Risk-oriented multi-area economic dispatch solution with high penetration of wind power generation and compressed air energy storage system

This paper investigates the risk-oriented multi-area economic dispatch (MAED) problem with high penetration of wind farms (WFs) combined with compressed air energy storage (CAES). The main objective is to help system operators to minimize the operational cost of thermal units and CAES units with an appropriate level of security through optimized WF power generation curtailment strategy and CAES charging/discharging control. In the obtained MAED model, several WFs integrated with CAES units are considered in different generation zones, and the probability to meet demand by available spinning reserve during N - 1 security contingency is characterized as a risk function. Furthermore, the contribution of CAES units in providing the system spinning reserve is taken into account in the MAED model. The proposed framework is demonstrated by a case study using the modified IEEE 40-generator system. The numerical results reveal that the proposed method brings a significant advantage to the efficient scheduling of thermal units' power generation, WF power curtailment, and CAES charging/discharging control in the power system.©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.fi=vertaisarvioitu|en=peerReviewed

Forecasting tools and probabilistic scheduling approach incorporatins renewables uncertainty for the insular power systems industry

Nowadays, the paradigm shift in the electricity sector and the advent of the smart grid, along with the growing impositions of a gradual reduction of greenhouse gas emissions, pose numerous challenges related with the sustainable management of power systems. The insular power systems industry is heavily dependent on imported energy, namely fossil fuels, and also on seasonal tourism behavior, which strongly influences the local economy. In comparison with the mainland power system, the behavior of insular power systems is highly influenced by the stochastic nature of the renewable energy sources available. The insular electricity grid is particularly sensitive to power quality parameters, mainly to frequency and voltage deviations, and a greater integration of endogenous renewables potential in the power system may affect the overall reliability and security of energy supply, so singular care should be placed in all forecasting and system operation procedures. The goals of this thesis are focused on the development of new decision support tools, for the reliable forecasting of market prices and wind power, for the optimal economic dispatch and unit commitment considering renewable generation, and for the smart control of energy storage systems. The new methodologies developed are tested in real case studies, demonstrating their computational proficiency comparatively to the current state-of-the-art

Optimization of a wind powered desalination and pumped hydro storage system

The penetration of intermittent renewable energy sources, for instances wind power, in the power system of isolated islands is limited, even when there is large potential. The wind power that cannot be directly injected in the power grid is usually curtailed. In addition, some islands need to desalinate seawater to produce fresh water, increasing the pressure on the power system, because desalination needs electricity. Nevertheless, the water scarcity problem of an island can be part of the solution of the problem of its integration of intermittent renewable energy sources. To tackle this issue, a system was proposed to use the excess wind power in desalination units and in a pumped hydro storage, resulting in an integrated power and water supply system that would minimize the wind power curtailed. This paper proposes a methodology to optimize the size and operational strategy of this wind powered desalination and pumped hydro storage system. The objective is to minimize the total annualized production costs, maximize the percentage of renewable energy sources in the total power production and minimize the wind power curtailed. To solve this optimization problem, a derivative free multiobjective optimization method (Direct MultiSearch) is used. This methodology is applied to the integrated power and water supply system proposed for the island of S. Vicente, in Cape Verde. The results show that the penetration of renewable energy sources can reach 84% with a 27% decrease of power and water production costs and 67% decrease of CO2 emissions, in relation to the values foreseen for 2020.info:eu-repo/semantics/publishedVersio

Unit Commitment Problem in Electrical Power System: A Literature Review

Unit commitment (UC) is a popular problem in electric power system that aims at minimizing the total cost of power generation in a specific period, by defining an adequate scheduling of the generating units. The UC solution must respect many operational constraints. In the past half century, there was several researches treated the UC problem. Many works have proposed new formulations to the UC problem, others have offered several methodologies and techniques to solve the problem. This paper gives a literature review of UC problem, its mathematical formulation, methods for solving it and Different approaches developed for addressing renewable energy effects and uncertainties

An MILP approach for the optimal design of renewable battery-hydrogen energy systems for off-grid insular communities

