A Convex Micro-Grid-Based Optimization Model for Planning of Resilient and Sustainable Distribution Systems Considering Feeders Routing and Siting/Sizing of Substations and DG Units
Description
Highlights • New convex optimization model is proposed for distribution system expansion planning. • Optimal resilient microgrid based planning. • Routing and hardening of feeders, sizing and siting of substations and distributed generators. • Emission reduction as well as uncertainty of wind generations is also taken into account. • Reconfigurable microgrids to tackle with severe outage states. Abstract Integration of distributed generation (DG) and renewable energy resources (DERs) has affected planning and operation of recent distribution networks (DNs). On the other side, resiliency and sustainability of DNs is the other concern of distribution network operators. In this paper, a new formulation is developed for optimal planning of resilient DNs based on optimal formation of resilient micro-grids (MGs). The formulation aims to implement optimal siting and sizing of conventional and renewable-based DGs, optimal routing and type of feeders, as well as optimal sizing and placement of HV/MV substations to configure adequate and resilient MGs against extreme events. The investment, operational, emissions, and resiliency costs have been included in the objective function, and all the problem constraints as well as uncertainty of renewable DGs have been taken into account. The new formulation uses line-flow-based (LFB) model of AC power flow equations, and reserve feeders (tie-lines) are employed to enhance resiliency after severe outages via reconfiguration concept. All the relations have been convexfied in order to compose a mixed-integer quadratically-constrained (MIQCP) model to be solved with global optimum solvers in GAMS. Efficiency of the conducted methodology has been evaluated by different experiments on the 24-node system, and the results are investigated.