Configuration optimization of distributed PV-storage system in industrial park considering load management

Industrial parks can effectively reduce carbon emissions by installing distributed photovoltaic (PV) power generation. Electrochemical energy storage can be configured to increase the level of green power consumption in parks and help to address source-load power imbalances by managing and analyzing adjustable loads within the parks. Co-optimizing PV and energy storage systems demonstrate key advantages in system configuration, capacity planning, and operational cost reduction. This integrated approach reduces energy expenses while enhancing efficiency, sustainability, and cost-effectiveness in industrial parks. A two-layer co-optimization model for a distributed PV energy storage system is established based on source-load power balance, storage climbing, and power constraints in an industrial park. Based on an industrial park project, this paper solves the proposed model using ILOG CPLEX Optimization Studio (CPLEX) and Genetic Algorithm and calculates the optimal capacity and economic benefits under the strategy of PV power generation and distributed PV energy storage system, by comparing the two scenarios of no-load management and load management. The results indicate that the integration of distributed PV energy storage enhances the economic efficiency of the energy supply in both scenarios. Furthermore, the findings demonstrate that both carbon trading and time-sharing tariffs significantly enhance the system's park economic performance. Through comprehensive optimization, annual carbon emissions are reduced by 20 415.2 tons, the financial net present value increases by 1 553 000 Chinese yuan (CNY), and the overall average annual net cost is reduced by 3 181 000 CNY. This provides valuable reference for promoting clean energy, optimizing energy structure, and enhancing carbon emission reduction capacity.