A hybrid probabilistic information gap decision theory based energy management of an active distribution network

Abstract

The optimal operation of an active distribution network requires proper coordination between multiple entities like renewable energy sources, storage units, power electronic devices, demand response implementation, and network reconfiguration. In this context, this paper proposes optimal energy coordination and management scheme among various entities with different ownership in a reconfigurable active distribution network. The distribution system operator manages the coordinated energy procurement scheme from multiple sources to maximize the expected hourly profit of operation. Uncertainties of load, renewable generation, grid energy price, and the charging power of hybrid electric vehicles are modelled using a probabilistic “Hong’s 2m point estimate” approach. On the other hand, the uncertainty of the demand response is modelled using information gap decision theory. The optimization problem is solved in a hybrid framework encompassing probability and information gap decision theory. Simulation studies on a thirty-three-node distribution network validate the efficacy of the proposed method. With the proposed energy management and coordination scheme, the daily expected operating cost reduces by ∼6.66% while the daily expected energy loss reduces by ∼26.05%. Implementing a risk-averse strategy to hedge against the risk of uncertain demand response participation reduces the profit by ∼3.21% for a tolerance limit of 5%.