Investigating the Impact of External Demand Response Flexibility on the Market Power of Strategic Virtual Power Plant

In this paper, a decision-making framework is proposed for a virtual power plant (VPP) to participate in day-ahead (DA) and regulating market (RM) considering internal demand response (IDR) flexibility. In the proposed model, a DR exchange market (DRXM) is also introduced to cover deviations of uncertain resources and decrease VPP’s imbalance penalties in the RM. The VPP can optimize its procurement expenditures by providing DR services from both IDR providers and DRXM. A market inefficiency index (MII) is defined to analyze the effect of trading energy in the DRXM on the market power of the VPP. The proposed model is formulated as a bi-level problem, in which at the upper level, the VPP maximizes its profit while at the lower level, the distribution system operator (DSO) strives to clear both DA and RM markets to maximize social welfare. The proposed problem is nonlinear and converted into a linear single-level problem through Karush-Kuhn-Tucker (KKT) optimality conditions and duality theory. The simulation results show that in high external demand response (EDR) participants, the expected profit of the VPP augments about 3% which is a substantial value for the one-day scheduling horizon. Furthermore, by providing EDR services, MII reduces which implies the EDRs preserve their economic surplus.©2022 Authors. Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/fi=vertaisarvioitu|en=peerReviewed

Estimación del costo de venta de energía eléctrica de una planta de energía virtual, basado en la elasticidad de la demanda aplicando política de pico crítico

En el presente documento se desarrolla un análisis de costos de energía eléctrica, considerando factores importantes como excedentes y generación de electricidad; se incluyen los parámetros de costos fijos y costos variables que servirán para encontrar los costos totales de generación de electricidad; por otro lado, se detallan modelos matemáticos de diferentes tecnologías de generación eléctrica y definiciones que engloban la metodología implementada. La gestión de las fuentes de generación se realiza por medio de una planta de energía virtual, ya que esta tiene la capacidad de administrar eficientemente los recursos; para el análisis se estudiará dos escenarios de fuentes de generación hidráulica y térmica. Adicionalmente, se obtendrá la estimación de costos de electricidad de las fuentes de generación empleadas, tomando en cuenta los parámetros de costos de generación. Para mejorar la eficiencia se implementa un programa de respuesta a la demanda y comparaciones de costos de generación de las fuentes analizadas.In this document an analysis of electrical energy costs is developed, considering important factors such as surpluses and electricity generation; The parameters of fixed costs and variable costs are included that will serve to find the total costs of electricity generation; on the other hand, mathematical models of different electricity generation technologies and definitions that encompass the implemented methodology are detailed. The management of generation sources is carried out by means of a virtual power plant, since it can efficiently manage resources; For the analysis, two scenarios of hydraulic and thermal generation sources will be studied. Additionally, the estimate of electricity costs of the generation sources used will be obtained, considering the generation cost parameters. To improve efficiency, a demand response program is implemented, and generation cost comparisons of the sources analyzed are implemented

Congestion Management by Applying Co-operative FACTS and DR program to Maximize Renewables

This research proposes an incremental welfare consensus method based on flexible alternating current transmission systems (FACTS) and demand response (DR) programs to control transmission network congestion in order to increase the penetration of wind power. The locational marginal prices are used as input by the suggested model to control the FACTS device and DR resources. In order to do this, a cutting-edge two-stage market clearing system is created. In the first stage, participants bid on the market with the intention of maximizing their profits, and the ISO clears the market with the goal of promoting societal welfare. The second step involves the execution of a generation re-dispatch issue in which incentive-based DR and FACTS device controllers are optimally coordinated to reduce the rescheduling expenses for generating firms. Here, a static synchronous compensator and a series capacitor operated by a thyristor are used as two different forms of FACTS devices. A case study on the modified IEEE one-area 24-bus RTS system is then completed. The simulation results show that the suggested interactive DR and FACTS model not only reduces system congestion but also makes the system more flexible so that it can capture as much wind energy as feasible.Comment: 23 pages, 8 figures, 8 table

Local Market Mechanisms: how Local Markets can shape the Energy Transition

Europe has embarked on a journey towards a zero-emission system, with the power system at its core. From electricity generation to electric vehicles, the European power system must transform into an interconnected, intelligent network. To achieve this vision, active user participation is crucial, ensuring transparency, efficiency, and inclusivity. Thus, Europe has increasingly focused on the concept of markets in all their facets. This thesis seeks to answer the following questions: How can markets, often considered abstract and accessible only to high-level users, be integrated for end-users? How can market mechanisms be leveraged across various phases of the electrical system? Why is a market- driven approach essential for solving network congestions and even influencing planning? These questions shape the core of this research. The analysis unfolds in three layers, each aligned with milestones leading to 2050. The first explores how market mechanisms can be integrated into system operator development plans, enhancing system resilience in the face of changes. In this regard, this step addresses the question of how a market can be integrated into the development plans of a network and how network planning can account for uncertainties. Finally, the analysis highlights the importance of sector coupling in network planning, proposing a study in which various energy vectors lead to a multi-energy system. According to the roadmap to 2030, this layer demonstrates how markets can manage several components of the gas and electrical network. Finally, even though the robust optimisation increases the final cost in the market, it allows to cover the system operator from uncertainties. The second step delves into the concept of network congestion. While congestion management is primarily the domain of operators, it explores how technical and economic collaboration between operators and system users, via flexibility markets, can enhance resilience amid demand uncertainties and aggressive market behaviours. In addition to flexibility markets, other congestion markets are proposed, some radically different, like locational marginal pricing, and others more innovative, such as redispatching markets for distribution. Building upon the first analysis, this section addresses questions of how various energy vectors can be used not only to meet demand but also to manage the uncertainties associated with each resource. Consequently, this second part revisits the concept of sector coupling, demonstrating how various energy vectors can be managed through flexibility markets to resolve network congestion while simultaneously handling uncertainties related to different vectors. The results demonstrate the usefulness of the flexibility market in managing the sector coupling and the uncertainties related to several energy vectors. The third and most innovative step proposes energy and service markets for low-voltage users, employing distributed ledger technology. Since this step highlights topics that are currently too innovative to be realized, this third section offers a comparative study between centralised and decentralised markets using blockchain technology, highlighting which aspects of distributed ledger technology deserve attention and which aspects of low-voltage markets need revision. The results show that the blockchain technology is still in the early stage of its evolution, and several improvements are needed to fully apply this technology into real-world applications. To sum up, this thesis explores the evolving role of markets in the energy transition. Its insights are aimed at assisting system operators and network planners in effectively integrating market mechanisms at all levels of

Forecasting and Risk Management Techniques for Electricity Markets

This book focuses on the recent development of forecasting and risk management techniques for electricity markets. In addition, we discuss research on new trading platforms and environments using blockchain-based peer-to-peer (P2P) markets and computer agents. The book consists of two parts. The first part is entitled “Forecasting and Risk Management Techniques” and contains five chapters related to weather and electricity derivatives, and load and price forecasting for supporting electricity trading. The second part is entitled “Peer-to-Peer (P2P) Electricity Trading System and Strategy” and contains the following five chapters related to the feasibility and enhancement of P2P energy trading from various aspects