Optimal Scheduling of Multi-Source Microgrid Considering Power to Gas Technology and Wind Power Uncertainty. (December 2017)

• Record Type: Journal Article
• Authors: Liu, Weikang; Wang, Dan; Yu, Xiaodan; Jia, Hongjie; Wang, Weiliang; Yang, Xianshen; Zhi, Yunqiang
• Is Part Of: Energy procedia. Volume 143(2017)
• Page Start: 668
• Page End: 673
• Publication Date: 2017-12
• Subjects: multi-source microgrid -- power to gas -- optimal scheduling -- energy flow optimization; Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.12.744
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: The development of renewable energy is essential for relieving the pressure of increasing energy demand and reducing the greenhouse gas emission. The intermittency and uncertainty nature of renewable energy generation can lead to overproduction and consequently the curtailment of renewable energy. As the installed capacity of renewable energy increases, the curtailment problem is getting more serious. Thus it is of great significance to improve the integration of renewable energy from the perspective of economy and stability among various energy vectors. Power to gas (P2G) technology is a novel way to deal with the promotion of renewable energy integration, which can increase the coupling of electricity and gas by transforming extra renewable energy to storable hydrogen and methane. In this paper, the P2G technology is integrated to the multi-source microgrid (MSM), which includes wind power, electric boiler, micro turbine and gas boiler, and thermal storage, gas storage and electric energy storage are also included in the MSM. The MSM is modeled under the framework of energy hub, the optimal scheduling model of the MSM is based on the objective function of minimizing the total cost, consisting of energy cost of buying electricity and nature gas, as well as the penalty cost of wind power curtailment. A Monte Carlo simulation is used in this paper to analyze the uncertainty of wind power. The result of this paper shows that by optimizing the various energy flows and utilization of energy conversion, dispatch and storage technology in the MSM, the overall energy efficiency is significantly improved.