Market design for a reliable ~100% renewable electricity system: Deliverable D3.5

Project TradeRES - New Markets Design & Models for 100% Renewable Power Systems: https://traderes.eu/about/ABSTRACT: The goal of this report is to identify in which respects the design and regulation of electricity markets needs to be improved in order facilitate a (nearly) completely decarbonized electricity system. It provides a basis for scoping the modeling analyses that are to be performed in subsequent work packages in the TradeRES project. These simulations will provide the basis for an update of this deliverable in the form of a more precise description of an all-renewable electricity market design. In this first iteration1 of deliverable 3.5, we analyze how the current design of electricity markets may fall short of future needs. Where there is a lack of certainty about the best market design choices, we identify alternative choices. Alternatives may concern a choice between policy intervention and no intervention or different intervention options. Section 2 outlines current European electricity market design and the key pieces of European legislation that underlie it. The European target model is zonal pricing with bidding zones that are defined as geographic areas within the internal market without structural congestion. That implies that within one bidding zone electricity can be traded without considering grid constraints and there are uniform wholesale prices in each zone. The main European markets are Nordpool, EPEX and MIBEL. Trading between zones in the European Price Coupling Region occurs through an implicit auction where price and quantity are computed for every hour of the next day, using EUPHEMIA, a hybrid algorithm for flowbased market coupling that is considered the best practice in Europe at this time.N/

Foundations of Infrastructure CPS

Infrastructures have been around as long as urban centers, supporting a society’s needs for its planning, operation, and safety. As we move deeper into the 21st century, these infrastructures are becoming smart – they monitor themselves, communicate, and most importantly self-govern, which we denote as Infrastructure CPS. Cyber-physical systems are now becoming increasingly prevalent and possibly even mainstream. With the basics of CPS in place, such as stability, robustness, and reliability properties at a systems level, and hybrid, switched, and eventtriggered properties at a network level, we believe that the time is right to go to the next step, Infrastructure CPS, which forms the focus of the proposed tutorial. We discuss three different foundations, (i) Human Empowerment, (ii) Transactive Control, and (iii) Resilience. This will be followed by two examples, one on the nexus between power and communication infrastructure, and the other between natural gas and electricity, both of which have been investigated extensively of late, and are emerging to be apt illustrations of Infrastructure CPS

New actor types in electricity market simulation models: Deliverable D4.4

Project TradeRES - New Markets Design & Models for 100% Renewable Power Systems: https://traderes.eu/about/ABSTRACT: The modelling of agents in the simulation models and tools is of primary importance if the quality and the validity of the simulation outcomes are at stake. This is the first version of the report that deals with the representation of electricity market actors’ in the agent based models (ABMs) used in TradeRES project. With the AMIRIS, the EMLab-Generation (EMLab), the MASCEM and the RESTrade models being in the centre of the analysis, the subject matter of this report has been the identification of the actors’ characteristics that are already covered by the initial (with respect to the project) version of the models and the presentation of the foreseen modelling enhancements. For serving these goals, agent attributes and representation methods, as found in the literature of agent-driven models, are considered initially. The detailed review of such aspects offers the necessary background and supports the formation of a context that facilitates the mapping of actors’ characteristics to agent modelling approaches. Emphasis is given in several approaches and technics found in the literature for the development of a broader environment, on which part of the later analysis is deployed. Although the ABMs that are used in the project constitute an important part of the literature, they have not been included in the review since they are the subject of another section.N/

Insurance mechanisms for the reliability of electricity supply

In the context of rapid shifts in the energy supply mix and the onset of climate change, tail risk in power systems presents an emergent threat to system reliability. Flexible resources like load control, storage and distributed energy resources are potent tools to alleviate system strains during extreme events. However, market participants need appropriate economic incentives to exploit the value of such resources. While spot prices serve as robust indicators of real-time scarcity, a complex challenge lies in translating short-term signals to long-term investment decisions. This is especially pertinent in the context of markets marked by incompleteness, and agents with pronounced aversion to risk. The financial technology of insurance is targeted at the assessment, pricing, and management of extreme and catastrophic risks. This thesis proposes the novel application of insurance contracts and risk architectures to modern electricity markets, extending existing approaches to reliability risk management. This leads to the central research question of this thesis: Can the delivery of electricity service to consumers be made more reliable through the application of insurance mechanisms? The thesis investigates this question through three main streams of research: This first stream proposes the novel application of insurance contracts and capital reserving frameworks on the procurement of strategic reserves in electricity markets. A strategic reserve is a reliability mechanism in electricity markets that seeks to contract generation capacity incremental to that incentivised by short-term spot markets, for use in times of critical supply shortage. The insurance contracts allow consumers to elect differentiated reliability preferences, and align the financial interests of the insurer with such preferences. Application to a case study suggests the potential for improved consumer and social welfare while maintaining insurer viability and solvency. The design is also robust to non-transparent market parameters such as generator risk aversion. The second stream develops a locational insurance model to value resilience in power systems exposed to high-impact low-probability common-mode events. It is demonstrated that the implementation of this scheme in a large-scale power system could reduce load losses via investment in resilient distributed energy resources. However the cost of such insurance may be expensive, and appropriate calibration of consumer expectations and preferences is important. The final stream examines the interaction between the design of contracts between central agencies and storage resources, and the operation of the resources in the market. Five principles for central agency contracting are proposed, focusing on incentive compatibility with existing spot dispatch and limiting distortions to long-term hedging markets. The principles are applied specifically to contracts with storage resources. It is demonstrated that many early designs for storage auctions may be inconsistent with the identified principles. A novel storage contract ‘yardstick’ is proposed, which is shown to align participant dispatch incentives, while maintaining revenue support

Market-based transmission congestion management using extended optimal power flow techniques

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University, 5/9/2001This thesis describes research into the problem of transmission congestion management. The causes, remedies, pricing methods, and other issues of transmission congestion are briefly reviewed. This research is to develop market-based approaches to cope with transmission congestion in real-time, short-run and long-run efficiently, economically and fairly. Extended OPF techniques have been playing key roles in many aspects of electricity markets. The Primal-Dual Interior Point Linear Programming and Quadratic Programming are applied to solve various optimization problems of congestion management proposed in the thesis. A coordinated real-time optimal dispatch method for unbundled electricity markets is proposed for system balancing and congestion management. With this method, almost all the possible resources in different electricity markets, including operating reserves and bilateral transactions, can be used to eliminate the real-time congestion according to their bids into the balancing market. Spot pricing theory is applied to real-time congestion pricing. Under the same framework, a Lagrangian Relaxation based region decomposition OPF algorithm is presented to deal with the problems of real-time active power congestion management across multiple regions. The inter/intra-regional congestion can be relieved without exchanging any information between regional ISOs but the Lagrangian Multipliers. In day-ahead spot market, a new optimal dispatch method is proposed for congestion and price risk management, particularly for bilateral transaction curtailment. Individual revenue adequacy constraints, which include payments from financial instruments, are involved in the original dispatch problem. An iterative procedure is applied to solve this special optimization problem with both primal and dual variables involved in its constraints. An optimal Financial Transmission Rights (FTR) auction model is presented as an approach to the long-term congestion management. Two types of series F ACTS devices are incorporated into this auction problem using the Power Injection Model to maximize the auction revenue. Some new treatment has been done on TCSC's operating limits to keep the auction problem linear