Sustainable and Optimized Black Start in Microgrids

– The modern energy transition has resulted in the development of sustainable Microgrids (MGs) that utilize Renewable Energy Sources (RES) in order to cover the demand in an environmental-friendly way. One of the main benefits of a MG is the ability to operate independently and provide flexibility services to the main grid’s operator. Perhaps one of the most desirable services that a MG can provide is the black start, which is required when the overall system faces a blackout. Up until recently, the main idea of the black start was to restart the operation of the MG utilizing fuel-based Distributed Energy Resources (DER) such as diesel generators. However, there are other controllable units that can be utilized for this purpose, such as Battery Energy Storage Systems (BESS). Therefore, provided that the BESS are charged with renewable energy, it is possible to have a totally sustainable black start. The purpose of this paper is to present an optimization algorithm that assists the MG’s operator in making key-decisions related to black start in MGs equipped with RES and BESS. The developed Mixed-Integer Linear Programming (MILP) optimizer is developed in Python with the use of Pyomo and the decision variables are the energy that needs to be discharged from (or charged to) each BESS and the curtailment of RES production, if required. The algorithm is tested on a MG that contains two BESS (one main and one secondary) and two sorts of RES, i.e., Photovoltaics (PV) and a Wind Generator (WG). The results highlight the sustainability and practicability of the proposed solution, even under extreme conditions.