Abstract
Integration of renewable energy sources (RES) in a distribution network facilities the establishment of sustainable power systems. Concurrently, the incorporation of energy storage system (ESS) plays a pivotal role to maintain the economical significance as well as mitigates the technical liabilities associated with uncontrollable and fluctuating renewable output power. Nevertheless, ESS technologies require additional investments that imposes a techno-economic challenge of selection, allocation and sizing to ensure a reliable power system that is operationally optimized with reduced cost. In this paper, a deterministic cost-optimization framework is presented based on a multi-input nonlinear programming to optimally solve the sizing and allocation problem. The optimization is performed to obviate the demand-generation mismatch, that is violated with the introduction of variable renewable energy sources. The proposed optimization method is tested and validated on an IEEE 24-bus network integrated with solar and wind energy sources. The deterministic approach is solved using GAMS optimization software considering the system data of one year. Based on the optimization framework, the study also presents various different scenarios of renewable energy mix in combination with advanced ESS technologies to outline an technical as well as economical framework for ESS sizing, allocation, and selection. Based on the optimal results obtained, the optimal sizing and allocation were obtained for lead-acid, lithium-ion, nickel-cadmium and sodium-sulfur (NaS) battery energy storage system. While all these storage technologies mitigated the demand-generation mismatch with optimal size and location. However, the NaS storage technology was found to be the best among the given storage technologies for the given system minimum possible cost. Furthermore, it was observed that the cost of hybrid wind-solar mix system results in the lowest overall cost.
Highlights
A cost optimization technique using a deterministic approach based on multi-input non linear programming is proposed to optimize the sizing and allocation of energy storage systems
This study comprehensively articulates the impact of the renewable energy mix on the cost optimization problem for various energy storage system that is pertinent at planning phase during the initial stages of sustainable energy development in the electricity sector
Numerous renewable generation scenarios are considered in this study and the optimization problem is solved using GAMS software
Summary
Depending on the characteristics battery usage, that is determined based on the depth of discharge [13], the authors presented a multi-constrained and multi-objective optimization of the entire renewable integrated power grid with optimal allocation and size for RES as well as ESS. This derivation of the “cost of use” can be further implemented for economic optimization of renewable-battery coupled multi-energy [14]. We formulate a cost optimization framework of energy storage system to achieve optimal sizing and allocation based on a deterministic multi-input non linear programming (MINLP) technique that aims to mitigate the demand-generation mismatch.
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