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Abstract
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Considering the existence of uncertain factors in electric energy systems, such asload variation, power market price, and power generation of renewable energysources, the results provided by the conventional deterministic optimal planningand operation of electric energy systems are not confirmed to be optimal frameworkfor future power system conditions. Accordingly, studying uncertainties associatedwith parameters of electric energy systems is of importance for obtaining moreeffective and promising solutions of planning and operation of electric energysystems. In traditional approaches, probabilistic methods, interval-based analysis,and hybrid probabilistic and possibilistic methods are implemented for handlinguncertainties associated with power system parameters. Recently, robust optimiza-tion (RO) and information gap decision theory (IGDT) methods are introduced aseffective tools for the solution of power system problems. The RO and IGDTmethods lead to more effective solutions and are promising for the robust planningand operation of electric energy systems. Such methods are capable to obtain optimalperformance of the electrical energy systems in the worst-case condition. This bookaims to study robust planning and operation of electric energy systems by employingRO and IGDT methods.TheRobust Optimal Planning and Operation of Electrical Energy Systemsencourages scientific research on all topics pertaining to operation and planning ofelectric energy systems in the presence of uncertainties attaining a robust level usingRO method and IGDT. This book presents the latest research being conducted ondiffering topics and recent developments and contribution of RO and IGDT methodsto the robust optimal planning and operation of the power systems. The topicscovered in this book are presented in the following: Information gap decision theory. •Robust optimization method. •Robust operation of multi-energy systems. •Risk-constrained scheduling of solar ice harvesting system. •Robust unit commitment. Robust scheduling of smart homes. •Robust scheduling of electrical distribution networks. •Robust microgrid and network expansion planning. •Robust control of distributed energy storage systems. The book contents are classified into two main parts, where the IGDT and ROmethod are discussed in thefirst and second parts, respectively. The aim of thefirst part is concentrating on definition and application of IGDT method inoptimal operation and planning of electrical energy systems, which are summarizedas follows:A review on the application of IGDT in electrical energy systems is provided inChap.1, where modeling of uncertain parameter using IGDT is accomplished usinga mathematical framework. The principles, fundamentals, applications, and advan-tages of the IGDT are discussed in Chap.2. The main aim of Chap.3 is to study theoptimal operation of hub energy systems with the consideration of net price uncer-tainty using IGDT. Chapter4 presents an IGDT-based framework for robust sched-uling of an ice storage system, where the uncertain nature of building cooling load isstudied. IGDT is implemented on a multi-period unit commitment problem inChap.5 aiming to maximize total profit obtained from selling electricity to con-sumers, where the uncertainty of electricity prices is modeled for assessing howmarket operator can make a risk averse decision at low market prices. Chapter6studies energy management of a renewable energy-based smart home, which con-tains a photovoltaic system for supplying a ratio of electrical demand of theconsidered home. In this chapter, the robust self-scheduling of a photovoltaic systempanel installed in the smart home is formulated, and the best suited set point of allsuppliers is obtained, where IGDT is applied for handling the uncertain powergeneration of the photovoltaic system. The main purpose of Chap.7 is investigatingthe unit commitment problem in the presence of renewable energy sources andenergy storage systems and mo
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