Abstract: In Southwest China, tremendous power has been abandoned and the consumption of clean energies hindered. Aimed at this problem and the minimum operation cost of interconnected power grids, this study develops a multi-objective optimization model of multi-power grid joint operation, considering clean energy consumption and power sending-out. This model uses the niche multi-objective particle swarm optimization (NMOPSO) algorithm to seek Pareto frontiers, and the entropy-based technique for order preference by similarity to ideal solution (TOPSIS) to decide the optimal trade-off solution. It is applied in a case study of one sending grid plus two receiving grids system for power transmission from Yunnan to Guangdong and Guangxi. The results show that NMOPSO gives approximate Pareto frontiers with a uniform distribution; the TOPSIS optimal trade-off solution is featured with a clean energy consumption rate up to 100% of that of the sending grid and daily hours of the transmission channels in use reaching the greatest. Thus, our new method of optimization calculation greatly improves the grids’ consumption capability of clean energy and the use factor of transmission channels.

Key words: consumption of clean energy, multi-power grid joint, power sending-out, niche multi-objective particle swarm optimization, technique for order preference by similarity to ideal solution