Abstract
In this paper, an energy management system is taken into account to control some distributed energy resources spread into an entity. The included facilities are aggregated by an energy hub (EH) and also equipped by some control and communication in a smart environment. Through this system, the stakeholder can prepare energy operational planning in the form of energy markets. In this paper, a novel convexity principle is presented to face the nonlinearity of combined heat and power (CHP) unit model considering triple operational zones. Here, the energy hub acts as a price taker in the energy markets. Here, some stochastic parameters such as day-ahead market price, wind power output, and plug-in hybrid electric vehicles (PHEVs) entry and exit time and their battery characteristics are considered; therefore a robust scenario-based optimization strategy is proposed to deal with them. The robust optimization is employed by upper and lower bounds for market price uncertain parameter by historical behaviors and also is presented through confidence bounds. Also, to deal with the wind power uncertainty, the scenario-based method is performed by scenario generation based on historical wind data. To demonstrate the effectiveness of the proposed strategy, a real case study is investigated and some prominent results are provided. As obtained, the CHP unit can work actively in the winter day so that the 3rd operational zone will be active and also with increasing the percentage of PHEV units to 100 % within the EH in the summer day, the percentage of power sold to the network will be increased to 68.1 % compared with no vehicle situation.
Published Version
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