Congestion Revenue Research Articles

When Efficiency Meets Equity in Congestion Pricing and Revenue Refunding Schemes

When Efficiency Meets Equity in Congestion Pricing and Revenue Refunding Schemes

A Transmission Price Design Considering the Marginal Benefits of the Transmission and Spatiotemporal Information of Electricity Demand

One of the most critical tasks of China’s power sector reformation is re-designing transmission and distribution (T&D) prices, which are essential in establishing fair and ordered power markets and encouraging the efficient allocation of resources. In view of the problems in China’s power market, such as the lack of a market mechanism for the reasonable allocation of congestion revenue, unreasonable transmission cost composition, and the failure of the transmission pricing mechanism to reflect the utilization degree of transmission resources by users in different geographical locations, this study proposes a transmission price design under the application scenarios of regional power grids and provincial power grids dominated by meshed AC networks in China that considers the marginal benefit of the transmission and spatiotemporal information of electricity demand. The proposed method effectively tackles the above-mentioned problem, with the transmission cost being divided into two parts: the expansion cost reflecting the marginal benefits of transmission, and the residual cost reflecting the rest. The expansion cost is objective and based on power system economics; it is calculated as the congestion revenue under the location marginal price-based wholesale electricity markets, resulting in a more reasonable division of transmission costs and allocation of congestion revenue. Furthermore, allocating the residual cost with the power flow distribution factor and the postage stamp method also reflects the utilization degree of transmission resources by users in different geographical locations. The effectiveness of this transmission price design is confirmed by testing it against a 3-bus and an IEEE 30-bus system.

Coordination of dynamic tariff and scheduled reprofiling product for day-ahead congestion management of distribution networks

The increasing penetration of distributed energy resources in distribution networks poses new challenges to the secure and efficient operation of distribution networks. One major challenge is the network congestion caused by the non-coordinated operation of flexible demands, such as electrical vehicles and heat pumps. In general, there are two categories of market-based day-ahead congestion management methods for distribution networks: price-based method and incentive-based method. In order to use the synergy of the two types of methods and to resolve potential conflicts against regulations when one type of method is implemented solely, a coordination scheme of the two types of methods is proposed for efficient day-ahead congestion management. In the proposed coordination scheme, the dynamic tariff (DT) as a price signal is used to partly resolve congestion firstly, and the scheduled reprofiling product (SRP) as an incentive-based flexibility service product is used to deal with the remaining congestion. By employing the coordination scheme, the distribution system operator (DSO) holds the profit neutral position in terms of congestion management, denoting that the DSO does not have the congestion management cost or revenue. Based on the DT model and SRP-based model, the coordination problem is formulated as a two-level non-convex mixed-integer non-linear programming (MINLP) model that is transformed into a one-level MINLP model with linear constraints and is solved by a proposed particle swarm optimization-based solution strategy. The Roy Billinton Test System was used to conduct case studies to validate the effectiveness of the proposed coordination scheme for day-ahead congestion management in distribution networks. The case study results demonstrate that the proposed coordination scheme can efficiently resolve congestion by the coordination of the DTs and SRPs while ensuring that the DSO is in a profit neutral position.

Transmission Integration and the Market for Congestion Revenue Rights

Texas electricity market saw a recent integration of electricity transmission as a part of Competitive Renewable Energy Zones (CREZ). Exploiting the commissioning date of CREZ based transmission integration as an exogenous shock, we analyze the effect of transmission expansion on market clearing prices of Congestion Revenue Rights (CRR). Reduced form estimates suggest that excess transmission led to a lowering of CRR prices for contracts at all Times of Use. We find strong evidence of spatial, distributional, and firm specific heterogeneity. The paper shows that transmission expansion enhanced efficiency of the CRR market in terms of a spatial convergence in prices and a decrease in aggregate auction expenditure of approximately $260 million over a period of 4.5 years post CREZ.

Study on the allocation of congestion revenue under doubletrack pricing system

The introduction of nodal spot market has brought unneglectable problem of congestion revenue allocation in China. Meanwhile, the coexistence of market and regulation in nowadays power market in China added specialty when it comes to appropriately allocate congestion revenue in China. Based on thorough review and analysis on both the principle of congestion revenue allocation as well as the status quo of a typical provincial market in China, this paper attempts to tackle this problem with consideration on property right, with which the contribution to the grid network of electricity users are taken into account. The solution is established in two stages, which is based on the reality that the distribution of two types of users in each node remains currently unknown.

