Modernizing India’s electricity market: Opportunities for market-based PPAs, contracts for difference, and revenue-sharing contracts

During a process of energy transaction in electricity market, in order to ensure electrical safety and prevent excessively quick growth of electricity price, the concept of contract for difference (CfD) is introduced. Considering the electricity characteristics of large consumers, this paper is in the views of both generators and large consumers which sign CfDs with Grid Corporation respectively, but the signed CfDs only set rules for contract price and total contract energy in settlement period. Because market prices are different at different period, the total contract energy should be decomposed to each period for settlement of CfDs. So a CfD energy decomposition model, whose objective is to maximize social benefit, is built to settle the CfDs at each period. After running the model, the optimal result which means maximal social benefit is obtained and it is 28.1% more than that by average decomposition.

The Contract for Difference (CfD) is recognized as an efficient tool for hedging risks in electricity markets. The decomposition of a CfD aims to schedule the concerned contract energy over the contract period for future delivery and settlement, and could directly affects the amount and distribution of the excess capacity of a generator as well as its market power level. In this paper, a decomposition model of CfDs is proposed from the prospective of mitigating the potential market power in an electricity market. First, the residual demand is employed to analyze the impact of CfDs decomposition on market power. The well-established Cournot competition model and perfect competition model are next introduced for market power assessment. On this basis, a decomposition strategy with the objective of minimizing the market price markups is formulated as a bi-level optimization problem. Finally, a 6-unit test system is employed to demonstrate the proposed model, together with detailed analysis of numerical results.

This thesis analyzes transmission pricing, transmission congestion risks and their associated hedging instruments as well as mechanisms for stimulating investments in transmission expansion. An example of risk management in the case of a hydropower producer is included.After liberalization and restructuring of electricity markets, risk management has become important. In particular the thesis analyzes risks due to transmission congestion both in the short- and long-term (investments) for market players such as generators, loads, traders, independent system operators and merchant investors. The work is focused on the northeastern United States electricity markets and the Nordic electricity markets.The first part of the thesis reviews the literature related to the eight research papers in the thesis. This describes the risks that are relevant for an electricity market player and how these can be managed. Next, the basic ingredients of a competitive electricity market are described including the design of the system operator. The transmission pricing method is decisive for hedging against transmission congestion risks and there is an overview of transmission pricing models considering their similarities and differences. Depending on the transmission pricing method used, locational or area (zonal) pricing, the electricity market players can use financial transmission rights or Contracts for Differences, respectively. In the long-term it is important to create mechanisms for investments in transmission expansion and the thesis describes one possible approach and its potential problems.The second part comprises eight research papers. It presents empirical analyses of existing markets for transmission congestion derivatives, theoretical analyses of transmission congestion derivatives, modeling of merchant long-term financial transmission rights, theoretical analysis of the risks of the independent system operator in providing financial transmission rights, an analysis of inefficiencies associated with ignoring losses when utilizing area (zonal) pricing, and an application of an integrated risk management model on the power system of Norway’s second largest hydropower producer.The most important research findings include the following issues. First, Contracts for Differences in the Nordic market appear to be over-priced. Second, a merchant long-term financial transmission rights model is possible to realize in mathematical and economic terms. Third, by including the proceeds from a financial transmission right auction the independent system operator can issue a higher volume of rights because there is a relationship between the congestion rent, the proceeds from the auction and the payments to the financial transmission rights holders. Fourth, ignoring losses in the Norwegian area pricing, can lead to inefficiencies. Next, an integrated risk management model is applicable on large-scale power systems. Then, an overview is presented of different contractual arrangements that can be used to hedge transmission congestion risks. Finally, empirical data from existing financial transmission rights markets demonstrate how these markets work.

Electricity markets (EMs) are a relatively new reality and also an evolving one, since both market rules and market players are constantly changing. Market participants can purchase and sell electrical energy through centralized markets and bilateral contracts. The revenue and cost certainty associated with bilateral contracts presents a number of benefits to producers and consumers, notably price stability and mitigation of market power. An agent-based modeling and simulation approach presents itself as a promising approach to model power markets. Accordingly, this chapter presents several key features of software agents able to negotiate bilateral contracts—both forward contracts and contracts for difference (CFDs). The chapter also presents a case study aiming at analyzing the role of CFDs as a financial tool to hedge against pool price volatility. The results of four different simulations involving CFDs and compensations are compared with a “no-compensation” base case involving a forward contract, allowing us to conclude that CFDs can be a useful financial tool for producers, especially when market prices drop to (or below) their marginal cost of production.

