The improvement of energy efficiency plays an important role to ensure sustainable electrical operation in large-scale buildings. In relation to the low-cost electrical components, a capacitor is an electrical component that can be used to sustain or improve the operating performance of an unbalanced electrical system in large-scale buildings so that energy efficiency improvement can be obtained. This is important to overcome the ineffective utilization of energy caused by the occurrence of power losses in an unbalanced electrical system of large-scale buildings. Further improvement of energy efficiency can be obtained by reducing an excessive amount of incoming power through the determination of tap setting for incoming transformer, and this is classified under the concept of conservative voltage regulation (CVR) approach. In order to solve the problem, the optimal capacitor placement and sizing (OCPS) with CVR is introduced as a new approach for energy efficiency improvement while ensuring a sustainable operation in an unbalanced electrical system of large-scale buildings. The proposed technique utilizes the artificial intelligence (AI) based differential evolution particle swarm optimization (DEPSO) technique with the objective function of total cost minimization for the real power losses, real power consumption, and capacitors installation. The effectiveness of the proposed technique to achieve energy efficiency improvement is investigated through a case study of an unbalanced electrical system in a large-scale office building. The significance of the research output is related to its low-cost technology that has the potential for a comprehensive, pragmatic implementation in large-scale buildings, and subsequently, it will significantly accelerate the increase of national agenda in energy efficiency.
Thyristor-controlled switch capacitor placement in large-scale power systems via mixed integer linear programming and Taylor series expansion
