Optimal planning of electricity storage to minimize operating reserve requirements in an isolated island grid - Nikolaidis, Pavlos; Chatzis, Sotirios P.; Poullikkas, Andreas (My University, 2020)
Electrical energy storage (EES) constitutes a potential candidate capable of regulating the power generation to match the loads via time-shifting. Optimally planned, EES facilities can meet the increasing requirement of reserves to manage the variability and uncertainty of renewable energy sources (RES) whilst improving the system operation efficiency and economics. In this work, the impact of intermittent RES on total production cost (TPC) is evaluated in the presence and absence of storage, using annual data regarding the non-interconnected power system of the island of Cyprus. Performing weekly simulations for the entire year of 2017, TPC is computed by solving the unit commitment based on a constrained Lagrange Relaxation method. Seven selected EES technologies are modeled and evaluated via a life-cycle cost analysis, based on the most realistic technical and cost data found in the literature. The results derived from the uncertainty analysis performed, show that zinc-air (Zn-air) battery offers the highest net present value (NPV). Lead-acid (Pb-acid) and sodium-sulfur (Na-S) are considered viable solutions in terms of mean NPV and investment risk. Lithium-ion (Li-ion) battery exhibits a particularly expensive choice. Dominated by its increased capital cost which still governs its overall cost performance Li-ion achieves a negative mean NPV far below zero. However, to strengthen the benefits derived from EES integration, further research and development is needed improving the performance and costs of storage. The uncertainty governing the majority of EES technologies, in turn, will be reduced, increasing their participation and RES contribution in autonomous power system operations.
Keywords: Autonomous power systems; Electrical energy storage; Lagrange relaxation; Life-cycle cost analysis; Non-interconnected power system; Uncertainty analysis