Market Power Mitigation Research Articles

Redesigning automated market power mitigation in electricity markets

Electricity markets are prone to the abuse of market power. Several U.S. markets employ algorithms to monitor and mitigate market power abuse in real-time. The performance of automated mitigation procedures is contingent on precise estimates of firms' marginal production costs. Currently, marginal cost is inferred from the past offers of a plant. We present new estimation approaches and compare them to the currently applied benchmark method. We test the performance of all approaches on auction data from the Iberian power market. The results show that our novel approaches outperform the benchmark approach significantly, reducing the mean (median) absolute estimation error from 11.53 (6.08) €/MWh in the benchmark to 4.03 (2.64) €/MWh for our preferred approach. This approach also performs best in our subsequent simulation of mitigation procedures. Here we find large welfare transfers from supplier to buyer surplus as well as a robust overall welfare gain, stemming from both productive and allocative efficiency gains. Our research contributes to accurate monitoring of market power and improved automated mitigation. Although we focus on power markets, our findings are applicable to monitoring of renewable energy tenders or market power surveillance in rail and air traffic.

Market power detection and mitigation measures for the spot electricity market based on bidding equilibrium

The spot electricity market (SEM) faces the challenge of inefficiency problems from market power (MP) abuse. However, previous studies have not adequately addressed such issues as the feasibility of MP mitigation measurements and authenticity of MP detection indicators. In this study, mitigation methods are developed, and MP detection indicators are designed to detect and mitigate the exercise of MP in an SEM in which multiple generators compete unilaterally through a uniform marginal clearing price mechanism. First, the incentives and general rules for rational generators to exercise their MP are analysed, providing theoretical support for the developed approaches. Then, two mechanisms that can mitigate the exercise of MP are devised by limiting the bid increase rate and maximising the consumer surplus. Furthermore, a behavioural detection indicator is designed to measure the MP of an individual generator, while an overall indicator is defined to assess the MP of an entire market. Finally, a joint clearing model is established to help implement the mechanism while promoting a high proportion of renewable energy consumption in the SEM. Case studies demonstrate the effectiveness and feasibility of the proposed approaches.

A Remedial Action Scheme To Mitigate Market Power Caused by Cyberattacks Targeting a Smart Distribution System

A Remedial Action Scheme To Mitigate Market Power Caused by Cyberattacks Targeting a Smart Distribution System

Exploring and Quantifying the Impact of Ex-Ante Market Power Mitigation in the Integrated European Day-Ahead Electricity Market

Exploring and Quantifying the Impact of Ex-Ante Market Power Mitigation in the Integrated European Day-Ahead Electricity Market

Market Power Mitigation in Two-Stage Electricity Markets With Supply Function and Quantity Bidding

Market Power Mitigation in Two-Stage Electricity Markets With Supply Function and Quantity Bidding

Market Power Mitigation in Transmission Expansion Planning Problems

The exercise of market power through network constraints in electricity markets can lead to high energy prices far from competitive prices. Traditional transmission expansion planning problem formulations do not consider strategic behavior of market agents. Therefore, they cannot capture the potential exercise of market power. In this paper, a predictor-corrector iterative algorithm is proposed to deal with market power mitigation in market-oriented transmission expansion planning problems. The predictor step consists of the solution of an equilibrium market model based on the conjectured supply function. The corrector step is a conventional transmission expansion planning posed as a mixed integer linear programming problem, where the feasible region is dynamically updated taking into account the results from the predictor step. Lerner index and other indices are used to quantify the potential market power. The algorithm finds the minimum cost expansion plan that avoids the exercise of market power through network congestion. The cost of this expansion plan is only slightly greater than the cost of a conventional expansion plan. The approach is illustrated using the 6-Bus Garver and the IEEE-24 RTS test systems.

Mixed Oligopoly and Market Power Mitigation: Evidence from the Colombian Wholesale Electricity Market*

Using information on price bids in wholesale electricity pools and empirical techniques described in the literature on electricity markets, this study identifies the market power mitigation effect of public firms in the Colombian market. The results suggest that while private firms exercise less market power than is predicted by a profit‐maximization model, there are marked differences between private and public firms in their exercise of unilateral market power. These findings support the hypothesis of the market power mitigation effect of public firms.

