On optimal participation in the electricity markets of wind power plants with battery energy storage systems

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/The recent cost reduction and technological advances in medium- to large-scale battery energy storage systems (BESS) makes these devices a true alternative for wind producers operating in electricity markets. Associating a wind power farm with a BESS (the so-called virtual power plant (VPP)) provides utilities with a tool that converts uncertain wind power production into a dispatchable technology that can operate not only in spot and adjustment markets (day-ahead and intraday markets) but also in ancillary services markets that, up to now, were forbidden to non-dispatchable technologies. What is more, recent studies have shown capital cost investment in BESS can be recovered only by means of such a VPP participating in the ancillary services markets. We present in this study a multi-stage stochastic programming model to find the optimal operation of a VPP in the day-ahead, intraday and secondary reserve markets while taking into account uncertainty in wind power generation and clearing prices (day-ahead, secondary reserve, intraday markets and system imbalances). A case study with real data from the Iberian electricity market is presented.Peer ReviewedPostprint (author's final draft

Optimized Energy Management Strategy for Wind Plants with Storage in Energy and Reserve Markets

This paper addresses the joint operation of wind plants with energy storage systemsin multiple markets to increase the value of wind energy from an economic and technical point of view. The development of an optimized energy management allows scheduling the wind generation in energymarkets, as well as contributing to the system stability through the joint participation in frequency ancillary services. The market optimization maximizes market revenuesconsidering overallstoragecosts, while avoidingenergy imbalancesand market penalties. Moreover, wind power fluctuations, forecast errors and real-time reserverequirementsare controlledby the energy storagesystem and managed afterward through the participation in continuous intraday market. Furthermore, model predictive control approach enables a high compliance of reserve requirementsand a hugereduction of energy imbalancesin real-time operation. Different energy storagecapacities are selected in order to evaluate theircost-effectiveness enhancing the wind plant operation underthe considered study case.This work was partially supported by the Basque Government under Project Road2DC (ELKARTEK Research Program KK-2018/00083)

Optimized battery sizing for merchant solar PV capacity firming in different electricity markets

Comunicació presentada a IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society (Lisbon, Portugal 14-17 Oct. 2019)This work analyses the minimum energy capacity requirements to be demanded to battery energy storage systems used in megawatt-range merchant solar PV plants to grant capacity firming. The operation of such a plant is simulated (with a 2-minute time step, at three different locations of the Iberian Peninsula, and for different battery sizes) after solving a quadratic programming optimization problem. The control algorithm takes into account the irradiance forecast and the intraday electricity market configuration, which presents certain peculiarities in the Iberian region with regard to other European markets. The analysis has been performed in an annual basis and current irradiance measured values have been used

Emission-aware Energy Storage Scheduling for a Greener Grid

Reducing our reliance on carbon-intensive energy sources is vital for reducing the carbon footprint of the electric grid. Although the grid is seeing increasing deployments of clean, renewable sources of energy, a significant portion of the grid demand is still met using traditional carbon-intensive energy sources. In this paper, we study the problem of using energy storage deployed in the grid to reduce the grid's carbon emissions. While energy storage has previously been used for grid optimizations such as peak shaving and smoothing intermittent sources, our insight is to use distributed storage to enable utilities to reduce their reliance on their less efficient and most carbon-intensive power plants and thereby reduce their overall emission footprint. We formulate the problem of emission-aware scheduling of distributed energy storage as an optimization problem, and use a robust optimization approach that is well-suited for handling the uncertainty in load predictions, especially in the presence of intermittent renewables such as solar and wind. We evaluate our approach using a state of the art neural network load forecasting technique and real load traces from a distribution grid with 1,341 homes. Our results show a reduction of >0.5 million kg in annual carbon emissions -- equivalent to a drop of 23.3% in our electric grid emissions.Comment: 11 pages, 7 figure, This paper will appear in the Proceedings of the ACM International Conference on Future Energy Systems (e-Energy 20) June 2020, Australi

Development of optimal energy management and sizing strategies for large-scale electrical storage systems supporting renewable energy sources.

