Financial Transmission Rights Research Articles

Congestion Risk, Transmission Rights, and Investment Equilibria in Electricity Markets

Financial instruments that help provide revenue certainty are fundamental for project finance in liberalized electricity markets. Improved management of locational risk caused by network congestion is becoming increasingly important with a growing share of production from geographically remote renewable resources. Nodal markets have financial transmission rights (FTRs) to enable participants to manage locational risk, but there is no evidence that FTRs have been used to support project finance. Through a stochastic equilibrium model in which market participants invest in production assets and trade risk, we show that long-term FTRs promote surplus-maximizing generation investments and reduce the cost of capital. Investors pair them with energy price hedges and thus protect themselves against both types of risk. Our results suggest that altering the definition and allocation of FTRs to match the needs of project finance, e.g., by enabling new generators to procure a long-term right at the time of interconnection, could help ensure a complete risk market and encourage efficient investments.

Virtual Prosumers’ P2P Transaction Based Distribution Network Expansion Planning

The deployment of prosumers with distributed energy resources (DERs) has facilitated the prosumer-centric transactive market, giving rise to the consequent necessity for the coordination between prosumers and the distribution networks. This paper proposes an incentive-based expansion planning method considering virtual peer-to-peer (P2P) transaction among prosumers, which is characterized as a tri-level planning-operation-transaction framework. Each prosumer optimizes its internal response of DERs and external P2P transaction jointly, formulating virtual P2P transaction. Under such a paradigm, the distribution company (DISCO) identifies the optimal expansion planning in the network assets, while the independent distribution system operator (IDSO) is responsible for the optimal operation of the expanded distribution networks. To derive appropriate incentives for each prosumer, the DISCO and IDSO allocate long-term investment network charges and short-term operation network charges on prosumers, along with the designed financial transmission rights coupling multiple time scales. Through such incentives, self-profit driven virtual transactions can relieve operation problems and postpone expansion planning, acting as a short-term alternative. Moreover, a risk-based approach is proposed for prosumer to flexibly change strategy according to different risk preference. Finally, results from the case study demonstrate the superiority and effectiveness of the proposed method in the collaborative application of virtual transaction in the expansion planning.

Rethinking the Role of Financial Transmission Rights in Wind-Rich Electricity Markets in the Central U.S.

Transmission congestion can cause a divergence between wholesale power prices at the individual pricing nodes where power is generated and the more-liquid trading hubs where that power is often delivered and sold. This nodal price difference is commonly referred to as the “locational basis” (or just “basis”). Because the basis varies over time, it can—if not hedged—unpredictably affect a wind plant’s revenue and/or value, which increases investor risk and potentially slows deployment. We find wind plants typically face a larger and more-negative basis than do thermal generators, and hence are more-negatively impacted by congestion. Moreover, while most thermal generators can effectively hedge basis risk by purchasing conventional fixed-volume financial transmission rights (FTRs), these fixed-volume FTRs do not effectively hedge basis risk for variable wind generation. More-effective hedging mechanisms may be required to support those generators most-impacted by congestion, and to promote continued investment in variable generation resources in congested markets.

Robust Data-Driven Sparse Estimation of Distribution Factors Considering PMU Data Quality and Renewable Energy Uncertainty - Part II: Scalability and Applications

This two-part paper proposes a data-driven, robust, and scalable sparse estimation framework of distribution factors (DFs). Part I proposes a novel Adaptive <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> -Lasso estimator with theoretically guaranteed robustness. For solving this estimator, common algorithms are not scalable to large-scale systems since they often fail to converge under parallelism. This is addressed in Part II, where a novel Online Parallel Stochastic Coordinate Descent algorithm with theoretically guaranteed scalability is proposed. It can simultaneously update massive DF estimates by stochastic parallelism with fast convergence. It also works recursively under a multi-core setting and does not need step-size tuning, which is applicable for cloud-computing-based online parallel estimation. Convergence bounds of this algorithm are theoretically proven, and its speedup and maximum parallel core number are derived. These guide practical computational resource allocation for high efficiency. The benefits of the framework are showcased in real-time market operations under locational marginal pricing (LMP) and financial transmission right (FTR) mechanisms for congestion management. Thanks to its sparsity-promoting effect, robustness, and scalability, it allows for correctly and fast solving LMPs, congestion patterns, and FTR revenues against uncertainties. Test results on IEEE 300- and European 9241-bus systems via Alibaba Cloud validate the high scalability of this algorithm and benefits of the proposed framework to system applications.

