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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]

Inverse equilibrium modeling fits parameters of an equilibrium model to observations. This allows investigation of whether market structures fit observed outcomes and it has predictive power. We introduce a methodology that leverages relaxed stationarity conditions from Karush-Kuhn-Tucker conditions to set up inverse equilibrium problems. This facilitates reframing of existing equilibrium approaches on power systems into inverse equilibrium programs. We illustrate the methodology on network-constrained and unconstrained Nash-Cournot games between price-making power generators. The inverse equilibrium problems in this paper reformulate into linear programming problems that are flexible and interpretable. Still, inverse equilibrium modeling provides generally inconsistent estimation and econometric approaches are better for this purpose. [ABSTRACT FROM AUTHOR]

We study market equilibria that are achieved by strategic firms that participate in electricity and natural gas markets. Strategic firms submit their offers and bids to both markets with the aim of maximizing profit or utility and we consider firms that can include a combination of electricity and natural gas supply and demand. The strategic actions of these firms are represented by upper-level problems that are optimized subject to shared lower-level problems that represent the clearing of electricity and natural gas markets. This market structure and our modeling approach yields a multiple-leader/two-follower complementarity problem. We develop a modeling approach that can find equilibria with different characteristics, e.g., maximized social welfare, producer profits, or consumer welfare. We demonstrate numerically that producers aim typically to increase market prices while consumers seek to decrease them. [ABSTRACT FROM AUTHOR]

While power system organization has evolved from a hierarchical structure to a more decentralized model, electricity markets are still not up to date with the ongoing transformation toward more consumer-centric economies. As information and communication technologies are broadly adopted, they allow prosumers to have a more proactive role in power system operation. This work introduces the concept of energy collectives, as a community-based electricity market structure. We find that when prosumers are allowed to share energy at community level, the overall electricity procurement for the community reflects prosumers’ preferences. We show that community members can be influenced by a supervisory third-party in charge of interfacing with the market and system operator and of guaranteeing the collective common agreements. We simulate a number of test cases and apply typical principles from analysis of communication networks and distributed systems to assess community fairness. [ABSTRACT FROM AUTHOR]

We consider an energy-only electricity market where some generation and/or load is uncertain, and where there are flexibility costs, i.e. some conventional power plants have to be scheduled well before real time in order to participate in the dispatch, while for others, additional cost incurs if generation plans have to be adjusted close to real time. In practice, electricity markets are often organized with sequential market clearing, and in this paper, we consider two sequential markets, for instance representing a day-ahead and a real-time market. We compare the outcomes of 1) a stochastic market clearing model, i.e. an integrated model that takes into account both markets and the uncertainty, to 2) a myopic market clearing model, where the first market is cleared based only on given bids, and not taking into account neither the uncertainty nor the bids to the second market. Compared to previous literature, our main contribution is that we compare the two different market models with respect to both efficiency and allocation of surplus, and thus the incentives they imply for the market participants. We discuss what information is needed in market agent bids and how that information can be manipulated. While the stochastic market clearing gives a solution with a higher expected social welfare, it poses several challenges for market design. The stochastic dispatch may lead to a dispatch where the day-ahead prices deviate from the bid curves to the first market. This can lead to incentives for self-scheduling, in that it may require market participants to accept prices that deviate from the marginal costs or benefits corresponding to the scheduled quantities. Our analysis shows that the intermittent producer has an incentive to deviate from the system optimal plan in both the myopic and stochastic model, and this incentive is particularly strong under the myopic model. We also discuss how the expected social welfare of the market outcome under stochastic market clearing depends on the quality of the information that the system operator will base the market clearing on. In particular, we show that an intermittent producer may have an incentive to misreport the probability distribution for its generation. [ABSTRACT FROM AUTHOR]

The stated aim of the European Commission has been the unbounded flow of energy across Europe and the effective functioning of a single European power market so as to achieve secure, sustainable and affordable energy supplies, as well as to foster competition and increase the utilization of electricity networks and generation capacity. Most countries have already adapted or are gradually adapting their wholesale markets to the provisions of the so called Target Model for the internal electricity market in Europe, however Greece still lies behind in this binding target. In this paper, the basic design variables and respective options for the integration of the Greek wholesale electricity market with the other European markets under the Target Model paradigm are presented. The design variables refer to all market instances and mechanisms. The proposed choices are justified in terms of effectiveness and market power mitigation, considering the current market structure in Greece. A transitional phase for the full integration of the Greek Intraday and Balancing Markets is proposed, considering the relevant evolutions in the wholesale markets of Greece’s neighboring countries. Finally, a simulation analysis is performed in order to highlight the implications on schedules of utilizing European-based order formats in the restructured Greek electricity market. [ABSTRACT FROM AUTHOR]

