Voltage Stability Margin Enhancement with Optimal DG and D-STATCOM Allocation in Radial Distribution System

Todays’ distribution systems are an active network due to the interconnection of renewable energy and distributed energy resources. With continuous load growth globally due to the population pressure and industrialization, the distribution system operators need to address the issues of lower voltage profile and increased losses in the network due to more reactive load requirements of nonlinear loads. This has concern towards the voltage stability issues in the distribution system. Therefore, the integration of the distributed generation and its optimal sizes and proper deployment of reactive power sources are the key aspects to be considered during planning. This paper addresses the issue of optimal allocation of DGs and reactive power source D-STATCOM considering maximizing reliability and minimizing total power loss, greenhouse gas emission and fault current with each aspect weighted according to their priority. The deregulation has made the issue more of a techno-economic problem thus tasking the Distribution Network Operator (DNO) with the task to provide for a stable system while being economical. As economics plays a crucial role in operations, the operating cost of various combinations is evaluated. Furthermore, the stability of the deployed combinations is analysed using the P–V curve. The various deployed combinations are compared and the simulated results obtained are promising thus making it easy for the DNO to pick the combinations according to the requirements which in turn make the distribution system more techno-economically efficient. The main highlights of the paper are loss minimization, emission reduction, voltage stability margin enhancement and improvement in the reliability of the network in terms of load oriented reliability index. The analysis has been carried out on an IEEE 33 bus test system using the heuristic optimization-based approach, Grey Wolf Optimization. The results are compared and analysed for different case studies.