Multi objective optimization approaches for solar photovoltaic inverter control and energy balance in a smart grid environment

Abstract

Placement of distributed generation in electrical distribution system is a critical newlineaspect of optimizing grid performance and ensuring effcient integration of renewable energy sources. Renewable based sources must be properly positioned and sized to avoid bidirectional power and#64258;ows, voltage/frequency and#64258;uctuations and performance degradation. Solar Photovoltaic Systems and Wind Turbines are potentially becoming the preferred renewable energy based, distribution generation sources. Precise control mechanisms like advanced inverter strategies and direct load control are crucial for regulating voltage, frequency and reactive power output, thereby optimizing grid operation and maximizing integration benefts from these sources. However, optimizing the allocation and operation of these systems in grid connected and islanded modes, particularly in radially confgured systems, requires addressing algorithmic challenges, problems related to nonlinear optimization, newlinevariable generations and load variations. To effectively allocate these systems in the newlineelectrical distribution system, advanced optimization techniques capable of newlinehandling multi-objective, nonlinear problems are needed. Similarly, optimizing the power factor of the distributed generation sources and optimizing the load factor in these systems demand adaptive algorithms that can manage nonlinear objectives and dynamic system conditions. In response to the above research questions, this study focuses on determining the optimal placement and sizing of the distributed generation sources in the electrical distribution system with the objective to minimize real power loss and improve voltage stability. Learning enthusiasm based teaching learning based optimization algorithm has been employed for location selection and sizing optimization. The effectiveness of the proposed approach is validated on standard IEEE 33-bus and newline69-bus test systems, demonstrating decreased distribution losses and improved voltage stability.