Hybrid renewable energy investment in microgrid

Both solar energy and wind energy are promising renewable sources to meet the world's problem of energy shortage in the near future. In this paper, we identify the complementary relation between solar power and wind power at certain locations of Hong Kong, and aim at studying the hybrid renewable energy investment in the microgrid. We jointly consider the investment and operation problem, and present a two-period stochastic programming model from the microgrid operator's perspective. In the first period, the operator makes optimal investment decisions on solar and wind power capacities. In the second period, the operator coordinates the power supply and demand in the microgrid to minimize the social operational cost. We design a decentralized algorithm for computing the optimal pricing and power consumption in the second period, and based on this solve the optimal investment problem in the first period. With realistic meteorological data obtained from Hong Kong observatory, we numerically demonstrate that the demand response saves 18% of the capital investment, and hybrid renewable energy investment reduces the generation capacity by up to 6.3% compared to a single renewable energy investment.