Decentralized prioritization of demand response programs in multi-area power grids based on the security...

The deregulation of electrical energy grids (EEGs) and surrogating the installation of bulk power plants with distributed generations such as wind energy sources, despite the score of advantages, bring new challenges for the secure operation of these EEGs for their operators. On the other hand, the deployment of demand response programs (DRPs) alongside the management of these multi-area EEGs (MEEGs) intensifies the complexity of the situation. In this paper, a method is proposed for the secure operation of MEEGs when DRPs are employed to incorporate the end-users in balancing the demand-supply chain. Moreover, the techno-economic impacts of fluctuating nature of wind energy sources are mitigated by coordinating them with energy storage systems (ESSs). To do so, a decentralized probabilistic DC-SCOPF model is developed for the operation of MEEGs with ESS-coordinated wind energy sources when several DRPs are deployed in their different areas. The decentralization of the model is performed based on the optimality condition decomposition (OCD) algorithm which results in a mixed-integer non-linear programming (MINLP) problem for each area of the MEEG. What is more; a priority list of DRPs in different areas of the MEEG is generated based on four criteria including the overall operational cost of the system, the number of critical contingencies as the security measure, the overall shed load, and the peak-to-valley ratio (PVR) of the daily demand curve. Numerical simulations are carried out on the New England 39-bus testbed and obtained results are discussed in depth.