market power and (iii) Nodal Cost. In the proposed FNN a trained multioutput neural network is being used as a fuzzy inference engine. The input of FNN consists of real loads and a bipolar code to represent a trading interval while the output consists of the fuzzy values of FCMI. To train the FNN a number of training patterns, covering the full operating range of the power system, are generated using the system data such as offer prices and operating constraints. OPF results are used to compute the above three market power indices and the corresponding FCMI. Once the network is trained it is capable of predicting the FCMI values in five fuzzy classes (GENCO ranking) for any given operating scenario, on line, instantaneously, without bothering about the computational burden of OPF. The computational effort is required only for training the network which is an off line process. Since the training of ANN is extremely fast and test results are accurate, they can be directly floated to OASIS (open access same time information system) and any other web site. An Independent system operator(ISO) and customers can access this information instantly. The performance of the proposed method has been tested on an IEEE 14 bus system.

In this paper, a novel conjectured supply function equilibrium (CSFE) based model is presented for simulating strategic interactions among generation companies (GenCos) in an electricity market under incomplete information. The model is derived theoretically from the well-acknowledged supply function equilibrium theory, and a general supply function for a GenCo is obtained based on its conjectural variation of the rivals' accumulated response to a change in the market price. The CSFE is a general and flexible model for simulating strategic behaviors of GenCos in an electricity market with inelastic demand. Supply functions will be linear when GenCos hold constant conjectures, and a unique equilibrium exists when linear supply functions are provided to the market. Finally, the IEEE 30-bus system is used to show the essential features of the proposed model.

The impacts of different bidding segment numbers on bidding strategies of generation companies

IntroductionThe monitoring of the electricity market and preventing incorrect usage behavior are well-known issues in the competitive electricity market (see for example Marulanda et al., 2006; Nagypal et al., 2015; Strielkowski and Lisin, 2016; Nagaj, 2016) that are well-embedded into the strategy of sustainable energy development (Streimikiene et al., 2016). The monitoring of the electricity market plays a key role in the free electric energy market (Kasperowicz, 2011; Lisin et al., 2016). Supervisory actions are important for the System Operator and the Regulatory Commissions in order to ensure the efficient market performance. For Federal Energy Regulatory Commission in USA (Haymes, 2000), the market monitoring has been identified as a standard market design component and a basic function in the deregulated electricity market. According to Rahimi et al. (2003) and London Economics et al. (2007), the electricity market monitoring could be organized as an internal system or an institution in the Independent System Operators (ISO) structures, as well as could function also outside of the ISO structures and can provide service for ISO or other recipients (Goldman and Lesieutre, 2004).Furthermore, the availability of a well-developed monitoring system would also help agents to optimize their bidding strategies (David and Wen, 2000; Dun-nan et al., 2006; Pires Manso et al., 2015). Currently agents are concentrating on increasing their efficiency in order to maximize profits through a complicated system of product and sales management. Due to the fact that the process of decision making is very complex, whereas complete information is often unavailable, the electricity market monitoring appears to be difficult (London Economics, 2007). Therefore, if the market monitoring system functions properly, the transparency and reliability of the information concerning the electricity market dynamics may be ensured.The main activities of market monitoring as described in Rahimi et al. (2003), London Economics et al. (2007), (Dehdashti, 2005) and (Guler et al., 2005) include: 1) Detection of attempts to exercise market power and fraudulent behavioral, 2) Monitoring of market performance, 3) Identification of market design imperfection, 4) Transmission and generation blackout controlling, 5) Market participants' behavioral monitoring (activities and transactions).After an in-depth analysis of the existing literature devoted to exploring the issue of electricity market monitoring, it is possible to state that the information regarding the general methods of monitoring are available. However, there is a deficit of information related to the monitoring techniques focused on economical parameters of Spanish electricity market. Furthermore, the conducted analyses of the market structure and of the available source data related to Spanish power system have proven that that there is a need for a modification or a creation of new methods and indices, which shall be applied in order to correctly monitor the economical parameters of Spanish electricity market.This paper firstly introduces the concept and functions of the electricity market monitoring system (section I). Subsequently, the main methods and indices applied to the monitoring (market power, market performance and behavioral monitoring) are outlined (section II). Section III outlines the particularities of Spanish market. Subsequently, section IV presents conclusions.1. The global overview of the monitoring systemThe result of the extensive analysis of the existing literature on market monitoring is represented graphically in Figure 1.The Figure 1 presents the market monitoring framework: the elements and the correlation between them. This extensive analysis is based inter alia on the following sources: London Economics et al. (2007), Goldman and Lesieutre (2004), Dun-nan et al. (2006), Chakrabarti et al. (2008), Newbery (2004), Asgari et al. …