Pricing inconsistency between the futures and Financial Transmission Right markets in North America

An empirical comparison of prices for two categories of financial derivatives of the NYISO, PJM and ISO-NE power markets, namely Financial Transmission Right (FTR) and futures contracts, is performed. The objective is to assess whether these two categories of derivatives are priced consistently, as their payoffs partially overlap. Statistical metrics reveal that implied prices for the loss component of the power price, which are obtained by combining information provided by both FTR and futures prices, are more volatile than corresponding realized loss values. This contradicts the idea of a price being a probability-weighted average of possible realized values, and therefore indicates the presence of the pricing misalignment between the FTR and futures markets of the three power markets during the period covered by the data sample.

Investment and Bidding Strategies for Optimal Transmission Management Dynamics: The Italian Case

This paper explores the allocation process of Financial Transmission Rights (FTRs) in the Italian electricity market. FTRs are financial instruments allowing market participants to hedge against transmission congestion, also playing a critical role in ensuring the efficient use of the transmission system. We present a linear programming (LP) model that simulates the FTRs allocation process, taking into account the transmission capacity limits of the electric network when the total revenue is considered as the utility function. Obtained results highlight that our solution allows us to develop better investment and bidding strategies for optimal transmission management dynamics. In particular, numerical simulations show good results, with an overall MAPE of approximately 7%, indicating that the model accurately predicts the allocation of transmission rights across the network. Overall, the paper provides insights into the inner workings of the FTR allocation process in Italy, also providing improved market efficiency while increasing revenue for market participants.

Optimal Offering Strategy of GenCo With Joint Participation in FTR Auction and Day-Ahead Market Considering Virtual Bidding

Nodal price separations in Day-Ahead (DA) market caused by transmission congestion create congestion charges&#x002F;surplus that are reallocated to the market participants through the financial transmission right (FTR) auction. From a market participant&#x0027;s viewpoint, these two markets are interrelated because the revenue of market participant in FTR auction is determined based on the day-ahead locational marginal prices. Furthermore, virtual transactions which are designed to improve price convergence between the day-ahead and real-time markets can directly impact day-ahead prices. This impact through virtual transactions may be utilized by a market participant to increase its FTR value and improve its overall strategy in participating in both FTR auction and day-ahead market. To this end, this paper is the first attempt to reveal this tactic in literature and proposes an offer strategy framework for a price-maker generating company participating in both FTR auction and day-ahead market with the consideration of virtual bidding. First, the possibility of FTR value manipulation is conceptually demonstrated by placing virtual bids in the day-ahead market. Second, a two-stage bi-level offering strategy model is formulated for strategic GenCos, which is further converted to a single level optimization problem by using Karush-Kuhn-Tucker conditions and strong duality theory. Numerical tests on a 5-bus system and IEEE reliability test system (RTS) demonstrate the effectiveness and applicability of the proposed approach.

Locational Marginal Pricing for Flexibility and Uncertainty With Moment Information

The continuous growth of variable renewable integration has greatly increased uncertainty and variability in the power system, resulting in unprecedentedly high demand for flexibility. Recently, there has been much attention in the power industry to manage the flexibility and uncertainty via market mechanisms. This paper presents a novel approach to jointly clearing energy, reserve, and uncertainty with moment information based on distributionally robust chance constraints (DR-CC). Locational marginal prices (LMP) are derived for both energy and reserve. Uncertainty is modeled with statistical moments of historical forecast errors, and uncertainty marginal prices (UMP) are defined to reflect the marginal cost of uncertainty following the cost-causation principle. The congestion cost of reserve trading is explicitly modelled, and is shown to fully cover financial transmission right (FTR) underfunding. We show that the proposed mechanism guarantees revenue adequacy and provides appropriate incentives for efficient operation and investment. Case studies are carried out to illustrate the impact of the proposed market scheme, and its feasibility is demonstrated on a testbed system based on a real-world 1934-bus grid.

