Abstract

Proper energy storage system design is important for performance improvements in solar power shared building communities. Existing studies have developed various design methods for sizing the distributed batteries and shared batteries. For sizing the distributed batteries, most of the design methods are based on single building energy mismatch, but they neglect the potentials of energy sharing in reducing battery capacity, thereby easily causing battery oversizing problem. For sizing the shared batteries, the existing design methods are based on a community aggregated energy mismatch, which may avoid battery oversizing but cause another severe problem, i.e., excessive electricity losses in the sharing process caused by the long-distance power transmissions. Therefore, this study proposes a hierarchical design method of distributed batteries in solar power shared building communities, with the purpose of reducing the battery capacity and minimizing the energy loss in the sharing process. The developed design method first considers all the distributed batteries as a virtual ‘shared’ battery and searches its optimal capacity using genetic algorithm. Taking the optimized capacity as a constraint, the developed method then optimizes the capacities of the distributed batteries for minimizing the energy loss using non-linear programming. Case studies on a building community show that compared with an existing design method, the proposed design can significantly reduce the battery capacity and electricity loss in the sharing process, i.e. 36.6% capacity reduction and 55% electricity loss reduction. This study integrates the considerations of aggregated energy needs, local PV power sharing, advanced community control, and battery storage sharing, which will be useful to optimize three functions (energy efficiency, energy production and flexibility) in a positive energy district towards energy surplus and climate neutrality.

Highlights

  • Buildings are large energy end-users worldwide [1]

  • Their simulation-based case studies showed that the application of a community energy storage to 100 houses could reduce the levelized cost by 56% by shifting demand compared to a single house energy storage installation

  • This study has proposed a hierarchical design optimization of distributed batteries in solar power shared building community

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Summary

Introduction

Buildings are large energy end-users worldwide [1]. In both E.U. and U.S, above 40% of total primary energy is consumed in the building sector [2]. Parra et al [22] designed a method to calculate the optimal community energy storage (CES) systems for end-user applications based on the levelized cost, which considers round-trip efficiency and durability Their simulation-based case studies showed that the application of a community energy storage to 100 houses could reduce the levelized cost by 56% by shifting demand compared to a single house energy storage installation. This study proposes a hierarchical design method for the distributed batteries in solar PV power shared building community, with the purpose of reducing the required battery capacity by applying energy sharing and minimizing the electricity loss in the energy sharing process. Based on the optimized aggregated capacity at community-level, the developed method optimizes the capacity of the distributed batteries installed in each building using non-linear programming with the objective of minimizing the storage sharing (and the associated power loss due to long-distance power transmission).

Methodology
Basic idea of energy sharing and typical design scenarios
Buildings and system modelling
Case studies and results analysis
Performance comparison of a single building
Findings
Conclusions
Full Text
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