Microgrids have emerged as a promising solution for accommodating the integration of renewable energy resources. But the intermittency of renewable generation is posing challenges such as voltage/frequency fluctuations, and grid stability issues in grid-connected modes. Model predictive control (MPC) is a method for controlling a process while satisfying a set of constraints. It has been in use for chemical plants and in oil refineries since the 1980s, but in recent years has been deployed for power systems and electronics as well.
This concise work for researchers, engineers and graduate students focuses on the use of MPC for distributed renewable power generation in microgrids. Fluctuating outputs from renewable energy sources and variable load demands are covered, as are control design concepts. The authors provide examples and case studies to validate the theory with both simulation and experimental results and review the shortcomings and future developments.
Chapters treat power electronic converters and control; modelling and hierarchical control of microgrids; use of MPC for PV and wind power; voltage support; parallel PV-ESS microgrids; secondary restoration capability; and tertiary power flow optimization.
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Jiefeng Hu is an associate professor in power electronics and smart microgrids, and the program coordinator (electrical engineering) of the School of Engineering, Information Technology and Physical Sciences at Federation University Australia. Previously, he was an assistant professor at The Hong Kong Polytechnic University, where he led an international team to develop renewable energy technologies for smart cities. He has published more than 100 research papers, and serves as editor/ associate editor on prestigious IET and IEEE journals.
Josep Guerrero is a professor with the Department of Energy Technology, Aalborg University, Denmark. He is responsible for the Microgrid Research Program, and the founder and director of the Centre for Research on Microgrids (CROM). Prof. Guerrero's research interests focus on different microgrid aspects, including power electronics, distributed energy-storage systems, control, energy management, metering and the use of the IoT. From 2014 to 2018 he was awarded a Highly Cited Researcher by Thomson Reuters.
Syed Islam is a professor and the dean for the School of Engineering, Information Technology and Physical Sciences at Federation University Australia. His awards include the Curtin University inaugural award for Research Development and two Sir John Madsen medals. He has published over 270 technical papers on condition monitoring of transformers, wind energy and smart power systems, and serves on prestigious committees and boards, and in editorial capacities of key journals.
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Hardback. Condición: New. Microgrids have emerged as a promising solution for accommodating the integration of renewable energy resources. But the intermittency of renewable generation is posing challenges such as voltage/frequency fluctuations, and grid stability issues in grid-connected modes. Model predictive control (MPC) is a method for controlling a process while satisfying a set of constraints. It has been in use for chemical plants and in oil refineries since the 1980s, but in recent years has been deployed for power systems and electronics as well. This concise work for researchers, engineers and graduate students focuses on the use of MPC for distributed renewable power generation in microgrids. Fluctuating outputs from renewable energy sources and variable load demands are covered, as are control design concepts. The authors provide examples and case studies to validate the theory with both simulation and experimental results and review the shortcomings and future developments. Chapters treat power electronic converters and control; modelling and hierarchical control of microgrids; use of MPC for PV and wind power; voltage support; parallel PV-ESS microgrids; secondary restoration capability; and tertiary power flow optimization. Nº de ref. del artículo: LU-9781839533976
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Hardback. Condición: New. Microgrids have emerged as a promising solution for accommodating the integration of renewable energy resources. But the intermittency of renewable generation is posing challenges such as voltage/frequency fluctuations, and grid stability issues in grid-connected modes. Model predictive control (MPC) is a method for controlling a process while satisfying a set of constraints. It has been in use for chemical plants and in oil refineries since the 1980s, but in recent years has been deployed for power systems and electronics as well. This concise work for researchers, engineers and graduate students focuses on the use of MPC for distributed renewable power generation in microgrids. Fluctuating outputs from renewable energy sources and variable load demands are covered, as are control design concepts. The authors provide examples and case studies to validate the theory with both simulation and experimental results and review the shortcomings and future developments. Chapters treat power electronic converters and control; modelling and hierarchical control of microgrids; use of MPC for PV and wind power; voltage support; parallel PV-ESS microgrids; secondary restoration capability; and tertiary power flow optimization. Nº de ref. del artículo: LU-9781839533976
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