Peer-to-peer energy trading market considering renewable energy uncertainty and participants’ individual preferences

With the development of renewable energy resources, peer-to-peer (P2P) energy trading is becoming more and more popular on the user side. However, the prosumers’ uncertain fluctuation and specific preference requirements have brought new challenges to the traditional market mechanism. Therefore, we propose a novel pricing mechanism, including preference marginal price (PMP), uncertainty marginal price (UMP), and local marginal price (LMP) in this paper. These pricing strategies can overcome the uncertainty problems in the current market and credit the reserve resources that ensure flexible energy delivery. We embed these pricing strategies into the robust economic dispatch model and employ a column-and-constraints generation (CCG) algorithm to solve the model. Among these prices, local marginal prices are used to charge energy consumption and financial transmission right (FTR) credits. Uncertainty marginal prices are charged for the reserve resources and financial transmission right holders. Preference marginal prices are charged from the prosumers with specific welfare requirements to credit the reserve resources, financial transmission right holders and energy producers. The market equilibrium and revenue adequacy are proven in the appendix to verify the effectiveness of the proposed pricing mechanism. In the simulation section, the total operation costs and marginal price payments increase with the rise of uncertainty level and preference requirement degree. The financial transmission right underfunding problem is verified in a three-bus system. The underfunding can be covered by congestion funds collected from uncertainty and preference marginal prices.

Mitigation of transmission line jamming by price intrusion technique in competitive electricity market

ABSTRACT In the past years of the electric market, very big corporation companies enjoyed domination or monopoly and takes complete responsibility for generating the electric power. In the new-age market electricity grid faces several techno-commercial challenges like power outage, conductor snag, equipment rundown, transmission congestion, financial constraint, price settlement issue, etc, so this cause transfer of generated electricity from generating station to load becomes a challenge. Also, transmission jamming or congestion is an issue that leads to catastrophe if not mitigated. Therefore to avoid such issues different techno-financial methods are adopted in a particular electricity zone with a large network. In this paper, we adopted an innovative technique to control the electricity transfer limit. Here an analytic tool based on the price-sensitive algorithm is developed to determine a suitable combination of Financial Transmission Rights (FTR) and Location-based low prices with curtailments in a competitive electricity market. The significant objective of this technique is to minimise the dispatch of low-cost generators and overall operational expenses thereby mitigating the traffic issue in a particular load node or zone. Finally, the transmission congestion mitigation is discussed with price sensitivity technique and with a proper financial mechanism like FTR with location pricing in a particular zone.

Financial transmission and storage rights

The paper presents concepts of Financial Transmission Rights (FTRs) and Financial Storage Rights (FSRs) as key market concepts for alleviating congestion issues in transmission networks. These instruments are in place in markets where prices differ depending on the location/node due to congestions. They serve as a tool for transmission system operators TSO (or independent system operators; ISOs) for eliminating congestions by remunerating entities who make it possible. The paper further discusses different aspects of FTRs, which are traditional financial instruments used to hedge the risk of high cost occurrence associated with transmission congestion. By owning and trading with FTRs, through auction or via bilateral contracts, market participants can gain additional profit. More variable and uncertain power system environment, characterized by high penetration of renewable energy sources (RES), creates potential for storage units to assist TSO/ISO in maximizing social welfare through FSR. As storage has the capability to move energy in time, it can alleviate transmission lines congestion and create profit through intertemporal arbitrage (by load shifting and peak shaving) improving return rate of its investment. These concepts are additionally explained by intuitive examples showing how, when congestion occurs and TSO/ISO awards market participants who own transmission and storage rights, price volatility is reduced.

An integrated theory of dispatch and hedging in wholesale electric power markets

The literature on optimal dispatch of wholesale power systems implicitly assumes that market participants are risk-neutral. But, in practice, most wholesale electricity market participants behave as though they are risk averse, seeking to insulate themselves from the market risks they face. In this context, achieving the overall social-welfare maximum requires simultaneously finding both the optimal dispatch and optimal hedging arrangements. Assuming that market participants have mean–variance preferences, we show that the dispatch task can be separated from the hedging task. We show how market participants can achieve a perfect hedge by forming a portfolio of inter-temporal hedge contracts. Departing from the previous literature, we assume the system operator is risk averse. We show how the system operator can achieve a perfect hedge using a portfolio of inter-nodal hedging instruments which we refer to as generalised Financial Transmission Rights. The total risk experienced by market participants when optimally hedged is equal to the variation in the total surplus or total economic welfare. This approach therefore leads naturally to a form of merchant transmission investment where network upgrade decisions are carried out by a coalition of risk-bearers in the market. In addition, we propose a natural extension in which transmission network operators provide a form of insurance against network outages, and face the correct social incentive for avoiding network outages. This approach resolves a number of outstanding issues in the economic analysis of power markets.

