Optimal Management of a Distribution Feeder During Contingency and Overload Conditions by Harnessing the Flexibility of Smart Loads

Due to an increase in penetration of intermittent distributed energy resources (DERs) in conjunction with load demand escalation, the electric power system will confront more and more challenges in terms of stability and reliability. Furthermore, the adoption of electric vehicles (EVs) is increasing day by day in the personal automobile market. The sudden rise in load demand due to EV load might cause overloading of the potential transformer, undue circuit faults and feeder congestion. The objective of this paper is to develop a strategy for distribution feeder management to support the implementation of emergency demand response (EDR) during contingency and overload conditions. The proposed methodology focuses on management of smart home appliances along with EVs by considering demand rebound and consumer convenience indices, in order to reduce network stress, congestion and demand rebound. The developed scheme ensures that the load profile is retained below a certain level during a demand response event while mitigating demand rebound impacts. Simultaneously, the mitigation of consumers' convenience level violation, information of smart loads and homeowners' objective of serving critical loads are also considered during the event. The effectiveness of the developed approach is assessed by simulating a node of a distribution network of 300kW, consisting of 9 distribution transformers serving the associated homes. In this study, the smart loads such as an air conditioner/heater, an EV, a clothes dryer, and a water heater are also modeled and simulated. Furthermore, the simulation results are compared with an already developed de-centralized approach, and a simple fair distribution approach to evaluate and validate the effectiveness of the designed methodology. It is exhibited by the analysis of the results that the developed approach reduced the demand rebound following a demand response event and minimized the congestion at distribution transformer during overloading condition while maintaining the consumers' comfort.