We present an empirical analysis of a supply function equilibrium model in the Texas spot electricity market. We derive conditions for optimal bidding behavior in a spot market with ex ante bilaterally contracted sales. By estimating costs, we are able to derive a set of ex post-and ex ante-optimal supply functions and use a non-parametric behavioral model to compare our theoretically optimal supply functions to actual offers made. Our results show that with the exception of the largest generators, firms make offers with markups and markdowns far in excess of what a model of profit-maximizing behavior suggests.

As independent economic entity, each power generation company in China participates in current electric power market competition by price bidding. Multi-population replicator dynamics of evolutionary game theory is applied to model and simulate power generation companiespsila discriminatory and bounded rationality bidding strategies according to different generating set status in a power market. The spontaneous forming process of the generation companiespsila bidding strategies and evolutionarily stable strategies are both analyzed. A practical case is set to verify the modelpsilas ability and reliability. The results not only demonstrate the multi-population replicator dynamics model can describe the dynamic process of generation companiespsila bidding quite well, but also suggest reasonable price competition rules must be constituted so as to ensure and promote the healthy development of the generation-side power market.

Many vertically integrated power companies have been restructured worldwide during the last three decades for improving the competitiveness and efficiency of energy industry. However, a perfectly competitive power market does not exist in real world, and most of the present electricity markets can be considered as oligopoly electricity markets. Some generation companies (GenCos), in these imperfect competition situations, possess market power to obtain more profits at the cost of other market players. Strategies of market power can be categorized as capacity withholding and financial withholding. When either strategy is successful, higher profits of GenCos and lower market performance are expected.

[Introduction] As the guarantee for the stable of the power system, the marketization of the regulation auxiliary service has been put on the agenda. The energy-regulation joint optimization becomes a mode of market organization. This paper aims to study the combined optimization model of the electric energy-regulation market considering the performance difference of frequency modulation resources in the PJM market background. [Method] Regulation auxiliary service pricing adjustment model and the joint clearing model of electric energy and regulation market considering the difference of fast and slow regulation resources and regulation performance was proposed in this paper, which were applied to the simulation of a real power grid to compared with domestic electric energy - regulation step clearing market. Two typical scenarios were set up in wet season and dry season. The clearing of regulation resources, the influence on the electricity purchase cost in the spot market and the active degree of regulation market were studied in detail. [Result] In the stepwise clearing mode, the rapid regulation resource has obvious advantages and causes the increase of electricity purchase cost in the electricity market. In the electricity-regulation joint optimization model, the clearing results of fast and slow regulation resources are affected by the pricing adjustment strategy and the increase rate of electricity purchase costs in the power market is smaller than that in the stepwise model, and the clearing price and fluctuation degree in the regulation market are higher than that in the stepwise clearing mode model. [Conclusion] The combined optimization mode of electric-regulation modulation with reasonable price adjustment strategy is helpful to realize reasonable competition among units with different regulation performance and stimulate market vitality.

In the future, the large-scale participation of renewable energy in electricity market bidding is an inevitable trend. In order to describe the Nash equilibrium effect and market power between renewable energy and traditional power generators in the tacit competition in the electricity market, a bidding strategy based on deep reinforcement learning is proposed. The strategy is divided into two layers; the inner layer is the electricity market clearing model, and the outer layer is the deep reinforcement learning optimization algorithm. Taking the equilibrium supply function as the clearing model of the electricity market, considering the green certificate trading mechanism and the carbon emission mechanism, and taking the maximization of social welfare as the objective function, the optimal bidding on the best electricity price is solved. Finally, the calculation examples of the 3-node system and the 30-node system show that compared with other algorithms, more stable convergence results can be obtained, the Nash equilibrium in game theory can be reached, social welfare can be maximized, renewable energy has more market power in the market. The market efficiency evaluation index is introduced to analyze the market efficiency of the two case systems. The final result is one of great significance and value to the reasonable electricity price declaration, the optimization of market resources, and the policy orientation of the electricity market with renewable energy.

