Simultaneous sizing and scheduling optimization for PV-wind-battery hybrid systems with a modified battery lifetime model: A high-resolution analysis in China

Abstract

Battery lifetime is a key factor in the optimal design of hybrid renewable energy systems (HRESs). However, the integration of both battery calendar and cycle lifetimes into HRES design optimization poses challenges in achieving high computational efficiency and ensuring global optimality. In this work, a battery lifetime model considering both calendar and cycle lifetimes is adopted for the simultaneous sizing and scheduling optimization of photovoltaics-wind-battery systems. To reduce computational complexity, the nonlinear term originated from the minimum function, which determines the actual battery lifetime as the earlier-reached one of calendar and cycle lifetimes, is reformulated into a mixed integer linear programming framework. This modified model is then applied to conduct HRES design optimization in China, utilizing climate and load data with 0.5° × 0.5° spatial resolution. High-resolution results not only validate the wide applicability and satisfactory computational efficiency of the proposed model, but also underline the economic importance of incorporating both calendar and cycle lifetimes in system design. It is found that lifecycle costs of stand-alone and grid-connected HRESs could be reduced by 5000k CNY and 22,600k CNY in over 50% of the resource-abundant areas in China, respectively. Moreover, it is discovered that costs of HRESs might apparently increase when local maximum consecutive rainy days (MCRD) exceeds 3, suggesting that MCRD could be a useful indicator to assess system feasibility in diverse locations. This work provides efficient tools and valuable insights that could be generalized worldwide to assist investors and governments in the system siting, evaluation and design processes.