Risk-Constrained Optimal Energy Management for Virtual Power Plants Considering Correlated Demand Response
| Autor: | Tao Jin, Zheming Liang, Wencong Su, Hajir Pourbabak, Qais Alsafasfeh |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Mathematical optimization
General Computer Science business.industry Energy management Computer science 020209 energy 020208 electrical & electronic engineering Energy balance 02 engineering and technology Renewable energy Microeconomics Demand response Load management Virtual power plant 0202 electrical engineering electronic engineering information engineering Electricity business Operating cost |
| Zdroj: | IEEE Transactions on Smart Grid. 10:1577-1587 |
| ISSN: | 1949-3061 1949-3053 |
| DOI: | 10.1109/tsg.2017.2773039 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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