Research Information System
JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, vol.40, no.2, pp.1335-1346, 2025 (SCI-Expanded)
The planning of energy generation and consumption is the basis for the daily operation of power systems in order to maintain a stable operation by keeping the generation and consumption in balance. An effective day- ahead planning strategy enables economic and reliable operation of the electricity grid. In addition, day- ahead scheduling provides a reference for intra-day scheduling. The aim of this study is to investigate optimal Pareto solutions that provide solutions to the day-ahead optimum energy planning or scheduling problems in a utility connected five bus distribution grid test system consisting of renewable energy sources and storage units. The multi objective function, which contain the operating cost and active power losses of the network, has been defined by considering the power generation units and network constraints. The weighted sum method based multi objective symbiotic organisms search (MOSOS) algorithm has been proposed to solve this multi constrained multi objective problem. The performance of the proposed algorithm is compared with that of the weighted sum method based multi objective particle swarm optimization (MOPSO) algorithm and the weighted sum method based multi objective cuckoo search optimization (MOCSO) algorithm. The results have shown that the proposed MOSOS algorithm results in better solution than those of MOPSO and MOCSO algorithms.