Multi-Input Nonlinear Programming Based Deterministic Optimization Framework for Evaluating Microgrids with Optimal Renewable-Storage Energy Mix

Integration of renewable energy sources (RES) in a distribution network facilities the establishment sustainable power systems. Concurrently, incorporation storage system (ESS) plays pivotal role to maintain economical significance as well mitigates technical liabilities associated with uncontrollable and fluctuating output power. Nevertheless, ESS technologies require additional investments that imposes techno-economic challenge selection, allocation sizing ensure reliable is operationally optimized reduced cost. In this paper, deterministic cost-optimization framework presented based on multi-input nonlinear programming optimally solve problem. The optimization performed obviate demand-generation mismatch, violated introduction variable sources. proposed method tested validated an IEEE 24-bus integrated solar wind approach solved using GAMS software considering data one year. Based framework, study also presents various different scenarios mix combination advanced outline for sizing, allocation, selection. optimal results obtained, were obtained lead-acid, lithium-ion, nickel-cadmium sodium-sulfur (NaS) battery system. While all these mitigated mismatch size location. However, NaS technology was found be best among given minimum possible Furthermore, it observed cost hybrid wind-solar lowest overall