This paper looks at the empirical and theoretical background to high shares of renewables in the electricity system. First we examine what is meant by "high shares" of renewables; next we consider what we mean by electricity "markets"; then we discuss what the term "cope with" implies; before returning to the suitability of "current" electricity markets. Second, we turn to three examples of jurisdictions--Germany, the UK and the State of New York in the US--with specific aspirations for decarbonisation and the role of renewables. Each exhibits very different approaches to the way they are adjusting their electricity market design to cope with high shares of renewables. We suggest that a new wave of electricity experiments is beginning around the theme of how to incorporate large shares of intermittent renewable generation in to electricity systems. [ABSTRACT FROM AUTHOR]

In many electric systems worldwide the penetration of Distributed Energy Resources (DER) at the distribution levels is increasing. This penetration brings in different challenges for electricity system management; however if the flexibility of those DER is well managed opportunities arise for coordination. At high voltage levels under responsibility of the system operator, trading mechanisms like contracts for ancillary services and balancing markets provide opportunities for economic efficient supply of system flexibility services. In a situation with smart metering and real-time management of distribution networks, similar arrangements could be enabled for medium- and low-voltage levels. This paper presents a review and classification of existing DER as flexibility providers and a breakdown of trading platforms for DER flexibility in electricity markets. [ABSTRACT FROM AUTHOR]

With changes to carbon output imminent as a result of governmental policies, the method by which energy generators in competitive markets are selected for operation can be called into question. We first simulated a bid-based day-ahead market with human participants and then analyzed generation asset owners’ profits based on bid strategy. We then studied computing generator unit dispatch for this simulated market by introducing an environmental index related to the carbon intensity of the relevant fuel type, and computing dispatch via linear programming to either maximize or minimize this index subject to the constraint that average profits be the same as in the original market simulation. The results show that lower bids, even below cost, are most profitable for generators, and that adding an environmental weighting to the bid process has the potential to reduce carbon intensity of power generation without reducing overall average profitability to generators or increasing cost to consumers. This research concludes an environmental score should be explored as a potential weighting factor in bid-based electricity market dispatch. [ABSTRACT FROM AUTHOR]

Efficient electricity day-ahead market designs include virtual transactions. These are financial contracts awarded at day-ahead prices and settled at real-time prices. Under current PJM market rules, there is an asymmetry in the settlement treatment of different types of virtual transactions, but a recent recommendation by PJM to eliminate this asymmetry is problematical. [ABSTRACT FROM AUTHOR]

Thailand's power system has been facing an energy transition due to the increasing amount of Renewable Energy (RE) integration, prosumers with self-consumption, and digitalization-based business models in a Local Energy Market (LEM). This paper introduces a decentralized business model and a possible trading platform for electricity trading in Thailand's Micro-Grid to deal with the power system transformation. This approach is Hybrid P2P, a market structure in which sellers and buyers negotiate on energy exchanging by themselves called Fully P2P trading or through the algorithm on the market platform called Community-based trading. A combination of Auction Mechanism (AM), Bill Sharing (BS), and Traditional Mechanism (TM) is the decentralized price mechanism proposed for the Community-based trading. The approach is validated through a test case in which, during the daytime, the energy import and export of the community are significantly reduced when 75 consumers and 25 PV rooftop prosumers participate in this decentralized trading model. Furthermore, a comparison analysis confirms that the decentralized business model outperforms a centralized approach on community and individual levels. [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]

In the electricity market, different pricing models can be applied to increase market competitiveness. Different electricity systems use different market structures. Uniform marginal pricing, zonal marginal pricing, and nodal marginal pricing methods are commonly used market structures. For markets wishing to move from a uniform pricing structure to a more competitive zonal pricing structure, the determination of price zones is critical for achieving a competitive market that generates accurate price signals. Three different pricing zone detection algorithms are analyzed in this paper including the k-means clustering and queen/rook spatially constraint clustering. Finally, the results of a case study for the Turkish electricity system are shared to compare each method. [ABSTRACT FROM AUTHOR]

• HHI and CRn are not applicable for market power measurement in electricity markets • Choice of structural index depends on market structure and cartel conspiracy risk • PDI addresses market parameters and possibility of producers' strategic positions • PDI and RSI have high correlation with market-clearing prices and demand • RSI and PDI can describe the market power exercise for Russian electricity market Typical market share indices are rarely suitable for market power measurement in electricity markets since they do not take into account major market features. This leads to the necessity of developing new or modification of existing instruments. In this paper, we study and assess outcomes of typical market share indices, and variations of Residual Supply Index (RSI). We propose a new market parameters dependent index (PDI) and a corresponding methodology, which as well relies on residual demand, demand elasticity, and incorporates a threshold value of price rise. We implement statistical methods on market data to derive values of indices and the relation between RSI and PDI. Then we formulate the conditions when the indices provide appropriate results and give them justification. [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]