Ex-ante market power evaluation and mitigation in day-ahead electricity market considering market maturity levels

Market power is detrimental to the fair operation of the spot market, thus many market power evaluation and mitigation approaches have been put forward. However, due to the market maturity levels and the approaches themselves, excessive/deficient mitigation or high computational burden for a more accurate evaluation in practice are not rare. Therefore, in this paper, we propose a combined market power evaluation and mitigation framework, based on the emerging electricity day-ahead markets, in which the market power mitigation can be achieved ex-ante to the market clearing and can be flexibly adopted according to the market maturity levels during the development of the markets. More specifically, an ex-ante Customized Market Operation (CMO) indicator is first proposed to evaluate the market power of individual generators. Secondly, based on the CMO and the maturity of the market levels, an optimal CMO threshold is derived through the Best and Worst Method (BWM)-Entropy approach to mitigate the market power via limiting individual generators’ offer coefficients. Finally, the proposed CMO-BWM-Entropy approach is applied to the Chinese electricity markets under different maturity levels. Our results indicate that the accuracy of market power mitigation, quantified by the Lerner index, is 10 times higher than other existing ex-ante market power mitigation approaches, and the computational efficiency is 50 times faster than the compared ones.

Mitigating Market Power and Promoting Competition in Electricity Markets through a Preventive Approach: The Role of Forward Contracts

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.

A pricing mechanism to jointly mitigate market power and environmental externalities in electricity markets

The electricity industry has been one of the first to face technological changes motivated by sustainability concerns. Whilst efficiency aspects of market design have tended to focus upon market power concerns, the new policy challenges emphasise sustainability. We argue that market designs need to develop remedies for market conduct integrated with regard to environmental externalities. Accordingly, we develop an incentive-based market clearing mechanism using a power network representation with a distinctive feature of incomplete information regarding generation costs. The shortcomings of price caps to mitigate market power, in this context, are overcome with the proposed mechanism.

A unit commitment based-co-optimization of generation and transmission expansion planning to mitigate market power

• A unit-commitment-based generation and transmission expansion planning model is proposed. • The planning problem is subject to the market power's constraint. • The scenario-based model is structured as a mixed-integer bi-level programming (MIBP). • The lower-level problem computes the must-run generation (MRG) as a market index. • An exact algorithm using the reformulation-and-decomposition technique is utilized to attain the optimal solution. This paper aims to construct a novel strategy for coordinated generation and transmission expansion planning (CGTEP) considering market power. The integrated model constitutes bi-level programming from a centralized planning point of view. The upper level seeks to minimize the investment and operation cost subject to technical constraints, while the lower level's objective is to mitigate the market power. A stochastic unit commitment-based approach is employed at the upper level to find the least-cost solution and at the lower level to minimize the transmission-constrained market power index. Since the lower level contains integer variables, it is impossible to utilize the Karush-Kuhn-Tucker (KKT) conditions or duality theory (DT) to convert the bi-level problem into a single level. Hence, an exact algorithm using the reformulation-and-decomposition technique (RDT) is utilized to attain the optimal solution to this complex mixed-integer bi-level programming (MIBP) problem. The IEEE 118-bus electric power network is used for numerical studies. Results from the numerical studies signify the effectiveness of the presented model showing that a well-designated power system can significantly mitigate market power.

A review of market power‐mitigation mechanisms in electricity markets

AbstractParticipants in the supply and demand sides of electricity markets can potentially exercise their market power for their benefits. Hence, market power mitigation is an essential component of market management that physically and economically benefits operators by ensuring fairness in deregulated electricity markets. However, the mechanisms of mitigating market power in electricity markets pose several challenges in terms of market structure monitoring, market power evaluation, and market power mitigation. Therefore, this study provides a comprehensive analysis of market power mitigation mechanisms in electricity markets. First, a review of market structure monitoring and market power evaluation methods is provided to assess participants’ potential and degree of use/abuse of market power. Then, a detailed review of optimal bidding strategies in the supply and demand sides of electricity markets is provided. Accordingly, a systematic classification of market power mitigation is described. Finally, market power mitigation challenges and potential future research directions are discussed.

