Abstract
Uncertainties are the most significant challenges in the smart power system, necessitating the use of precise techniques to deal with them properly. Such problems could be effectively solved using a probabilistic optimization strategy. It is further divided into stochastic, robust, distributionally robust, and chance-constrained optimizations. The topics of probabilistic optimization in smart power systems are covered in this review paper. In order to account for uncertainty in optimization processes, stochastic optimization is essential. Robust optimization is the most advanced approach to optimize a system under uncertainty, in which a deterministic, set-based uncertainty model is used instead of a stochastic one. The computational complexity of stochastic programming and the conservativeness of robust optimization are both reduced by distributionally robust optimization.Chance constrained algorithms help in solving the constraints optimization problems, where finite probability get violated. This review paper discusses microgrid and home energy management, demand-side management, unit commitment, microgrid integration, and economic dispatch as examples of applications of these techniques in smart power systems. Probabilistic mathematical models of different scenarios, for which deterministic approaches have been used in the literature, are also presented. Future research directions in a variety of smart power system domains are also presented.
Highlights
Energy demand is expanding in lockstep with global population expansion, resulting in a supply-demand mismatch
It is a known fact that real time problems of smart power systems have uncertainties and can be handled only by probabilistic optimization
This review paper has been focused on various aspects of probabilistic optimizaion in smart power system
Summary
Energy demand is expanding in lockstep with global population expansion, resulting in a supply-demand mismatch. In an electrical power system, the grid is composed of multiple energy generating, transmission, distribution, and control elements. Intelligent distribution systems are a critical component of a smart power system It is composed of a variety of sensors and smart sensing mechanisms, as well as a sensor network that includes smart metres, distribution transformer management, and monitoring. Employing sensors for real-time monitoring helps to deal with the power management of distributed energy resources, such as distributed generators (DGs) [17] and electric vehicles [18], as well as to improve the smart grid’s reliability as it makes the integration of renewable energy resources much more convenient and improves both the efficiency and reliability of smart power system [19,20]. It is necessary to investigate probabilistic optimization in order to formulate the influence of various types of uncertainty in intelligent power systems
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