Price Formation in Auctions for Financial Transmission Rights

Financial Transmission Rights (FTRs) are financial derivatives in wholesale electricity markets that are sold in auctions. The revenue collected from FTR auctions is passed through to electricity customers to reimburse them for transmission congestion payments they make in the spot energy market. On average, electricity customers’ congestion payments greatly exceed auction reimbursements in electricity markets across the United States. We study the issue of auction revenue deficiency through the lens of Auction Revenue Rights (ARRs), which is the predominant mechanism used in U.S. electricity markets to distribute auction revenue to electricity customers. We demonstrate how the ARR process influences fundamental supply conditions in the FTR auction market and show how divergent auction equilibria emerge under different ARR decision-making regimes. Using market data from PJM, we find empirical evidence that variation in ARR management strategies helps explain differences between an FTR’s auction price and its realized ex post value.

Electricity market design and implementation in the presence of asymmetrically informed strategic producers and consumers: A surrogate optimization-based mechanism

We consider electricity networks where the agents (producers and consumers) are strategic and possess asymmetric information about the networks’ status. The network model accounts for power losses, line congestion, and financial transmission rights (FTRs). We propose a mechanism (a set of rules for energy production and consumption) that takes into account the network model, the agents’ strategic behavior and their informational asymmetries, and has the following properties at all Nash equilibria of the game induced by it: (i) it is budget balanced (the sum of taxes received by the agents and the sum of subsidies paid to the agents is equal to zero); (ii) it implements the optimal power flow (OPF) dispatch (equivalently it implements the social welfare maximizing dispatch); (iii) it is price efficient (the price received per unit of energy production is equal to the price paid per unit of energy consumption, and they are both equal to the price corresponding to the OPF dispatch); (iv) it is individually rational (the strategic agents voluntarily participate in the mechanism). We also propose a tâtonnement-process (an algorithm), based on a best-estimate method, and prove that it converges to a Nash equilibrium of the game induced by the proposed mechanism. The allocations (energy production and consumption) resulting at each step of the tâtonnement-process are a feasible solution of the OPF problem.

Carbon Trading Analysis and Impacts on Economy in Market-to-Market Coordination With Higher PV Penetration

This work has dealt with a market-to-market coordination (M2M) with higher photovoltaic (PV) penetrations in a market. Recent developments of renewable penetrations in the electricity grid have caused excess power generation during the peak hours of availability and low demand, i.e., during mid-day. Financial analysis, i.e., generation costs, locational marginal prices, and financial transmission rights along with carbon trading in M2M using different interconnection topologies have been analyzed. Carbon trading agreements allow for the trade of credits to emit CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> or tax the CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emissions comprising international agreements intended to cut down the total greenhouse gases. The obtained test results show that the direct interconnections of identified PV units to identified load buses have provided a better economy and have saved higher carbon emissions for the M2M interconnections.

Data-driven financial transmission right scenario generation and speculation

This paper proposes a data-driven framework to solve the financial transmission right (FTR) portfolio construction problem from the perspective of a speculator. FTR speculation is modeled as a stochastic programming problem in which uncertainty comes from the price spread across different pricing nodes over a certain holding period. Since it is difficult to model and forecast the joint distribution of prices for typical electricity markets with thousands of pricing nodes, k-means clustering with network congestion patterns is first used to help focus on important nodes and reduce the problem size. Then, a quantile regression (QR)-based method is proposed to predict the conditional distribution of average nodal prices. A Gaussian copula is further used to construct the joint conditional distribution of average nodal prices. The proposed method is tested on real market data obtained from the southwest power pool (SPP). The results show that the method has a steady performance in both node selection and price scenario generation and outperforms state-of-art methods, including copula-GARCH and truncated skew-t distributions.