284 p.El desarrollo e integración de las fuentes de energía renovable (RES) conducirá a un futuro energético más sostenible. Las plantas renovables deberán mejorar su participación y operación a través de los mercados de electricidad de una manera más controlada y segura. Además, el diseño actual del mercado está cambiando para permitir una participación inclusiva en mercados de flexibilidad. En este contexto, los sistemas de almacenamiento de energía (ESS) se consideran una de las tecnologías flexibles clave que pueden apoyar la operación de las energías renovables, mediante servicios como: 1) control de la potencia generada, 2) mejora de los errores de predicción, y 3) provisión de servicios auxiliares de regulación de frecuencia. Sin embargo, el desarrollo del almacenamiento ha sido frenado también por sus altos costos. Por lo tanto, esta tesis doctoral aborda el tema del ¿Desarrollo de estrategias óptimas de gestión y dimensionamiento de los sistemas de almacenamiento eléctrico a gran escala como apoyo a fuentes de energía renovable¿, con el objetivo de desarrollar una metodología con una perspectiva global, mediante una estrategia de gestión de energía avanzada (EMS) que aborda la gestión de activos (RES + ESS) a largo plazo y por otro lado, el cálculo del dimensionamiento y operación del almacenamiento a corto plazo (en la operación en tiempo real), para asegurar un marco adecuado que permita evaluar la rentabilidad de la integración del almacenamiento en aplicaciones conectadas a la red. La estrategia de gestión de energía propuesta es validada a través de dos casos de estudio: una planta renovable individual (eólica o solar) con almacenamiento, y un porfolio de renovables y almacenamiento

Development of optimal energy management and sizing strategies for large-scale electrical storage systems supporting renewable energy sources.

284 p.El desarrollo e integración de las fuentes de energía renovable (RES) conducirá a un futuro energético más sostenible. Las plantas renovables deberán mejorar su participación y operación a través de los mercados de electricidad de una manera más controlada y segura. Además, el diseño actual del mercado está cambiando para permitir una participación inclusiva en mercados de flexibilidad. En este contexto, los sistemas de almacenamiento de energía (ESS) se consideran una de las tecnologías flexibles clave que pueden apoyar la operación de las energías renovables, mediante servicios como: 1) control de la potencia generada, 2) mejora de los errores de predicción, y 3) provisión de servicios auxiliares de regulación de frecuencia. Sin embargo, el desarrollo del almacenamiento ha sido frenado también por sus altos costos. Por lo tanto, esta tesis doctoral aborda el tema del ¿Desarrollo de estrategias óptimas de gestión y dimensionamiento de los sistemas de almacenamiento eléctrico a gran escala como apoyo a fuentes de energía renovable¿, con el objetivo de desarrollar una metodología con una perspectiva global, mediante una estrategia de gestión de energía avanzada (EMS) que aborda la gestión de activos (RES + ESS) a largo plazo y por otro lado, el cálculo del dimensionamiento y operación del almacenamiento a corto plazo (en la operación en tiempo real), para asegurar un marco adecuado que permita evaluar la rentabilidad de la integración del almacenamiento en aplicaciones conectadas a la red. La estrategia de gestión de energía propuesta es validada a través de dos casos de estudio: una planta renovable individual (eólica o solar) con almacenamiento, y un porfolio de renovables y almacenamiento

Towards near 100% renewable power systems: Improving the role of distributed energy resources using optimization models

The envisioned near 100 % renewable Power Systems, crucial in attaining the sustainability goals aspired by society, will call for the active and multifaceted participation of all the actors involved in the energy systems. Time-varying renewable energy systems (vRES), such as solar photovoltaic (PV) and wind, will play a decisive role in meeting the ambitious renewable targets. This is due to the large availability of natural resources and the rapid decrease in investment costs observed in the last two decades. In fact, most of the scenarios to achieve near 100% RES in Europe strongly rely on these two energy sources. However, the high temporal and spatial variability of the power generated by these technologies represents a challenge for preserving the high-security standards of supply, quality of service, and the robustness of current power systems, especially with the foreseen contributions from vRES. With an emphasis on the vital role these renewable technologies play in this process, this work aims to develop new methods and tools that may assist different players in different stages of this transition. The three leading contributions are: 1. A Multiyear Expansion-Planning Optimization Method (MEPOM) to be used in the planning processes carried out by system operators and governmental entities. 2. An Optimal Design and Sizing of Hybrid Power Plants (OptHy) decision-support tool to be used in accessing investment decisions and other managing actions led by renewable power plant owners and investors. 3. A Decision-aid Algorithm for Market Participation and Optimal Bidding Strategy (OptiBID) that market agents may adopt to operate and value their renewable energy assets in the electricity markets

