一种考虑天气条件的分布式电源选址定容与配电网开关协调的概率型温变模型

Optimally siting distributed generations (DGs) and appropriately switching of distribution lines are regarded as the most effective mechanisms for loss mitigation in a distribution network. Power loss curtailment in distribution networks is very essential in power system operation and management since it constitutes the major share of the overall power loss in power systems. Losses in power systems lead to exorbitant network operation costs as well as the distortion of the system's voltage profile. In traditional DG placement and network switching (reconfiguration) mechanisms, the optimal locations and the number of distributed generators and state of switches are optimally determined for ensuring that losses are reduced to the barest minimum in order to meet the power demand of consumers. Load variation in distribution buses leads to different resultant losses in comparison with constant loads. Nevertheless, most of the proposed models for DG allocation and network switching problem have ignored consumers' load variability. While the selected few that considered load variation in their proposed models neglected the impact of ambient temperature change and weather conditions on electrical energy demand and thermal rating of lines which influence appropriate places and DG number, as well as optimal switching plans. Accordingly, the current study evaluates environment's temperature and weather conditions changes impacts on DG allocation and switching solutions to assess environmental temperature and conditions change importance in loss optimization via DG placement and network reconfiguration. In the 16-bus system, the network topology and DG arrangement change with just a 10% rise in environmental temperature. The actual grid of Koprivnica demonstrates greater resilience to temperature increases, maintaining a stable network configuration under various temperature variations. In the 84-bus network, the maximum CPU time is less than 27 seconds, indicating the applicability of the proposed approach to large-scale and real-world networks. From the simulation results, the lost power is influenced by heat degree increment for all test systems. In total, it is observed that ambient temperature, solar irradiation, and wind speed variations significantly change the appropriate places and DG sources number and switching combination.