Chapter 13 - Application of DERs in electricity market

Electricity markets (EMs) are a complex evolving reality -- new players and new business models are emerging and market rules are constantly changing. As EMs continue to evolve, there is a growing need for advanced modeling approaches that simulate the behavior of market participants, particularly how they may react to the economic, financial and regulatory changes that can occur in the environments in which they operate. This article presents several key features of software agents able to negotiate bilateral contracts in EMs, paying special attention to risk management, forward contracts and contracts for difference (CFDs). Also, it describes a set of case studies aiming at assessing the performance of CFDs as a risk management tool and comparing their performance to forward bilateral contracts.

A contract for difference is a medium and long-term financial contract, which can be used in the electricity market to lock the electricity price in advance and avoid the risk of electricity price fluctuations in the spot market. The construction of the domestic power spot market has just started. With the release of relevant policies and the gradual improvement of the market structure, it is urgent to design a corresponding trading mechanism to ensure the smooth transition of the market. The current day-ahead transactions, real-time transactions and other short-term transactions for distributed power generation, on the one hand power load forecasting, electricity price demand response and other related technologies need to be further improved, on the other hand due to the randomness and uncertainty of distributed energy, participating in the short-term spot market has large price fluctuations, which is not conducive to the stability of the electricity market, and it is also not conducive to the consumption of distributed energy. Aiming at the above problems, this paper uses the characteristics of CFDs to restrain market power to design a distributed energy trading mechanism to achieve the purpose of energy saving and emission reduction.

The European electricity market is on the brink of transformative regulatory changes designed to reshape its landscape fundamentally. These changes encompass measures aimed at ensuring market stability, enhancing efficiency, promoting investment in clean energy, and safeguarding stakeholders from energy crises. Central to these reforms is the promotion of Power Purchase Agreements (PPAs) and Contracts for Difference (CFDs) to stabilize markets. Considering that existing barriers are impeding PPAs widespread adoption, the new design of the electricity market prompts regulatory adjustments to streamline access while maintaining fair competition. Concurrently, the design of CFDs must navigate competition distortions and ensure long-term viability, posing challenges for the European Commission in aligning them with State aid rules. Efforts to boost market efficiency include the reduction of intraday gate closure times, effective January 2026, and the establishment of minimum bid sizes to optimize resource allocation and pricing mechanisms. Moreover, the regulatory framework prioritizes incentivizing investments in clean energy, underscoring Europe’s commitment to sustainability. Member states will wield the power to implement non-fossil flexibility support schemes, offering payments for available non-fossil flexibility capacity, thereby fostering the transition towards cleaner energy sources. Lastly, protective measures are being instituted to shield consumers and undertakings from energy crises, emphasizing the need for resilience and stability in the sector. As these reforms unfold, policymakers must delicately balance fostering innovation, ensuring competitiveness, and safeguarding stakeholders’ interests. This article delves into the complexities of these reforms, offering insights into their implications and challenges.

In this paper, the necessity to study financial risks in electricity markets, the application of the value at risk (VaR) method and the feasibility of historical simulations are firstly introduced and discussed. Then the gross profit, daily VaR and weekly VaR models of an electricity company (the unique buyer) based on practical conditions of the Zhejiang electricity markets are presented, and the corresponding computational results are reported. Furthermore, the application of historical simulations in financial risk investigations of electricity markets is analyzed, and the influence of the two factors (contracted price Pc and contract rate k) of CFD (contract for difference) on the company's gross profit and daily VaR are discussed. The numerical results revealed that the historical simulation is suitable to analyze and to predict the short-term financial risk (next day or next week) of electricity market. It is intuitive, simple and easy to implement.

