Planning Stage Reliable Operation of Dynamic Microgrids

Abstract

The deployment of renewable energy generation is increasing at the distribution level in power systems. The concept of microgrids reduces the complex control burden from the system operator and lowers electricity prices. As the number of nested microgrids grows in the distribution system, there is a paradigm transition from static to dynamic microgrids. This research introduced reliable planning for the operation of dynamic microgrids in the planning stages to provide solutions in case of a real contingency, to provide solutions in case of real contingencies. The research begins with the partitioning of distribution networks in the planning stage based on different objective functions. Several constraints must be maintained during the partitioning process. This research proposes three modified algorithms to address different problems. The effectiveness of these algorithms was verified through the IEEE 33 Radial Bus System in PSCAD and the IEEE 39-Bus system in PSLF. The worst case in a distribution system is the sudden trip of one or more generators. Load shedding is equivalent to increasing power generation in steps. With the objective of reducing interruption costs, a greedy-based sorting algorithm was proposed to minimize outage costs. The algorithm was implemented in Python and tested on the IEEE 39-Bus system. In addition to addressing economic issues on the demand side, economic considerations were also considered on the generation side. During the planning stage of reliable operation, the objective was to minimize the fuel cost of various generators while maintaining power balance. Particle swarm optimization was utilized to generate the best results, and the algorithm was implemented in Python. The test results from a three-generator and thirteen-generator systems were compared with those published in technical papers.