TY  - EJOU
AU  - Luo, Xiaole 
AU  - Lan, Haitao 
AU  - Song, Yang 
AU  - Zhao, Yunliang 
AU  - Bai, Yingnan 
AU  - Yang, Yinan 
AU  - Peng, Haichao 
AU  - Wang, Xiaojing 

TI  - Distributionally Robust Co-Optimization of Rural PV-Storage Distribution Networks Incorporating Adjustable Agricultural Load Characteristics
T2  - Energy Engineering

PY  - 
VL  - 
IS  - 
SN  - 1546-0118

AB  - Rural distribution networks are experiencing increasing integration of distributed photovoltaic (PV) generation, yet the inherent intermittency of PV output and the pronounced peak-valley disparities of agricultural loads pose significant challenges to grid economy and security. To address photovoltaic (PV) fluctuations and agricultural load peak-valley disparities in rural distribution networks, this paper proposes a distributionally robust cooperative planning method integrating load elasticity. Firstly, a refined agricultural load model is established: irrigation loads couple pump head-flow characteristics with load shifting mechanisms; greenhouse loads incorporate curtailable heating and temperature-light constraints; production loads combine time-shiftable machinery charging with rigid sensor demands. A two-stage distributionally robust optimization model is then formulated to minimize total investment-operation costs under PV uncertainty, innovatively embedding the CMA-ES algorithm for coordinated electricity consumption strategy optimization. Simulations on a modified IEEE 33-node system demonstrate: compared to conventional planning, the proposed method reduces total costs by 15.6% and mitigates peak-valley differences by 28.5% while maintaining voltage deviations within 1.04–1.05 p.u., verifying the synergy of distributed PV-storage systems and load elasticity.
KW  - Load elasticity; distributed PV-storage; distributionally robust optimization; rural distribution network; CMA-ES algorithm

DO  - 10.32604/ee.2026.079356