Time-series quasi-dynamic load flow analysis with seasonal load variation to resolve energy nexus for a practical distribution network in Puducherry smart grid system incorporating harmonic analysis and mitigation

Abstract

Time-series quasi-dynamic load flow analysis is an important methodology to estimate the voltage profiles across various nodes in modern distribution networks. This paper describes the necessity of time-series load flow analysis (LFA) for a real-time power distribution network in Puducherry smart grid system by considering seasonal load variations in the union territory of Puducherry, India to obtain optimal performance. In this study, this load flow analysis has been applied to test systems such as IEEE 69, IEEE 37, IEEE 34 and the Indian utility 29 node distribution network (IU29NDN) in Puducherry smart grid system with unbalanced load patterns and energy sources in close proximity. Modified Decision Making (MDM) algorithm is proposed in this paper to improve voltage profiles with in distribution networks by choosing the size and location of solar photovoltaic (SPV) systems. The variations in the node voltages, real power, and reactive power flows are estimated for distribution networks subjected to seasonal load variations by quasi-dynamic load flow simulations conducted over a period of 24 h with 15-minute step size. Furthermore, a harmonic power flow is illustrated and extended to mitigate the harmonics by optimal placement of shunt capacitors (SCs) in all the test systems by incorporating MDM algorithm.