Convergence bids and market manipulation in the California electricity market

Abstract Financial instruments are designed to improve the efficiency of a physical market in theory. In practice, underlying physical relationships may prevent financial instruments from working as intended. This paper analyzes the relationship between two financial instruments in electricity markets: convergence bidding and congestion revenue rights. Convergence bids allow participants to trade virtual power, whereas congestion revenue rights capture the value of congestion on a transmission line. Both instruments were introduced to solve inefficiencies, however the interaction of these two instruments provides incentives for manipulation. In this work I test whether the financial instruments are being used as intended. The results show that electricity market participants are more likely to hold unprofitable convergence bids on a node where the convergence bid can benefit the value of the congestion revenue rights held at that node. This type of uneconomic convergence bid is consistent with manipulative behavior. I then perform a back of the envelope calculation that shows these potentially manipulative convergence bids create inefficiencies in the market.

Generalized Convex Hull Pricing for the AC Optimal Power Flow Problem

We study an abstract myopic electricity market subject to general nonconvex power flow models and convex generator models (without discrete commitment variables) in a setting where there may be no market equilibrium that guarantees revenue adequacy of the independent system operator. A generalized version of convex hull prices (CHPs) are proposed and are defined to solve a novel multiobjective minimum uplift problem that captures the tradeoff between generator side-payments and potential congestion revenue shortfall (PCRS). A convex primal counterpart of this multiobjective minimum uplift problem, called the primal CHP problem , is formulated in terms of the convex hull of the set of feasible net power injections. Indeed the term convex hull price derives from the result that the CHPs are equivalent to the optimal Lagrange multipliers of the primal CHP problem . However, depending on the chosen model of the transmission network, the convex hull of the feasible set of net power injections may be intractable to evaluate. In this case, CHPs are approximated using state-of-the-art convex relaxations that are efficiently solvable. This is the first proposed method of approximating CHPs in polynomial-time that is general enough to accommodate the nonlinear transmission constraints in the AC optimal power flow (OPF) problem. In our abstract myopic market setting, we show that tight relaxations of the AC OPF problem can be used to effectively approximate CHPs that decrease potential congestion revenue shortfall significantly with little effect to side-payments.

The Legal and Economic Challenges for Single Interconnector Companies in the European Electricity Market – The Baltic Cable Case

The legal and economic challenges, which Single Interconnector Companies face, are currently subject to a preliminary ruling procedure in front of the European Court of Justice (“ECJ”, Case C-454/18). This case deals with the application and interpretation of Article 16 (6) of Regulation (EU) No 714/2009 of 13 July 2009 on conditions for access to the network for cross-border exchanges in electricity (“Regulation 714/2009”). Article 16 (6) Regulation 714/2009 regulates the use of congestion revenues that are obtained by allocating interconnector capacity to the market. Interconnectors can be classified into two types: - interconnectors owned by a Transmission System Operator (“TSO”) as part of a larger transmission system (“regular TSO”), where the costs of the interconnector are carried by network users, and - interconnectors owned by a so-called “Single Interconnector Company” without network users. The application of Article 16 (6) Regulation 714/2009 to regular TSOs is straightforward. Article 16 (6) Regulation 714/2009 aims to ensure that network users benefit from the congestion revenues. In the case of regular TSOs, network users cover all costs and risks associated with the interconnector through network tariffs: Congestion revenues should thus be used to invest in additional interconnection capacity or to reduce network tariffs. The application of Article 16 (6) Regulation 714/2009 to Single Interconnector Companies is not straightforward. Congestion revenues are the sole source of income for Single Interconnector Companies and they do not socialise costs and risks to network users. Applying Article 16 (6) Regulation 714/2009 to Single Interconnector Companies in exactly the same way as to regular TSOs would cause Single Interconnector Companies to go bankrupt, an effect obviously not intended by the EU regulation. Therefore, another interpretation and application of Article 16 (6) Regulation 714/2009 is needed. And solutions do exist. Current practice for interconnectors between Great Britain on the one hand, and Ireland, France and Belgium on the other hand, show that such different interpretation and application is possible and already good practice of renowned national regulatory authorities applying respective European Union (“EU”) law. The following assessment shows that this practice is fully in line with the objectives of Article 16 (6) Regulation 714/2009 and of EU legislation in general, as it fosters investments in new interconnection capacity and provides incentives to make all interconnection capacity available. The wording of Article 16(6) Regulation 714/2009 has been changed and can now be found in the new Article 19 of Regulation (EU) 2019/943 of 5 June 2019 on the internal market for electricity (“Regulation 2019/943”) which is part of the so-called Clean Energy Package. It allows the Agency for the Cooperation of Energy Regulators (“ACER”) to provide guidance on a proper application of the regulations regarding the use of congestion revenues. These developments flowing from the Clean Energy Package point in the right direction as a harmonised, fair and legally sound application of EU law to Single Interconnector Companies as truly European companies running cross-border infrastructure and bearing risk without being able to pass it on to network users, is much needed.

