A swarm intelligence approach to harness maximum techno-commercial benefits from smart power grids
Modern electricity power market has evolved from conventional vertically integrated structure to the present deregulated form and eventually to the development of the smart power grids, over the past few decades. Different market players like generation, transmission and distribution companies with their individual and collective goals and constraints are now participating in real time, prompting the need for optimal allocation and utilization of the smart grid infrastructure and resources. The objective of the optimization thus received a paradigm shift from the traditional generation cost optimization, to optimal utilization of the available resources to deliver maximum benefit to all the power market participants and the so-called social welfare. Maximization of social welfare is a highly nonlinear optimization problem and generally requires application of an efficient stochastic optimization method with in-built ability of avoiding local optima. The swarm intelligence-based optimization algorithms, developed and presented in this book chapter, offer substantial improvement in the quality of solution to the problem over the conventional solution methods. The chapter presents real-time simulation and experiments on benchmark power system networks with the developed optimization algorithms. The results are found to be quite encouraging.
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