Research on the impact of financial transmission rights on transmission expansion: A system dynamics model

With the development of the power market, the traditional transmission congestion management method of using a power generation plan is no longer applicable, and congestion management using financial transmission rights (FTRs) is becoming a trend. However, after the introduction of FTRs, the profit from transmission lines changes, and those changes affect the expansion of and investment in transmission lines. Therefore, this paper constructs a system dynamics analysis model and presents specific calculation methods and a case analysis. Load growth, construction time, congestion, the step nature of the bid from generating units, and relative changes in the locational marginal prices (LMPs) at the sink and source nodes under the expansion and non-expansion scenarios are considered for a simulation calculation of net present value of transmission expansion project. Sensitivity analyses of factors such as generator bid prices, transmission expansion costs, the proportion of expansion capacity to transmission congestion, and the market maturity of FTRs are analysed. The results show that decision-making on the basis of transmission expansion investment in combination with FTRs is feasible and such decision-making can reflect the value of transmission expansion via the market, which conforms to market rules. That decision-making method is very important for the marketisation of power transmission.

Financing costs and barriers to entry in Australia’s electricity market

PurposeThis paper aims to provide investors’ views on financing costs and barriers to entry into the electricity generation sector, with a focus on investors’ views on potential impacts on cost of capital from adopting nodal pricing and financial transmission rights (FTRs). The implications for policymakers and policy reforms are also discussed in detail.Design/methodology/approachSurvey-based data collection of investors and developers in electricity generation, consisting of multiple choice questions from a closed list of discrete choices, binary-choice questions, and questions with free-text/open-ended answers.FindingsAcross survey respondents, weighted-average cost of capital (WACCs) were broadly unchanged over 2019, with increases for undiversified/non-integrated participants offset by decreases for horizontally integrated participants. Cost of equity has risen, whereas cost of debt has fallen. Nodal pricing-cum-FTRs were estimated to increase WACCs by 150–200 basis points p.a. (15–20%), reflecting concerns around the firmness of FTRs and ability to automatically access intraregional settlement residues.Research limitations/implicationsThese findings have energy policy implications, namely, the need to consider the interaction between economic theory and real-world financing models when designing and implementing fundamental energy sector reforms.Practical implicationsThe need to consider implementation and transitional issues (e.g. grandfathering of existing rights, focusing on reducing the largest barriers to entry) is associated with implementing nodal pricing.Originality/valueUnique set of survey questions and insights that have not previously been addressed in an Australian context; what-if analysis not previously done in an Australian context

Long Term Interconnection, Transmission Rights and Renewable Deployment

Long-term transmission rights promotes competition, fosters investment of new entrants facilitating, in this way, the efficient renewable deployment across the EU member states, and helps the efficient use of interconnectors. However, EU regulations only require long-term transmission rights of up to one-year term. The lack of longer term transmission rights appears to be inconsistent with the twin EU goals of electricity markets integration and ambitious renewable target. Other countries experiences show that longer term transmission rights are viable and proved to be important for promoting investment efficiency and market competition. In addition, longer term financial transmission rights provides information about the need of interconnection investment.

Generalized FTRs for hedging inter-nodal pricing risk

tIn liberalised wholesale power markets, risk averse market participants seek to enter into hedge contracts referenced to their local pricing node to offset the price and volume risks they face. In typical power markets, a range of inter-temporal hedge products emerge to meet these needs, such as swaps, caps, or load-following hedges. But some market participants also face risks from trading across pricing locations. To facilitate the hedging of these risks, many liberalised wholesale power markets make available an inter-nodal hedging instrument known as fixed-volume Financial Transmission Rights (FTRs). But, with the increasing penetration of intermittent and peaking generation, very few market participants trade in a fixed volume of electricity; most market participants cannot effectively hedge their inter-nodal pricing risks using fixed-volume instruments. To solve this problem, we propose a generalization of the concept of FTRs. Specifically, we propose that for each conventional hedge contract traded in the market, such as a Cap or Floor, a matching generalized Financial Transmission Right is made available to the market. We show that traders can form a portfolio of these generalized FTRs (G-FTRs) which matches the supply curve of a generator or the demand curve of a load. We show that, given access to a full range of G-FTRs, traders can offer generators, loads, and the system operator the hedge contracts they need to fully insulate themselves from all risk while taking the market risk on themselves. This approach offers the potential for a substantial improvement in the effectiveness of hedging of inter-nodal pricing risk in liberalised wholesale electricity markets.