COSTOS DE GENERACIÓN, INVERSIÓN Y PRECIOS DEL SECTOR ELÉCTRICO EN MÉXICO

<p>Los precios de la electricidad han registrado una marcada tendencia al alza desde la implementación de la reforma en el mercado eléctrico (RME) de México, que ha sido citada por algunos como evidencia de su fracaso. En este artículo estudiamos los determinantes de esa alza mediante la deducción de la curva de costos de generación de la Comisión Federal de Electricidad, antes de la entrada en vigor de la reforma, la construcción de datos horarios sobre precios promedios y el estudio de la relación entre precios y rentas de congestión. Los resultados principales del documento muestran que los tipos de tecnología de generación más rentables son los resultantes de la RME y que el aumento de los precios registrado durante los primeros años de la RME se explica, principalmente, por una creciente congestión de la red nacional de transmisión eléctrica más que por un diseño ineficiente de la competencia en el sector de generación.</p><p> </p><p align="center">GENERATION COSTS, INVESTMENT AND PRICES IN MEXICO’S ELECTRICITY SECTOR<strong></strong></p><p align="center"><strong>ABSTRACT</strong><strong> </strong><strong></strong></p>Electricity prices have seen a consistent upward trend since the implementation of Mexico’s electricity market reform (EMR). This has been interpreted by some as a failure of the EMR. In this paper we study the determinants of such price increases. We calculate the generation cost curve of the Federal Electricity Commission prior to the entry into force of the reform. We then construct daily data on average prices during the EMR. We also finally study the relationship between prices and transmission congestion rents. Our main results indicate that the most profitable types of generation technology are the ones resulting from the EMR. Likewise, price increases have taken place despite the existence of a considerably larger number of competitors in the generation sector. Lastly, the strong correlation between prices and congestion revenues is evidence that the increase in prices under the EMR is mainly due to the growing congestion in the national electricity transmission network rather than due to an inefficient competitive market design in the generation sector.

A Review of Price Risk Management in PJM and Nord Pool Electricity Market

Market participants and system operators are faced with price risks caused by various factors, such as congestions or market power abuse. Therefore, the price risk management in deregulated market environment is of great importance. In this paper, various risk-hedge financial instruments in PJM and Nord Pool, such as FTRs, futures, forwards and CFDs are investigated. These risk management mechanisms can be further utilized for congestion revenue allocation, speculation or arbitrage under different market circumstances.

Risk and Abnormal Returns in Markets for Congestion Revenue Rights

In organized energy markets that use locational pricing, power generators and energy suppliers procure financial transmission rights (FTRs) to hedge against grid con- gestion charges, while third-party speculators attempt to capture a return with these extremely volatile contracts. This paper develops a novel methodology for estimating the systematic risk of individual FTRs and detecting the presence of abnormal returns among these financial instruments. The prevalence of congestion paths with abnormal returns could be used by policy experts as an efficiency measure when assessing the performance of FTR markets. Being the only organized energy market in the Western Interconnection, California has implemented a version of FTRs officially known as congestion revenue rights (CRRs). This paper applies the proposed methodology to all auctioned CRRs from 2009 to 2015. Our analysis identifies the paths that exhibit persistent abnormal returns, with the majority of them being positive. We also compare the patterns of risk and abnormal returns between on-peak and off-peak CRRs, and find no significant differences.

