Enhancing the integration of renewable power generation from wind and solar into the traditional power network requires the mitigation of the vulnerabilities affecting the grid as a result of the intermittent nature of these resources. Variability and ramp events in power output are the key challenges to the system operators due to their impact on system balancing, reserves management, scheduling, and commitment of generation units. This book presents development of energy management system for renewable power generation (EMSRPG) tool that aims to achieve power-dispatching strategies based on forecasting renewable energy resources outputs to guarantee optimal dispatch of hybrid wind-solar photovoltaic power systems (HWSPS). The key selling points of the book include the following: Renewable energy management in modern and future smart power systems Energy management systems Modeling and simulations using a real-time digital simulator (RTDS) High penetration level of renewable energy sources Case studies based on Oman’s power systems and other power grids This book discusses the challenges of integrating renewable resources, including low inertia systems, hosting capacity limitations of existing power systems, and weak grids. It further examines the detailed topologies, operation principles, recent developments in control techniques, and stability of power systems with a large scale of renewables. Finally, it presents case studies of recent projects from around the world where dispatchable power plant techniques are used to enhance power system operation.
Standalone (off-grid) renewable energy systems supply electricity in places where there is no access to a standard electrical grid. These systems may include photovoltaic generators, wind turbines, hydro turbines or any other renewable electrical generator. Usually, this kind of system includes electricity storage (commonly lead-acid batteries, but also other types of storage can be used). In some cases, a backup generator (usually powered by fossil fuel, diesel or gasoline) is part of the hybrid system. The modelling of the components, the control of the system and the simulation of the performance of the whole system are necessary to evaluate the system technically and economically. The optimization of the sizing and/or the control is also an important task in this kind of system.
Focused on renewable energy systems and the development of information and communication technologies (ICTs) for their integration in smart grids, this book presents recent advances and methods that help to ensure that power generation from renewable sources remains stable, that power losses are minimized, and that the reliable functioning of these power generation units is maintained. The book highlights key topics and technologies for renewable energy systems including the intelligent control of power generators, power electronics that connect renewable power generation units to the grid, and fault diagnosis for power generators and power electronics. In particular, the following topics are addressed: • Modeling and control of power generators (PMSGs, DFIGs); • Modeling and control of power electronics (converters, inverters); • Modeling and fault diagnosis of the transmission and distribution Grid; and • Modelling and control of distributed power generation units (interconnected synchronous generators or photovoltaic units). Because of the above coverage, members of the wider engineering community will find that the nonlinear control and estimation methods presented provide essential insights into the functioning of renewable energy power systems, while the academic community will find the book a valuable textbook for undergraduate or graduate courses on renewable energy systems.
Nowadays, power production, reliability, quality, efficiency and penetration of renewable energy sources are amongst the most important topics in the power systems analysis. The need to obtain optimal power management and economical dispatch are expressed at the same time. The interest in extracting an optimum performance minimizing market clearing price (MCP) for the consumers and provide better utilization of renewable energy sources has been increasing in recent years. Due to necessity of providing energy balance while having the fluctuations in the load demand and non-dispatchable nature of renewable sources, implementing an energy management system (EMS) is of great importance in Microgrids (MG). The appearance of new technologies such as energy storage (ES) has caused increase in the effort to present new and modified optimization methods for power management. Precise prediction of renewable energy sources power generation can only be provided with small anticipation. Hence, for increasing the efficiency of the presented optimization algorithm in large-dimension problems, new methods should be proposed, especially for short-term scheduling. Powerful optimization methods are needed to be applied in such a way to achieve maximum efficiency, enhance the economic dispatch as well as provide the best performance for these systems. Thus, real-time energy management within MG is an important factor for the operators to guarantee optimal and safe operation of the system. The proposed EMS should be able to schedule the MG generation with minimum information shares sent by generation units. To achieve this ability, the present thesis proposes an operational architecture for real time operation (RTO) of a MG operating in both islanding and grid-connected modes. The presented architecture is flexible and could be used for different configurations of MGs in different scenarios. A general formula is also presented to estimate optimum operation strategy, cost optimization plan and the reduction of the consumed electricity combined with applying demand response (DR). The proposed problem is formulated as an optimization problem with nonlinear constraints to minimize the cost related to generation sources and responsive load as well as reducing MCP. Several optimization methods including mixed linear programming, pivot source, imperialist competition, artificial bee colony, particle swarm, ant colony, and gravitational search algorithms are utilized to achieve the specified objectives. The main goal of the thesis is to validate experimentally the design of the real-time energy management system for MGs in both operating modes which is suitable for different size and types of generation resources and storage devices with plug-and-play structure. As a result, this system is capable of adapting itself to changes in the generation and storage assets in real-time, and delivering optimal operation commands to the assets quickly, using a local energy market (LEM) structure based on single side or double side auction. The study is aimed to figure the optimum operation of micro-sources out as well as to decrease the electricity production cost by hourly day-ahead and real time scheduling. Experimental results show the effectiveness of the proposed methods for optimal operation with minimum cost and plug-and-play capability in a MG. Moreover, these algorithms are feasible from computational viewpoints while having many advantages such as reducing the peak consumption, optimal operation and scheduling the generation unit as well as minimizing the electricity generation cost. Furthermore, capabilities such as the system development, reliability and flexibility are also considered in the proposed algorithms. The plug and play capability in real time applications is investigated by using different scenarios.
