A Quadratic Formulation of ESS Degradation and Optimal DC Microgrid Operation Strategy Using Quadratic Programming

Abstract

Microgrids are fundamental elements in modern energy systems. Among the various microgrid components, the Energy Storage System (ESS) plays a pivotal role in ensuring system reliability, but its high cost and inevitable degradation over time pose significant challenges. Many current studies overlook the impact of ESS degradation on operational optimization, potentially leading to cost-ineffective systems. To address this gap, we introduce a quadratic ESS degradation model that captures intricate battery dynamics, such as State of Charge (SoC) and Depth of Discharge (DoD), using Markovian properties. Based on this model, we propose an optimal energy management framework for DC microgrids using Quadratic Programming (QP). The objective is to minimize the combined costs of degradation and electricity, considering the Time-of-Use (ToU) tariff while adhering to ESS constraints. This financially focused approach provides a pragmatic and economically aligned optimization strategy. Testing across various State of Health (SoH) scenarios demonstrates that our proposed model reduces total operational costs by 3-18%. This research advances microgrid optimization techniques and offers practical insights to enhance efficiency and economic resilience in real-world scenarios.

Keywords

• Energy storage system
• microgrid
• battery degradation
• electricity cost
• quadratic programming