Risk and abnormal returns in markets for congestion revenue rights

Risk and abnormal returns in markets for congestion revenue rights

Time-of-day vehicle mileage fees for congestion mitigation and revenue generation: A simulation-based optimization method and its real-world application

Congestion pricing of a large-scale network is characterized by expensive-to-evaluate objective functions without closed forms. This paper further enhances a computationally efficient simulation-based optimization (SBO) framework to solve the problem within tight computational budget. This paper applies surrogate models to solve the optimization problem with computationally expensive objective functions based on simulation-based dynamic traffic assignment (DTA). DIRECT (a deterministic search algorithm with modification to Lipschitzian optimization) is used for metamodel parameter tuning. A trade-off of different objectives (i.e. the average travel time minimization, expected network throughput maximization, and toll revenue maximization) are converted into a single desirability function. To demonstrate the SBO framework with an application to the vehicle mileage traveled (VMT) based pricing for a real-world freeway network, this paper utilizes a calibrated simulation-based DTA model to evaluate system performance. A stochastic mesoscopic simulator is applied. We investigate the existence of an invariant macroscopic fundamental diagram (MFD) for the network, and compare simulated MFDs with measurements of fixed detectors and probe data. The proposed SBO framework is generic and can be used to solve other congestion pricing problems.

A Market-Based Transmission Planning for HVDC Grid—Case Study of the North Sea

There is significant interest in building HVDC transmission to carry out transnational power exchange and deliver cheaper electricity from renewable energy sources which are located far from the load centers. This paper presents a market-based approach to solve a long-term TEP for meshed VSC-HVDC grids that connect regional markets. This is in general a nonlinear, non-convex large-scale optimization problem with high computational burden, partly due to the many combinations of wind and load that become possible. We developed a two-step iterative algorithm that first selects a subset of operating hours using a clustering technique, and then seeks to maximize the social welfare of all regions and minimize the investment capital of transmission infrastructure subject to technical and economic constraints. The outcome of the optimization is an optimal grid design with a topology and transmission capacities that results in congestion revenue paying off investment by the end the project's economic lifetime. Approximations are made to allow an analytical solution to the problem and demonstrate that an HVDC pricing mechanism can be consistent with an AC counterpart. The model is used to investigate development of the offshore grid in the North Sea. Simulation results are interpreted in economic terms and show the effectiveness of our proposed two-step approach.

Transmission management for congested power system: A review of concepts, technical challenges and development of a new methodology

Transmission networks have some constraints that should be addressed in order to ensure sufficient control to maintain the security level of a power system while maximising market efficiency. The most obvious drawback of transmission constraints is a congestion problem that becomes an obstacle to perfect competition among the market participants since it can influence spot market pricing. As the power flow violates transmission constraints, redispatching generating units is required and this will cause the price at every node to vary. This manuscript presents concepts, technical challenges and methodology for investigating an alternative solution to the redispatch mechanism and then formulates LMP scheme using an optimisation technique that may well control congestion as the main issue. The LMP scheme are varied and improved to take into account the energy price, congestion revenue, cost of losses, as well as the transmission usage tariff by utilising shift factor-based optimal power flow (SF-OPF), which is derived from the well-known DC optimal power flow (DC-OPF) model.

Optimal transmission switching: economic efficiency and market implications

Traditionally, transmission assets for bulk power flow in the electric grid have been modeled as fixed assets in the short run, except during times of forced outages or maintenance. This traditional view does not permit reconfiguration of the transmission grid by the system operators to improve system performance and economic efficiency. The current push to create a smarter grid has brought to the forefront the possibility of co-optimizing generation along with the network topology by incorporating the control of transmission assets within the economic dispatch formulations. Unfortunately, even though such co-optimization improves the social welfare, it may be incompatible with prevailing market design practices since it can create winners and losers among market participants and it has unpredictable distributional consequences in the energy market and in the financial transmission rights (FTR) market. In this paper, we first provide an overview of recent research on optimal transmission switching, which demonstrates the substantial economic benefit that is possible even while satisfying standard N−1 reliability requirements. We then discuss various market implications resulting from co-optimizing the network topology with generation and we examine how transmission switching may affect locational Marginal Prices (LMPs), i.e., energy prices, and revenue adequacy in the FTR market when FTR settlements are financed by congestion revenues.