Research on the Effects of the Most Used Market Power Mitigation Mechanisms Considering Different Market Environments

The market power mitigation method of the supply-side has become one of the key points affecting the stability of the electricity spot market. Different mitigation mechanisms are used in the current mature electricity markets of the world. However, the same market power mitigation mechanism shows different effects in different market environments. Every market operator in the world needs the most efficient way to mitigate market power. Considering that there is no relevant literature discussing the market power effects of different mitigation methods in detail, the mitigation effects need to be discussed and further researched. So, we analyze the effects of the most utilized market power mitigation mechanisms while considering different market environments. Firstly, we establish a Nash-Stackelberg interactive game model to simulate the competitive strategies of power suppliers. Secondly, the different market power mitigation approaches are modeled. Then, a multi-agent system (MAS) genetic interior-point algorithm is proposed to solve the problem of suppliers. Finally, through the simulation analysis, the market power mitigation effects of different mechanisms while considering three operation states of the system in two market structures are all analyzed.

An experimental study of capacity remuneration mechanisms in the electricity industry

After electricity liberalization, the “energy-only market” design lacks effective incentives to invest in new capacity. Across the world, capacity remuneration mechanisms have been taking hold as an alternative to the energy-only market to ensure adequate power generation capacity. The way these designs are characterized reflects the insight from general economic theory on market power and strategic behavior. Indeed, Europe is heading toward a patchwork of different, uncoordinated national mechanisms. In practice, design choices are driven by national policies, needs and constraints. In addition, they are progressively converging toward a market-based mechanism with a forward period and market power mitigation. In this paper, we investigate their efficiency properties in terms of new investments, the reduction in unserved energy frequency and the energy prices of a generic capacity remuneration mechanism that is impervious to the so-called forward capacity market. The results from laboratory experiments confirm that this mechanism gives better incentives to invest in new capacity than the energy-only market alone and provides an empirical understanding of the investment decision process. The forward capacity market contributes to lower energy market prices in peak demand and extra-high peak demand periods and average energy costs if we consider the social cost of unserved energy.

A Predictor-Corrector Approach for Market Power Mitigation in Transmission Expansion Planning Problems

A Predictor-Corrector Approach for Market Power Mitigation in Transmission Expansion Planning Problems

Market power analysis in power systems using PSO based must run indices

The development of restructuring has encouraged and brought up competitive markets in power systems. However, the exercise of market power evokes monopoly into the power system and tends to decrease competitiveness. This article assesses the market power of a generating company in a power system using must run indices and proposes a method to mitigate market power. Modified must run generation, must run share (MRS) and nodal must run share indices are used to quantify the market power of generating companies. Phase shifting transformers (PST) are installed in selected lines for mitigating the market power. Particle swarm optimization is used in the determination of must run indices and optimizing the angle of Phase Shifting Transformers. IEEE 14 bus test system is used to illustrate the proposed technique. The analysis also includes the impact of contingencies. Sensitivity analysis is performed to analyze the impact of phase shifting angle variation on MRS. The results clearly quantifies the market power of a generating company and show that the market power incurred by the generating companies can be minimized by installing PST with optimum phase shift angle.

Market Power Mitigation Clearing Mechanism Based on Constrained Bidding Capacities

Market power has been a problematic issue for fair and transparent trades in various electricity markets. To deal with the problems of existing market power mitigation methods, such as complicated judgment criteria, excessive supervision probability, impersonal cost data accounting, and the requirements on perfect information circumstances, a novel spot market power mitigation clearing mechanism (MPMCM) is proposed, which manages to limit potential market power execution while avoiding overregulation and maintaining a real market supply–demand situation. The MPMCM consists of three processes, namely, market power evaluation, bidding capacity division, and bidding capacity constraint. The MPMCM is transformed into a set of bidding constraints and properly integrated in the common market clearing procedure. A bilevel mathematical problem with equilibrium constraints market equilibrium model is proposed to formulate the MPMCM for market simulation, and the mixed integer linear problem reformulation of the bilevel model is derived. Finally, an illustrative example is proposed to observe the strategic behaviors under various situations, thereby proving the validity and effectiveness of the MPMCM. A large-scale numerical example based on a modified IEEE 200-node system is proposed to prove the adaptivity of the MPMCM.