Abstract The optimal sizing of stand-alone renewable H2-based microgrids requires the load demand to be reliably satisfied by means of local renewable energy supported by a hybrid battery/hydrogen storage unit, while minimizing the system costs. However, this task is challenging because of the high number of components that have to be installed and operated. In this work, an MILP optimization framework has been developed and applied to the off-grid village of Ginostra (on the Stromboli island, Italy), which is a good example of several other insular sites throughout the Mediterranean area. A year-long time horizon was considered to model the seasonal storage, which is necessary for off-grid areas that wish to achieve energy independence by relying on local renewable sources. The degradation costs of batteries and H2-based devices were included in the objective function of the optimization problem, i.e., the annual cost of the system. Efficiency and investment cost curves were considered for the electrolyzer and fuel cell components in order to obtain a more detailed and precise techno-economic estimation. The design optimization was also performed with the inclusion of a general demand response program (DRP) to assess its impact on the sizing results. Moreover, the effectiveness of the proposed MILP-based method was tested by comparing it with a more traditional approach, based on a metaheuristic algorithm for the optimal sizing complemented with ruled-based strategies for the system operation. Thanks to its longer-term storage capability, hydrogen is required for the optimal system configuration in order to reach energy self-sufficiency. Finally, considering the possibility of load deferral, the electricity generation cost can be reduced to an extent that depends on the amount of load that is allowed to participate in the DRP scheme. This cost reduction is mainly due to the decreased capacity of the battery storage system

Energy storage systems and grid code requirements for large-scale renewables integration in insular grids

This thesis addresses the topic of energy storage systems supporting increased penetration of renewables in insular systems. An overview of energy storage management, forecasting tools and demand side solutions is carried out, comparing the strategic utilization of storage and other competing strategies. Particular emphasis is given to energy storage systems on islands, as a new contribution to earlier studies, addressing their particular requirements, the most appropriate technologies and existing operating projects throughout the world. Several real-world case studies are presented and discussed in detail. Lead-acid battery design parameters are assessed for energy storage applications on insular grids, comparing different battery models. The wind curtailment mitigation effect by means of energy storage resources is also explored. Grid code requirements for large-scale integration of renewables are discussed in an island context, as another new contribution to earlier studies. The current trends on grid code formulation, towards an improved integration of distributed renewable resources in island systems, are addressed. Finally, modeling and control strategies with energy storage systems are addressed. An innovative energy management technique to be used in the day-ahead scheduling of insular systems with Vanadium Redox Flow battery is presented.Esta tese aborda a temática dos sistemas de armazenamento de energia visando o aumento da penetração de energias renováveis em sistemas insulares. Uma visão geral é apresentada acerca da gestão do armazenamento de energia, ferramentas de previsão e soluções do lado da procura de energia, comparando a utilização estratégica do armazenamento e outras estratégias concorrentes. É dada ênfase aos sistemas de armazenamento de energia em ilhas, como uma nova contribuição no estado da arte, abordando as suas necessidades específicas, as tecnologias mais adequadas e os projetos existentes e em funcionamento a nível mundial. Vários casos de estudos reais são apresentados e discutidos em detalhe. Parâmetros de projeto de baterias de chumbo-ácido são avaliados para aplicações de armazenamento de energia em redes insulares, comparando diferentes modelos de baterias. O efeito de redução do potencial de desperdício de energia do vento, recorrendo ao armazenamento de energia, também é perscrutado. As especificidades subjacentes aos códigos de rede para a integração em larga escala de energias renováveis são discutidas em contexto insular, sendo outra nova contribuição no estado da arte. As tendências atuais na elaboração de códigos de rede, no sentido de uma melhor integração da geração distribuída renovável em sistemas insulares, são abordadas. Finalmente, é estudada a modelação e as estratégias de controlo com sistemas de armazenamento de energia. Uma metodologia de gestão de energia inovadora é apresentada para a exploração de curto prazo de sistemas insulares com baterias de fluxo Vanádio Redox

Techno-Economic modelling of hybrid renewable mini-grids for rural electrification planning in Sub-Saharan Africa

