文献类型：期刊文献

英文题名：Economic scheduling of a smart microgrid utilizing the benefits of plug-in electric vehicles contracts with a comprehensive model of information-gap decision theory

作者：Sriyakul, Thanaporn[1];Jermsittiparsert, Kittisak[2,3,4]

第一作者：Sriyakul, Thanaporn

通讯作者：Jermsittiparsert, K[1];Jermsittiparsert, K[2];Jermsittiparsert, K[3]

机构：[1]Mahanakorn Univ Technol, Fac Business Adm, Bangkok 10530, Thailand;[2]Duy Tan Univ, Inst Res & Dev, Da Nang 550000, Vietnam;[3]Duy Tan Univ, Fac Informat Technol, Da Nang 550000, Vietnam;[4]Henan Univ Econ & Law, MBA Sch, Changsha 450046, Hunan, Peoples R China

第一机构：Mahanakorn Univ Technol, Fac Business Adm, Bangkok 10530, Thailand

通讯机构：[1]corresponding author), Duy Tan Univ, Inst Res & Dev, Da Nang 550000, Vietnam;[2]corresponding author), Duy Tan Univ, Fac Informat Technol, Da Nang 550000, Vietnam;[3]corresponding author), Henan Univ Econ & Law, MBA Sch, Changsha 450046, Hunan, Peoples R China.|[1048419]河南财经政法大学MBA学院;[10484]河南财经政法大学;

年份：2020

卷号：32

外文期刊名：JOURNAL OF ENERGY STORAGE

收录：;EI(收录号：20204409423443);Scopus(收录号：2-s2.0-85094154392);WOS:【SCI-EXPANDED(收录号:WOS:000599944300004)】；

语种：英文

外文关键词：Smart microgrid; Plug-in electric vehicle; Information gap decision theory; Two-stage stochastic programming; Hybrid uncertainty management

摘要：In this paper, a hybrid optimization approach is proposed to smart microgrid (SMG) operators to schedule the existing energy resources optimally to meet the load demand of the system. The proposed hybrid optimization is structured based on information-gap decision theory (IGDT) and two-stage stochastic programming to minimize the operational cost of the system in day-ahead (DA) and real-time (RT) power markets. The uncertainty of the day-ahead market price is tackled with the IGDT. The IGDT is furnished with robustness and opportunity functions leading to various risk-averse and risk-taker decision-making strategies. The problem is structured as bi-level programming, while by implementing the concept of envelop bounds, it is transferred into a single-level optimization problem. On the other hand, the uncertainties of the operation of the real-time market are modeled using scenarios with stochastic programming. The studied SMG is equipped with a photovoltaic system, a wind turbine, two microturbines (MTs), and battery storage. The results determine the scheduling of day-ahead exchange power and scheduled PEV contracts as here-and-now decisions of the optimization. However, the traded energy in the real-time market, MTs' dispatch, and the charging/discharging plan of battery storage are wait-and-see decisions made by the second stage of the programming. The results are obtained and discussed from the perspective of risk-neutral, risk-averse, and risk-taker decision-makers. As an example of performance, when the uncertainty horizon is increased by 10% in the robustness mode, the operation cost is increased by about 27.5%. In comparison, the same amount of increment of uncertainty horizon leads to cost-saving about 33.3% addressing the positive aspect of uncertainty using opportunity function.