Mitigating the volatility of renewable distributed generators with plug-in electric vehicles in optimal operation of active distribution networks

Abstract

Active distribution networks (ADNs) are becoming popular worldwide, where renewable distributed generators (DGs) are responsible to support system operation and allowed to be integrated to networks under non-firm connection agreements. With the increasing penetration of renewable DGs, their power volatility cannot be neglected any more. In order to overcome the negative influences caused by the volatility of renewable DGs, a strategy for mitigating the volatility with plug-in electric vehicles (PEVs) is proposed for economic and safe operation of ADNs. First, a PEV aggregator is proposed to control a group of PEVs, which can act as demand response in ADNs by charging/discharging power. Then, a volatility index (VI) is defined to measure the volatile degree of power from renewable DGs in a certain time period. Based on VI, the formulation of union volatility index is derived, considering the power charged/discharged by PEV aggregators. Thereafter, an optimal operation model of ADN operation with volatility constraints is proposed. Its objective is to minimize the operation cost of ADNs. This optimal model is solved by a novel algorithm–disruption bare-bones particle swarm optimization algorithm, which integrates disruption strategies into the bare-bones particle swarm optimization algorithm. The proposed model is demonstrated on a 37-node radial distribution system with a PEV aggregator. Five scenarios are carefully designed to certify the necessity of mitigating the volatility of renewable DGs in network economic operation. It is concluded that mitigating the volatility of renewable DGs and adopting real-time pricing schemes on PEV aggregators are particularly effective for optimal operation of ADNs.