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Optimal distributed generation and shunt capacitor bank placement in microgrid distribution planning for enhanced performance

  • Binaya Kumar Malika,
  • Vivekananda Pattanaik,
  • Binod Kumar Sahu,
  • Pravat Kumar Rout,
  • Subhasis Panda,
  • Mohit Bajaj

摘要

The transformation of traditional power distribution networks with the emerging technological revolution of communication technology, semiconductor devices and information technology according to the concept of smart grid and microgrid strategic planning leads to a better system in terms of reliability, cost-effectiveness, robustness and high efficiency. However, among many influential factors, proper distributed generation (DGs) and capacitor placement during the planning stage are vital in bringing efficient power handling capability considering all the system constraints. With this motivation, this paper proposed an enhanced differential evolution-based metaheuristic approach (EDE) for the optimal sitting of DGs and shunt capacitor banks (SCBs) in microgrid radial distribution systems. A single-objective formulation has been taken based on the real power loss minimization meeting the rise of power demand, considering the enhancement of the voltage profile and stability as other priorities. Various equality and inequality system operational constraints are considered in the formulation to make the approach practicable for real-time condition application. In addition to the above, the approach is tested through simulation under different operating conditions related to the power factor variation, load angle variations, types of DGs and loads. Extensive comparative analysis has been done for the IEEE 33-bus and 69-bus, along with other prominent methods suggested by various authors recently. It is observed that the proposed approach exhibits a substantial reduction in active power loss for both the 33-bus and 69-bus systems. The numerical results reflect that the proposed approach effectively handles large and complex optimization problems concerning distribution system planning.