Abstract
Distribution network expansion planning (DNEP) is a multiobjective problem fulfilling demand growth, ensuring reliable supply and minimizing total expansion cost. It is a sequential methodology to plan for the reinforcement of existing or installation of new feeders and substations. This paper handles dynamic DNEP incorporating energy storage systems (ESSs), used to shave the peak demand and valley filling. Monte Carlo simulation method is used to introduce uncertainty in load demand of the system A.C. power flow, annual and daily load duration curve are used. Reliability index is modeled for composite system of lines and ESSs. Planning is formulated as constrained, mixed integer nonlinear programming problem (MINLP) and solved using inertia PSO with controlled particle movement to avoid randomness and premature convergence. An 11 kV, 30-bus radial distribution network is considered as a case study. Simulation results validate the consideration of ESSs in DNEP by a significant improvement in the voltage profile, losses, total expansion cost and reliability of the distribution system. The proposed PSO proves efficient with improved convergence and reduced planning cost.
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Acknowledgements
The authors acknowledge the financial support provided by DST Rajasthan Grant No. 7(3) DST/Rand D/2016/3286 titled “Distribution Network Planning Mechanisms for state utilized under large integration of EV’s and DERs in Smart Grid Framework.”
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Kumari, S., Jain, P., Saxena, D., Bhakar, R. (2020). Dynamic Distribution Network Expansion Planning Under Energy Storage Integration Using PSO with Controlled Particle Movement. In: Venkata Rao, R., Taler, J. (eds) Advanced Engineering Optimization Through Intelligent Techniques. Advances in Intelligent Systems and Computing, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-8196-6_44
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DOI: https://doi.org/10.1007/978-981-13-8196-6_44
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