Rate Regulation Redux

In the 1990s, the Federal Energy Regulatory Commission (FERC) stopped treating power generation as a regulated monopoly and supported the development of competitive electricity markets. Competition has encouraged innovation and reduced costs, but the payment system FERC and grid operators developed has struggled to provide low-cost electricity without leaving itself vulnerable to market power abuses. In a payment system based on marginal costs, generators necessary for grid reliability cannot recover their fixed costs unless they charge high prices when supply is scarce. However, because these generators have market power, permitting them to recover their fixed costs leaves energy markets vulnerable to market manipulation. To mitigate market power abuses, every grid operator in the United States has introduced offer caps that limit revenues available in energy markets. Offer caps can prevent some generators from recovering their fixed costs, leading to a “missing money” problem as critical suppliers are forced out of business and potential new entrants cannot cover their start-up costs. Today, growing penetration of renewables is exacerbating the missing money problem. Regulators and grid operators are responding by administratively pricing certain resources and supporting specific units deemed too important to retire. These interventions lead to excess capacity and undermine competitive markets. As a result, current regulatory responses to the missing money problem recreate the inefficiencies that competitive markets were designed to solve, and they do so under questionable legal authority and at the expense of a clean energy grid. Rather than quietly revive cost-of-service rate regulation, this Article argues that FERC should simplify reserve requirements, stop counteracting state clean energy programs, and support the development of competitive markets for services that support grid reliability. Specifically, FERC and grid operators need not administratively reprice resources or force load-serving entities (LSEs), which distribute electricity to consumers, to transact with specific generators. Instead, the Commission should support long-term resource procurement markets that would be built on top of today’s short-term energy markets. Wholesale markets would consist primarily of short-term energy dispatch and balancing markets. They would not be relied on to ensure that revenues are sufficient to maintain resource adequacy.If LSEs were permitted to determine for themselves how to comply with resource procurement requirements, they could balance renewable policies, flexibility needs, and reserve mandates. This approach would maintain reliability while respecting FERC’s jurisdictional limits. Most importantly, it would prevent the Commission from quietly reviving cost-of-service regulation in regions that ostensibly abandoned that market structure decades ago.

Participation of an Energy Storage Aggregator in Electricity Markets

An important function of aggregators is to enable the participation of small energy storage units in electricity markets. This paper studies two generally overlooked aspects related to aggregators of energy storage: i) the relationship between the aggregator and its constituent storage units and ii) the aggregator's effect on system welfare. Regarding i), we show that short-term outcomes can be Pareto-inefficient: all players could be better-off. In practice, however, aggregators and storage units are likely to engage in long rather than short-term relationships. Using Nash Bargaining Theory, we show that aggregators and storage units are likely to cooperate in the long-term. A rigorous understanding of the aggregator-storage unit relationship is fundamental to model the aggregator's participation in the market. Regarding ii), we first show that a profit-seeking energy storage aggregator is always beneficial to the system when compared to a system without storage, regardless of size or market power the aggregator may have. However, due to market power, a monopolist aggregator may act in a socially suboptimal manner. We propose a pricing scheme designed to mitigate market power abuse by the aggregator. This pricing scheme has several important characteristics: its formulation requires no private information, it incentivizes a rational aggregator to behave in a socially optimal manner, and allows for regulation of the aggregator's profit.

Capacity Withholding Constrained by Operational Limits of Generation Under Financial Virtual Divestiture in a Day-Ahead Market

This paper develops an equilibrium-based model for ex ante analysis of capacity withholding under financial virtual divestiture in a day-ahead market, including one dominant producer and a number of small producers considered as a price-taking competitive fringe. We model the offering problem of the dominant producer as a bilevel optimization problem. In the upper-level problem, the dominant producer derives optimal strategy of physical capacity withholding restricted by operational limits of its own generating units and conditions stated in the financial virtual divestiture. In the lower-level problem, market operator clears the day-ahead market on an hourly basis. We recast the bilevel optimization problem as a mathematical programming with equilibrium constraints problem and convert it to a mixed integer linear programming problem. We show how the application of the financial virtual divestiture may mitigate market power in the day-ahead market, through a case study. The numerical results demonstrate that the dominant producer can exploit technological diversification of its own generating units to exercise market power, even in the presence of this market power mitigation policy.