Stochastic programming and market equilibrium analysis of microgrids energy management systems
Journal
Energy
Journal Volume
113
Pages
662-670
Date Issued
2016
Author(s)
Abstract
Microgrids facilitate optimum utilization of distributed renewable energy, provides better local energy supply, and reduces transmission loss and greenhouse gas emission. Because the uncertainty in energy demand affects the energy demand and supply system, the aim of this research is to develop a stochastic optimization and its market equilibrium for microgrids in the electricity market. Therefore, a two-stage stochastic programming model for microgrids and the market competition model are derived in this paper. In the stochastic model, energy demand and supply uncertainties are considered. Furthermore, a case study of the stochastic model is conducted to simulate the uncertainties on the INER microgrids in Taiwanese market. The optimal investment of the generators and batteries installation and operating strategies are determined under energy demand and supply uncertainties for the INER microgrids. The results show optimal investment and operating strategies for the current INER microgrids are also determined by the proposed two-stage stochastic model in the market. In addition, trade-off between the battery capacity and microgrids performance is investigated. Battery usage and power trading between the microgrids and main grid systems are the functions of battery capacity. © 2016 Elsevier Ltd
Subjects
Market equilibrium; Microgrids; Two-stage stochastic programming; Uncertainty analysis
Other Subjects
Competition; Economic and social effects; Electric batteries; Energy management; Energy management systems; Energy policy; Greenhouse gases; Investments; Optimization; Stochastic programming; Stochastic systems; Uncertainty analysis; Market competition; Market equilibria; Micro grid; Optimal investments; Renewable energies; Stochastic optimizations; Two-stage stochastic models; Two-stage stochastic programming; Stochastic models; demand analysis; electricity; energy market; greenhouse gas; management practice; market conditions; optimization; renewable resource; stochasticity; uncertainty analysis
Type
journal article