This book features extensive coverage of all Distributed Energy Generation technologies, highlighting the technical, environmental and economic aspects of distributed resource integration, such as line loss reduction, protection, control, storage, power electronics, reliability improvement, and voltage profile optimization. It explains how electric power system planners, developers, operators, designers, regulators and policy makers can derive many benefits with increased penetration of distributed generation units into smart distribution networks. It further demonstrates how to best realize these benefits via skillful integration of distributed energy sources, based upon an understanding of the characteristics of loads and network configuration.
Renewable Energy Systems: Modelling, Optimization and Control aims to cross-pollinate recent advances in the study of renewable energy control systems by bringing together diverse scientific breakthroughs on the modeling, control and optimization of renewable energy systems by leading researchers. The book brings together the most comprehensive collection of modeling, control theorems and optimization techniques to help solve many scientific issues for researchers in renewable energy and control engineering. Many multidisciplinary applications are discussed, including new fundamentals, modeling, analysis, design, realization and experimental results. The book also covers new circuits and systems to help researchers solve many nonlinear problems. This book fills the gaps between different interdisciplinary applications, ranging from mathematical concepts, modeling, and analysis, up to the realization and experimental work. Covers modeling, control theorems and optimization techniques which will solve many scientific issues for researchers in renewable energy Discusses many multidisciplinary applications with new fundamentals, modeling, analysis, design, realization and experimental results Includes new circuits and systems, helping researchers solve many nonlinear problems
Distributed resource (DR) impacts voltage and frequency, and deviations out of tolerance limits are financial damage to the customers. This chapter presents an energy management system (EMS) with several approaches to overcome intermittency and create a semi-dispatchable generation supply. The EMS will work as a prosumer considering its level of dispatchability, without disturbing the frequency of the network. The power generation model is based on a small wind turbine, solar panels, PEMFC, and a hydrogen storage system. Probabilistic information concerning short-term forecast applied to wind speed and radiation is provided by individual stochastic models. The prosumer is modeled by applying time series analysis through the root mean square algorithm with forgetting factor and by using model predictive control to integrate the system. A case is presented using historic wind speed and radiation data from Mexico City and loads curves based on average households and mini-store on a daily basis.
This book provides a manual for the technical and structural design of systems for supplying decentralised energy in residential buildings. It presents the micro-combined cooling, heating & power systems Stirling engines & renewable energy sources (mCCHP-SE-RES) systems in an accessible manner both for the public at large, and for professionals who conceive, design or commercialise such systems or their components. The high performance levels of these systems are demonstrated within the final chapter by the results of an experiment in which a house is equipped with a mCCHP-SE-RES system. The reader is also familiarized with the conceptual, technical and legal aspects of modern domestic energy systems; the components that constitute these systems; and advanced algorithms for achieving the structural and technical design of such systems. In residential buildings, satisfying demands of durable development has gradually evolved from necessity to obligation and institutionalisation. Consequently a major paradigm change has appeared in the supply of energy to residential buildings, from the centralised production of energy using fossil fuels to the decentralised production of energy using local renewable sources. Furthermore, on the energy system market, energy micro systems which use renewable energy sources are increasingly commercialised. From among these, the mCCHP-SE-RES systems are particularly striking because they offer a high performance and they enhance the relationship between humans and the environment. This book is intended for postgraduate students of electrical engineering, applied mathematicians, and researchers of modelling and control of complex systems or power system technologies.
This dissertation, "Energy Management in Power Grid With Power Flow Routing" by Junhao, Lin, 林俊豪, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: The increase in energy demand and the integration of intermittent renewable energy sources (RESs) are stressing the power grid, prompting system operators to take active control measures for managing the power flow more efficiently and intelligently. Power flow routing, an emerging control paradigm for the flexible and responsive control of power flows, is a promising solution for power flow control and energy management. While most existing research efforts have been devoted to the hardware implementation of power flow controllers (PFCs) and power flow routers (PFRs), a systematic modelling and optimization framework is desired to facilitate the network-level research on power flow routing. In this thesis, we focus on the steady-state analysis and energy management for the future power network integrated with PFCs and PFRs. First, a generic functional model of the PFR is developed and incorporated into the optimal power flow (OPF) framework. The proposed PFR model encapsulates the desired features of PFRs, and is amenable for implementation of power flow routing. To pursue global optimality, a semidefinite programming (SDP) relaxation of the PFR-OPF problem is developed with a regularization method to guide a rank-1 solution. The numerical study on the assessment of the system loadability shows that the integration of PFRs and PFCs can improve the loadability significantly, and that the proposed SDP relaxation succeeds in obtaining the optimal or near-optimal solution of the PFR-OPF problem. Second, we study the robust dispatch of energy supply and spinning reserve to overcome the uncertainty of renewable generation. Based on the PFR-OPF framework, a robust OPF problem that incorporates power flow routing is formulated and solved by a column-and-constraint generation (C&CG) algorithm. A second-order cone programming relaxation is applied to the non-convex alternating-current (AC) power flow regions with the phase angle constraints for loops retained by linear approximation. Numerical results show the efficacy of our robust dispatch strategy in guaranteeing immunity against uncertain renewable generation, as well as in reducing the energy management costs through power flow routing. Finally, the robust OPF framework is extended to a multi-period robust OPF framework with receding horizon control to further cope with the variability of renewables. A robust resource scheduling problem for the direct-current (DC) microgrid is formulated to jointly optimize the power injections of distributed energy resources (DERs) and the configurations of PFCs and PFRs. Numerical results show that the proposed robust scheduling method is able to adapt to the fluctuations and variations of renewable generation in real time, and to achieve robustness guarantee with negligible loss of optimality. Empirically, with just a few PFCs and PFRs installed, the system can already achieve remarkable reduction of energy management costs. Subjects: Electric power systems - Automatic control Distributed generation of electric power - Computer simulation
