Development of Novel State Estimation Algorithms for Active Distribution Networks

The increasing penetration of Distributed Generation and emerging smart metering technologies are transforming the distribution networks from passive to active conditions. In such active networks, extensive monitoring and remote control technologies are essential. Therefore, a State Estimation (SE) tool is the core component in future distribution management systems. Extensive research is ongoing with regard to the development of novel Distribution System State Estimation (DSSE) tools for improved network monitoring and control. The novel DSSE tool is required to be scalable to fit into small to large size networks, operable with limited real time measurements and able to execute the computation of large volumes of data in a limited time. This paper proposes and develops a novel scalable DSSE tool that satisfies the requirements for present and future distribution network infrastructure and management systems. The proposed DSSE tool applies an emerging meta-heuristic optimization mechanism known as Differential Evolution Algorithm (DEA). A detailed investigation is performed with various case studies related to expected scenarios of future distribution networks.