The inherent inefficiency of simultaneously feasible financial transmission rights auctions

Empirical evidence from the New York ISO shows that the clearing prices for point-to-point congestion revenue rights, also known as financial transmission rights (FTRs), resulting from centralized auctions conducted by Independent System Operators differ significantly and systematically from the realized congestion revenues that determine the accrued payoffs of these rights. The question addressed by this paper is whether such deviations are due to price discovery errors which will eventually vanish or due to inherent inefficiencies in the auction structure. We show that even with perfect foresight of average congestion rents the clearing prices for the FTRs depend on the bid quantity and therefore may not be priced correctly in the financial transmission right (FTR) auction. In particular, we prove that quantity limits on the FTR bids may cause the auction clearing prices to differ from the bid prices. This phenomenon which is inherent in the theoretical properties of the optimization algorithm used to clear the auction, is further illustrated through numerical simulations with test systems. We conclude that price discovery alone would not remedy the discrepancy between the auction prices and the realized values of the FTRs. Secondary markets or frequent reconfiguration auctions are necessary in order to achieve such convergence.

Pareto-improving congestion pricing and revenue refunding with multiple user classes

This study investigates Pareto-improving congestion pricing and revenue refunding schemes in general transportation networks, which make every road user better off as compared with the situation without congestion pricing. We consider user heterogeneity in value of time (VOT) by adopting a multiclass user model with fixed origin–destination (OD) demands. We first prove that an OD and class-based Pareto-improving refunding scheme exists if and only if the total system monetary travel disutility is reduced. In view of the practical difficulty in identifying individual user’s VOT, we further investigate class-anonymous refunding schemes that give the same amount of refund to all user classes traveling between the same OD pair regardless of their VOTs. We establish a sufficient condition for the existence of such OD-specific but class-anonymous Pareto-improving refunding schemes, which needs information only on the average toll paid and average travel time for trips between each OD pair.

Regulated cross-border transmission investment in Europe

In a liberalized market, generation and transmission investment decisions are decoupled, so that a more elaborated grid is necessary. The European transmission grid has to ensure security of supply, facilitate the market and integrate renewables. Transmission grid investments are clearly needed, especially to increase the scarcely available cross-border transfer capacities. The regulatory framework in which these investments have to take place is discussed in this paper. It is stated that this framework does not ensure that congestion revenues are used for transmission investments that are in the long-term benefit of the market, because regulators are biased towards a short-term tariff reduction. The authors conclude that more coordination is clearly necessary, either pushed by European regulation or driven by coordinated regulatory actions. Copyright © 2006 John Wiley & Sons, Ltd.

Impact of Market Uncertainty on Congestion Revenue Right Valuation

Congestion revenue rights (CRRs) are property rights that entitle and/or obligate their holders to receive specified (possibly negative) congestion revenues. They provide price certainty for transmission customers who need to purchase open access transmission service. Auctions and bilateral transactions allocate CRRs to market participants who value the transmission rights the most. If valued correctly, CRRs would yield market signals required in valuing congested transmission facilities and inducing capital investment in the transmission sector. Financial transmission rights (FTRs) and flowgate rights (FGRs) are two specific forms of CRRs. This paper presents a simulation based approach for valuing FTRs and FGRs. Using the proposed approach, we derive the probabilistic characteristics of FTR and FGR values under market uncertainties resulting from fluctuating system loads, varying fuel prices, and other system contingencies such as unplanned transmission circuit and generator outages. A theoretical framework consisting of a multilateral-transaction model, a nonconforming electric load model, and CRR valuation models under different market structures incorporating market aforementioned uncertainties is proposed. A Monte Carlo simulation procedure is employed to obtain the distributions of FTR and FGR values. Numerical implementation of the proposed approach is illustrated on a sample test system.