Abstract
Capacitor allocation is one of the complex and challenging problems in modern power system operation. Several benefits including reduction of system loss and improvement of bus voltage profile can be achieved by optimal capacitor allocation. It is a complex nonlinear constrained optimization problem, and many modern meta-heuristic techniques have been applied to solve the problem. However, one of the major difficulties in modern population-based meta-heuristic techniques is the selection of control parameters which are normally problem-dependent. As reported in the literature, a wrong parameter selection may result in premature convergence and even lead to stagnation. This paper introduces a new improved algorithm using chaos enhanced differential evolution (DE) for optimal capacitor allocation to avoid premature convergence. Logistic map chaotic sequence is used for self-adjustment of control parameters of DE. A multi-objective framework for the capacitor allocation problem is presented considering active power loss, cumulative voltage deviation (CVD) and system cost with a set of equality and inequality constraints. A 69-bus radial distribution is selected for demonstration and validation purpose.
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Mandal, S., Mandal, K.K., Tudu, B., Chakraborty, N. (2019). A New Improved Hybrid Algorithm for Multi-objective Capacitor Allocation in Radial Distribution Networks. In: Bansal, J., Das, K., Nagar, A., Deep, K., Ojha, A. (eds) Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 816. Springer, Singapore. https://doi.org/10.1007/978-981-13-1592-3_46
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DOI: https://doi.org/10.1007/978-981-13-1592-3_46
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