Access to clean, modern energy services is a necessity for sustainable development. The UN Sustainable Development Goals and SE4ALL program commit to the provision of universal access to modern energy services by 2030. However, the latest available figures estimate that 1.1 billion people are living without access to electricity, with over 55% living in Sub-Saharan Africa. Furthermore, 85% live in rural areas, often with challenging terrain, low income and population density; or in countries with severe underinvestment in electricity infrastructure making grid extension unrealistic. Recently, improvements in technology, cost efficiency and new business models have made mini-grids which combine multiple energy technologies in hybrid systems one of the most promising alternatives for electrification off the grid. The International Energy Agency has estimated that up to 350,000 new mini-grids will be required to reach universal access goals by 2030. Given the intermittent and location-dependent nature of renewable energy sources, the evolving costs and performance characteristics of individual technologies, and the characteristics of interacting technologies, detailed system simulation and demand modelling is required to determine the cost optimal combinations of technologies for each-and-every potential mini-grid site. Adding to this are the practical details on the ground such as community electricity demand profiles and distances to the grid or fuel sources, as well asthe social and political contexts,such as unknown energy demand uptake or technology acceptance, national electricity system expansion plans and subsidies or taxes, among others. These can all have significant impacts in deciding the applicability of a mini-grid within that context. The scope of the research and modelling framework presented focuses primarily on meeting the specific energy needs in the sub-Saharan African context. Thus, in being transparent, utilizing freely available software and data as well as aiming to be reproducible, scalable and customizable; the model aims to be fully flexible, staying relevant to other unique contexts and useful in answering unknown future research questions. The techno-economic model implementation presented in this paper simulates hourly mini-grid operation using meteorological data, demand profiles, technology capabilities, and costing data to determine the optimal component sizing of hybrid mini-grids appropriate for rural electrification. The results demonstrate the location, renewable resource, technology cost and performance dependencies on system sizing. The model is applied for the investigation of 15 hypothetical mini-grids sites in different regions of South Africa to validate and demonstrate the model’s capabilities. The effect of technology hybridization and future technology cost reductions on the expected cost of energy and the optimal technology configurations are demonstrated. The modelling results also showed that the combination of hydrogen fuel cell and electrolysers was not an economical energy storage with present day technology costs and performance. Thereafter, the model was used to determine an approximate fuel cell and electrolyser cost target curve up to the year 2030. Ultimately, any research efforts through the application of the model, building on the presented framework, are intended to bridge the science-policy boundary and give credible insight for energy and electrification policies, as well as identifying high impact focus areas for ongoing further research

A Conic Model for Electrolyzer Scheduling

The hydrogen production curve of the electrolyzer describes the non-linear and non-convex relationship between its power consumption and hydrogen production. An accurate representation of this curve is essential for the optimal scheduling of the electrolyzer. The current state-of-the-art approach is based on piece-wise linear approximation, which requires binary variables and does not scale well for large-scale problems. To overcome this barrier, we propose two models, both built upon convex relaxations of the hydrogen production curve. The first one is a linear relaxation of the piece-wise linear approximation, while the second one is a conic relaxation of a quadratic approximation. Both relaxations are exact under prevalent operating conditions. We prove this mathematically for the conic relaxation. Using a realistic case study, we show that the conic model, in comparison to the other models, provides a satisfactory trade-off between computational complexity and solution accuracy for large-scale problems

Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm

The deployment of utility-scale energy storage systems (ESSs) can be a significant avenue for improving the performance of distribution networks. An optimally placed ESS can reduce power losses and line loading, mitigate peak network demand, improve voltage profile, and in some cases contribute to the network fault level diagnosis. This paper proposes a strategy for optimal placement of distributed ESSs in distribution networks to minimize voltage deviation, line loading, and power losses. The optimal placement of distributed ESSs is investigated in a medium voltage IEEE-33 bus distribution system, which is influenced by a high penetration of renewable (solar and wind) distributed generation, for two scenarios: (1) with a uniform ESS size and (2) with non-uniform ESS sizes. System models for the proposed implementations are developed, analyzed, and tested using DIgSILENT PowerFactory. The artificial bee colony optimization approach is employed to optimize the objective function parameters through a Python script automating simulation events in PowerFactory. The optimization results, obtained from the artificial bee colony approach, are also compared with the use of a particle swarm optimization algorithm. The simulation results suggest that the proposed ESS placement approach can successfully achieve the objectives of voltage profile improvement, line loading minimization, and power loss reduction, and thereby significantly improve distribution network performance