In order to curb market power, encourage investment and redistribute welfare, revenue regulation should be carried out in electricity market. The incentive contract represented by the Contract for Difference is a kind of regulation. This paper proposes a Government Authorized Contract based on Revenue Estimation Method (REM) from the perspective of regulating generation revenue. First, the principle and design of the Vesting Contract in Singapore electricity market is employed, analyzing its limitations in regulation. Then, the incentive contract based on REM is presented in four steps. Finally, the IEEE30 node classic system is adopted to demonstrate the proposed model, showing that it can promote generators to bid rationally.

In this paper, a pricing mechanism is proposed for the electricity supply chain, which is consisting of one generation company (GC), multiple consumers, and competing utility companies (UCs). The UC participates in electricity supply chain management by a revenue sharing contract (RSC). In the electricity supply chain, the electricity real-time balance has an important role in the stable operation of the power system. Therefore, we introduce the demand response into the electricity supply chain to match supply with demand under forecast errors. Hence, we formulate a noncooperative game to characterize the interactions among the multiple competing UCs, which set the retail prices to maximize their profits. Besides, the UCs select their preferred contractual terms offered by the GC to maximize its profits and coordinate the electricity supply chain simultaneously. The existence and uniqueness of the Nash equilibrium (NE) are examined, and an iterative algorithm is developed to obtain the NE. Furthermore, we analyze the RSC that can coordinate the electricity supply chain and align the NE with the cooperative optimum under the RSC. Finally, numerical results demonstrate the superiority of the proposed model and the influence of market demand disruptions on the profits of the UCs, GC, and supply chain.

In view of the existence of contract for difference (CFD) in the electricity market, the market rules require all the entities of the market to participate in spot market bidding. This study develops a step-wise planning model to determine the bidding curves on day-ahead market for electricity sales companies. Due to the deviation between the actual electricity consumption and the bidding amount in the day-ahead market, both punishment of electricity deviation and risk are taken into account, and the relationship between them is weighed by different coefficients. Because the competitor's bidding curve is unknown, and it is assumed that their bidding coefficients obey the normal probability distribution, then a stochastic optimization method based on Monte Carlo simulation is developed. A numerical example serves to illustrate the impacts of different factors on the electricity sales companies’ profit expectation and variance. The results show that electricity sales companies can benefit from optimizing the coefficients of each factor in different market environments.

The paper introduces a framework of operation of maritime-related enterprises like port authorities and ship-owning or operating companies along with electric energy providers in the electric energy market as a consequence of the global decarbonization effort and, in particular, due to the implementation of ship electrification at berth. Within this context, the main rules of this energy market framework will consist of a proper combination of power purchase agreements along with contracts for difference in an attempt to obtain transactions that are mutually beneficial at least on a mid-term basis. The methodology, which is fully compatible with the electric energy market rules of the European Union, is enriched by a variety of alternative scenarios on the selling prices of electricity, showing that even when monthly or annual periods are used for reference, it is highly possible that all parties engaged have benefits.

This chapter presents the key features of an agent-based simulation tool, called MATREM (for Multi-Agent TRading in Electricity Markets). The tool allows the user to conduct a wide range of simulations regarding the behavior and outcomes of electricity markets (EMs), including markets with large penetrations of renewable energy. In each simulation, different autonomous software agents are used to capture the heterogeneity of EMs, notably generating companies (GenCos), retailers (RetailCos), aggregators, consumers, market operators (MOs) and system operators (SOs). The agents are essentially computer systems capable of flexible, autonomous action and able to interact, when appropriate, with other agents to meet their design objectives. They are able to generate plans and execute actions according to a well-known practical reasoning model—the belief-desire-intention (BDI) model. MATREM supports two centralized markets (a day-ahead market and an intra-day market), a bilateral market for trading standardized future contracts (a futures market), and a marketplace for negotiating the terms and conditions of two types of tailored (or customized) long-term bilateral contracts: forward contracts and contracts for difference. The tool is currently being developed using both JADE—the JAVA Agent DEvelopment framework—and Jadex—the BDI reasoning engine that runs over JADE, enabling the development of BDI agents. A graphical interface allows the user to specify, monitor and steer all simulations. The human-computer interaction paradigm is based on a creative integration of direct manipulation interface techniques with intelligent assistant agents. The target platform for the system is a 32/64-bit computer running Microsoft Windows.

Determining commercially viable two-way and one-way ‘Contract-for-Difference’ strike prices and revenue receipts