Review of trends and targets of complex systems for power system optimization

Optimization systems (OSs) allow operators of electrical power systems (PS) to optimally operate PSs and to also create optimal PS development plans. The inclusion of OSs in the PS is a big trend nowadays, and the demand for PS optimization tools and PS-OSs experts is growing. The aim of this review is to define the current dynamics and trends in PS optimization research and to present several papers that clearly and comprehensively describe PS OSs with characteristics corresponding to the identified current main trends in this research area. The current dynamics and trends of the research area were defined on the basis of the results of an analysis of the database of 255 PS-OS-presenting papers published from December 2015 to July 2019. Eleven main characteristics of the current PS OSs were identified. The results of the statistical analyses give four characteristics of PS OSs which are currently the most frequently presented in research papers: OSs for minimizing the price of electricity/OSs reducing PS operation costs, OSs for optimizing the operation of renewable energy sources, OSs for regulating the power consumption during the optimization process, and OSs for regulating the energy storage systems operation during the optimization process. Finally, individual identified characteristics of the current PS OSs are briefly described. In the analysis, all PS OSs presented in the observed time period were analyzed regardless of the part of the PS for which the operation was optimized by the PS OS, the voltage level of the optimized PS part, or the optimization goal of the PS OS.Web of Science135art. no. 107

Forecast Error Sensitivity Analysis for Bidding in Electricity Markets with a Hybrid Renewable Plant Using a Battery Energy Storage System

Deep integration of renewable energies into the electricity grid is restricted by the problems related to their intermittent and uncertain nature. These problems affect both system operators and renewable power plant owners since, due to the electricity market rules, plants need to report their production some hours in advance and are, hence, exposed to possible penalties associated with unfulfillment of energy production. In this context, energy storage systems appear as a promising solution to reduce the stochastic nature of renewable sources. Furthermore, batteries can also be used for performing energy arbitrage, which consists in shifting energy and selling it at higher price hours. In this paper, a bidding optimization algorithm is used for enhancing profitability and minimizing the battery loss of value. The algorithm considers the participation in both day-ahead and intraday markets, and a sensitivity analysis is conducted to check the profitability variation related to prediction uncertainty. The obtained results highlight the importance of bidding in intraday markets to compensate the prediction errors and show that, for the Iberian Electricity Market, the uncertainty does not significantly affect the final benefits

Benefits of demand-side response in providing frequency response service in the future GB power system

The demand for ancillary service is expected to increase significantly in the future Great Britain (GB) electricity system due to high penetration of wind. In particular, the need for frequency response, required to deal with sudden frequency drops following a loss of generator, will increase because of the limited inertia capability of wind plants. This paper quantifies the requirements for primary frequency response and analyses the benefits of frequency response provision from demand-side response (DSR). The results show dramatic changes in frequency response requirements driven by high penetration of wind. Case studies carried out by using an advanced stochastic generation scheduling model suggest that the provision of frequency response from DSR could greatly reduce the system operation cost, wind curtailment, and carbon emissions in the future GB system characterized by high penetration of wind. Furthermore, the results demonstrate that the benefit of DSR shows significant diurnal and seasonal variation, whereas an even more rapid (instant) delivery of frequency response from DSR could provide significant additional value. Our studies also indicate that the competing technologies to DSR, namely battery storage, and more flexible generation could potentially reduce its value by up to 35%, still leaving significant room to deploy DSR as frequency response provider