In January 2017, The Government of Yunnan Province issued the implementation plan of electricity market reform for retail side. The electricity retail market has officially entered the stage of power market in Yunnan Province. The construction of power retail market is conducive to improving the activity of power market, cultivating the market awareness of power users, promoting power users to improve demand side management ability, and ensuring the safe, economic and efficient operation of power system. According to the official website of Kunming Power Exchange Center Company Limited, at present, there are 146 registered power sales companies and 33062 registered power users in Yunnan Province. The power market transactions are active, the transacted electricity quantity is increasing year by year, and the power retail market is booming. The retail package of electricity is the basis of mutual benefit and win-win between the electricity selling company and the retail users. The flexible, reasonable and effective electric retail package reflects the healthy and efficient operation of the electric retail market to a certain extent. Therefore, the research and development of electric power retail package is a very meaningful topic, which is worthy of in-depth study and practice.Firstly, based on the operation of Yunnan electric power wholesale market and electric power retail market, combined with the business practice of Yunnan electric power retail settlement payment, this paper points out the constraint boundary of the design of electric power retail package in electricity market of Yunnan province, such as the coupling constraints between electric power wholesale transaction and retail transaction, the coupling constraints between electric power wholesale settlement and retail settlement, etc. Then, combined with the characteristics of electricity load, electricity price bearing capacity, demand response and other characteristics, this paper makes a user portrait of Yunnan users, classifies and summarizes the power transaction demand of retail users, and designs the corresponding electric power retail package, such as free service, conditional service fee, price difference income, energy management and other electric power packages, which are full through the appropriate electric power retail package. It can meet the demand of electricity retail users and form a win-win situation. Secondly, this paper introduces the operation mode of all kinds of retail packages in Electricity Market of Yunnan province in detail. On the one hand, it is the business process of transaction and settlement, including the wholesale, retail transaction and settlement business process of power selling company, the transaction and settlement business process of power users, the transaction and settlement business organization flow of power exchange center et al. On the other hand, it is the cash flow and invoice flow of settlement and payment, including the cash flow and invoice flow of retail electricity payment of power users. Finally, through the practical analysis of the operation of power retail market in Yunnan province, it points out the advantages and disadvantages of various packages. Further combining with the construction and development plan of electricity market in Yunnan province, especially the operation of electric power spot market, some changes for the design of power retail package are proposed.

With the continuous promotion of the unified electricity spot market in the southern region, the formation mechanism of spot market price and its forecast will become one of the core elements for the healthy development of the market. Effective spot market price prediction, on one hand, can respond to the spot power market supply and demand relationship; on the other hand, market players can develop reasonable trading strategies based on the results of the power market price prediction. The methods adopted in this paper include: Analyzing the principle and mechanism of spot market price formation. Identifying relevant factors for electricity price prediction in the spot market. Utilizing a clustering model and Spearman’s correlation to classify diverse information on electricity prices and extracting data that aligns with the demand for electricity price prediction. Leveraging complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to disassemble the electricity price curve, forming a multilevel electricity price sequence. Using an XGT model to match information across different levels of the electricity price sequence. Employing the ocean trapping algorithm-optimized Bidirectional Long Short-Term Memory (MPA-CNN-BiLSTM) to forecast spot market electricity prices. Through a comparative analysis of different models, this study validates the effectiveness of the proposed MPA-CNN-BiLSTM model. The model provides valuable insights for market players, aiding in the formulation of reasonable strategies based on the market's supply and demand dynamics. The findings underscore the importance of accurate spot market price prediction in navigating the complexities of the electricity market. This research contributes to the discourse on intelligent forecasting models in electricity markets, supporting the sustainable development of the unified spot market in the southern region.

In power systems, transmission network provides the infrastructure to support a competitive electricity market, but congestion occurs frequently in weakly connected networks. The definitions of the market power are presented from the views of economics and regulation. Bidding strategies, such as withholding capacity and bidding at higher price, are analyzed and the impacts of transmission congestion on the locational marginal price (LMP) are illustrated in detail. Congestion will cause relative scarcity of generating capacities in the congested areas, so generation companies in these areas have locational market power. Impacts of transmission congestion on market power are evaluated by an 8-bus system. The results indicate that transmission congestion can enhance the locational market power in the congested areas and weaken the efficiency of electricity market. So this study can provide a theoretical basis for stipulating market operation rules and supervising behaviors of market participants.

Bidding strategy of energy storage in imperfectly competitive flexible ramping market via system dynamics method