Decentralized Stochastic Optimal Power Flow Problem Considering Prohibited Operating Zones and Renewables Sources

The traditional Optimal Power Flow (OPF) problem is formulated in a centralized manner assuming a single operator manager has full access to the system information. However, transmission power systems often consist of interconnected areas controlled by multiple regional operators who can only access local information and must coordinate with neighboring areas, sharing limited data like voltage magnitude and angle at tie-lines. In this work, the decentralized OPF problem is extended by including prohibited operational zones (POZ) constraints of thermoelectrical units and formulated as a mixed-integer nonlinear programming model. Uncertainties in load behavior and renewable energy sources are addressed using a stochastic scenario-based approach. A matheuristic algorithm based on the variable neighborhood descent heuristic method is used to handle the integer variables. The proposed model and solution technique are applied in the IEEE 118-bus system, considering the local weather conditions. The obtained results demonstrate the good quality and performance of the proposed model and solution technique compared with the solution of the OPF problem considering a centralized approach.

Palavras-chave

Decentralized power systems operation, matheuristic optimization, optimal power flow (OPF), prohibited operating zones (POZ), renewable energy sources