The paper first provides, for Latin America and the Caribbean, country-specific synthetic quantitative measures of the degree of adoption of governance reforms in the electricity sector, focusing on four key dimensions (market structure, private sector participation (PSP), regulatory autonomy and operational organization). These measures are then correlated with standard policy performance outcomes measures. The findings suggest that, the reforms, considered jointly, were statistically significantly associated with higher technical and process quality but not with social or service improvements. Considered individually, increased regulatory autonomy enjoyed the highest positive correlation with desirable outcomes, but PSP has no significant correlation with any of the outcomes. In sum, as of 2018, governance reforms, considered jointly, had still not delivered on some promised payoffs, notably in addressing energy poverty, although the sensitivity analysis suggests that, for some indicators, the relationships are stronger for larger than for smaller countries. • Governance reforms are statistically associated with higher technical and process quality. • But they are not associated with social or service improvements. • Excessive reform standardization failed to address country specificities well enough. [ABSTRACT FROM AUTHOR]

• California has a new method to report retail electricity GHG emissions intensities. • The new rules focus on emissions accounting based on physical grid conditions. • The new rules improve the accuracy of emissions associated with retail loads. • However, a handful of transient effects could bias reported emissions downward. Accurately attributing greenhouse gas (GHG) emissions in the electric power sector is critical to measuring progress towards climate policy goals. We evaluate a new methodology adopted by the California Energy Commission to calculate the GHG emissions intensity of retail electricity providers. In the long run, the new regulations better align with the physical nature of grid operation than did past practices, but policymakers should monitor a set of potential challenges as market structures evolve. [ABSTRACT FROM AUTHOR]

• Two models for the participation of PV power producers in three market floors. • Rescheduling following the characteristic of the six intraday market sessions. • Risk-hedging map associated with the scheduling and rescheduling of the bids. Optimal bidding that considers different electricity market floors can increase the financial gains of photovoltaic (PV) power producers. However, the current approach to trading PV power essentially consists of committing to sell the forecasted PV generation. To analyze profits and investigate new business opportunities for PV power producers, this paper proposes two novel stochastic programming-based methods for scheduling and rescheduling for trading the PV generated energy in day-ahead and intraday electricity markets. Risk-hedging is also considered in terms of co-optimizing the expected profit with the Conditional Value-at-Risk (CVaR) metric. As a consequence of the structure and organization of the market floors and due to different market windows, rescheduling is necessary to exploit the most recent information. Updated rescheduling progressively reveals actual profits or losses, risk-hedging possible engagement in business transactions, and the final effect of strategic bidding. A case study in the Spanish electricity market based on actual data is presented. The analysis of the case study shows the influence of the three market floors (day-ahead, intraday, and imbalance), the participation in multiple intraday sessions, risk-hedging, and rescheduling on the profits of the PV producer. [ABSTRACT FROM AUTHOR]

The European Commission's call for energy communities has motivated academia to focus research on design and trading concepts of local electricity markets. The literature provides a wide range of conceptual ideas and analyses on the technical and economic framework of single market features such as peer-to-peer trading. The feasible, system-wide integration of energy communities into existing market structures requires, however, a set of legal adjustments to national regulation. In this paper, we test the implications of recently proposed market designs under the current rules in the context of the German market. The analysis is facilitated by a simplistic equilibrium model representing heterogeneous market participants in an energy community with their respective objectives. We find that, on the one hand, these proposed designs are financially unattractive to prosumers and consumers under the current regulatory framework. On the other hand, they even cause distributional effects within the community when local trade and self-consumption are exempt from taxes. To this end, we introduce a novel market design—Tech4all—that counterbalances these effects. With only few legal amendments, it allows for ownership and participation of renewable technologies for all community members independent of their property structure and affluence. Our presented analysis shows that this design has the potential to mitigate both distributional effects and the avoidance of system service charges, while simultaneously increasing end-user participation. [ABSTRACT FROM AUTHOR]

• An equilibrium problem integrated with individual risk-averse features is proposed. • The conditional value-at-risk method is used for individual risk-averse evaluation. • The linearization and binary expansion method are used to solve the nonlinearity. • The model can better formulate the market with several risk-averse oligopolies. With the deregulation of world power markets, the importance of power market equilibrium analysis tools becomes more prominent. Due to the increasing uncertainty in the power markets, the influences of risk attitudes on the participants' strategic bidding behaviors and market equilibrium become more significant, which makes risk feature formulation more necessary in the market bidding decision-making process. This paper fully considers the risk-averse features of power generation companies based on the concept of the conditional value at risk and proposes a bilevel equilibrium model to practically simulate market behaviors. The mathematical model is essentially a modified equilibrium problem with equilibrium constraints. The upper-level problem of the model maximizes the profits minus the risks of each generation company, while the lower-level problem represents the market clearing processes of day-ahead markets by the independent system operator. A linearization method is proposed to transform the proposed model into a mixed-integer linear model. An illustrative example and a numerical example are performed to show the effectiveness, validity and adaptability of the proposed model. The comparisons with other equilibrium models demonstrate the better performances of the proposed method to simulate the market equilibrium with several oligopolies. The sensitivity analysis is proposed to analyze the phenomenon where different risk-averse levels and market ownership structures would result in different market equilibrium. [ABSTRACT FROM AUTHOR]