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Journal article(2022)
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Juan M. Rey, Iván Jiménez-Vargas, Pedro P. Vergara , Germán Osma-Pinto, Javier Solano
Autonomous microgrids are a suitable solution for off-grid electrification in terms of costs and reliability. The correct sizing of its generation and storage systems ensures efficient utilization of the available energy resources. Generally, many sizing approaches assume optimized energy management strategies that rely on central control architectures. However, these architectures are not always available, especially in limited investment microgrid projects. For this reason, the study of operation scenarios based on decentralized control strategy such as droop control is relevant. Based on this, this paper aims to evaluate the impact of the droop control over the sizing results of a solar/wind/battery/diesel microgrid. For this purpose, a case study of a sizing problem is presented, including the formulation and modelling. Results are presented comparing an hourly optimized energy management scenario with multiple values of the droop control parameters. Simulations results indicate that a competitive total cost can be obtained if the droop parameters are calculated considering the microgrid sizing results. Based on this, a generalizable design methodology for this purpose is presented.
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Autonomous microgrids are a suitable solution for off-grid electrification in terms of costs and reliability. The correct sizing of its generation and storage systems ensures efficient utilization of the available energy resources. Generally, many sizing approaches assume optimized energy management strategies that rely on central control architectures. However, these architectures are not always available, especially in limited investment microgrid projects. For this reason, the study of operation scenarios based on decentralized control strategy such as droop control is relevant. Based on this, this paper aims to evaluate the impact of the droop control over the sizing results of a solar/wind/battery/diesel microgrid. For this purpose, a case study of a sizing problem is presented, including the formulation and modelling. Results are presented comparing an hourly optimized energy management scenario with multiple values of the droop control parameters. Simulations results indicate that a competitive total cost can be obtained if the droop parameters are calculated considering the microgrid sizing results. Based on this, a generalizable design methodology for this purpose is presented.
Book chapter(2018)
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Juan M. Rey, Pedro P. Vergara, Javier Solano, Gabriel Ordóñez
This chapter introduces concepts to understand, formulate, and solve a microgrid design and optimal sizing problem. First, basic concepts of energy potential assessment are introduced, in order to determine if a location is suitable for PV and wind generation systems implementation. Second, different modeling approaches are presented and the required characteristics for the optimal microgrid sizing problem are discussed. Third, basic concepts about load estimation for the design and sizing of microgrids are introduced. Fourth, the most common microgrid sizing criteria are presented and classified according to the type of analysis. Fifth, basic concepts related to multi-objective optimization are introduced and some common design approaches and optimization algorithms are presented, emphasizing into multi-objective genetic algorithms. In addition, microgrids design commercial software is reviewed. Sixth, some IEEE standards related to the design, operation, and implementation of microgrids are presented. Finally, the chapter concludes with key remarks on microgrid design and sizing problem.
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This chapter introduces concepts to understand, formulate, and solve a microgrid design and optimal sizing problem. First, basic concepts of energy potential assessment are introduced, in order to determine if a location is suitable for PV and wind generation systems implementation. Second, different modeling approaches are presented and the required characteristics for the optimal microgrid sizing problem are discussed. Third, basic concepts about load estimation for the design and sizing of microgrids are introduced. Fourth, the most common microgrid sizing criteria are presented and classified according to the type of analysis. Fifth, basic concepts related to multi-objective optimization are introduced and some common design approaches and optimization algorithms are presented, emphasizing into multi-objective genetic algorithms. In addition, microgrids design commercial software is reviewed. Sixth, some IEEE standards related to the design, operation, and implementation of microgrids are presented. Finally, the chapter concludes with key remarks on microgrid design and sizing problem.
