A novel economic method of battery modeling in stand-alone renewable energy systems to reduce life cycle costs

Abstract

Since the main part of a stand-alone Renewable Energy System (RES) is related to the battery, effective means of reducing the energy ‎mismatch between generation and demand could be obtained using such devices. But with the advent of new types of batteries with unique capabilities, choosing the right type of battery used in stand-alone RESs, in terms of technical and economic components including battery life costs, operation costs, and repair and maintenance costs, has become a very important issue. This research tries a significant step forward since previous conducted researches on ‎storage systems are based on oversimplified economic battery models, considering the impact of power generation and consumption, as well as the impact of battery lifetime on battery lifetime-related costs. Considering the battery lifetime feature, multi-objective optimization has been provided to minimize the costs and maximize the useful lifetime of the system through the Teaching-learning-based optimization (TLBO) algorithm. Technical and economic analysis shows that the generation cost of each scattered product varies according to the type of battery optimization and with increasing system useful life, the TCPDBES index system increases. The results illustrate that the battery type selection varies according to the grid-independent lifetime and the ‎use of Lithium-ion battery, Gel Lead Acid battery, and AGM (Absorbent Glass Mat) Lead Acid types has the minimum energy storage cost for 15, 10, and 5 year lifetimes, respectively.‎‎