Title | ||
---|---|---|
Risk-Constrained Optimal Energy Management for Virtual Power Plants Considering Correlated Demand Response |
Abstract | ||
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In this paper, we propose a new framework for the optimal virtual power plant (VPP) energy management problem considering correlated demand response (CDR). Our objective is to minimize the VPP operating cost while maintaining the power quality of the system. We formulate a risk-constrained two-stage stochastic program to address uncertainties in day-ahead and real-time electricity prices, renewable energy source’s generation processes, and the CDR relationship. The VPP can also maintain cooling and heating balances by coordinating combined cooling, heating, and power production and CDR units. Extensive simulation results show that the VPP can minimize the operating cost and ensure the energy balance and power quality by coordinating components in the framework we propose. |
Year | DOI | Venue |
---|---|---|
2017 | 10.1109/TSG.2017.2773039 | IEEE Transactions on Smart Grid |
Keywords | Field | DocType |
Uncertainty,Load management,Trigeneration,Boilers | Load management,Energy management,Mathematical optimization,Renewable energy,Electricity,Microeconomics,Demand response,Control engineering,Energy balance,Virtual power plant,Engineering,Operating cost | Journal |
Volume | Issue | ISSN |
10 | 2 | 1949-3053 |
Citations | PageRank | References |
2 | 0.42 | 0 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Zheming Liang | 1 | 2 | 1.44 |
Qais H. Alsafasfeh | 2 | 10 | 3.63 |
Tao Jin | 3 | 4 | 2.48 |
Hajir Pourbabak | 4 | 13 | 2.82 |
Wencong Su | 5 | 254 | 27.89 |