Optimal Planning of Distributed Energy Resources in Distribution Microgrid to Improve Resource Owner Profit and Network Resiliency
محورهای موضوعی : smart grid
Soheil Haji Mohammadi
1
(Department of Electrical Engineering, South Tehran Branch, Islamic Azad University,
Tehran, Iran)
Mahmoud Modaresi
2
(Department of Electrical Engineering, South Tehran Branch, Islamic Azad University,
Tehran, Iran)
کلید واژه: Energy storage, independent microgrid, distributed wind generation resources, distributed solar generation resources, biogeography-based algorithm,
چکیده مقاله :
The objective of this study is to strategize the allocation of resources within the distribution microgrid. The primary goals are to diminish active power loss and voltage discrepancies, enhance resilience, decrease the expense of procuring energy from the main network, augment the incorporation of distributed renewable energy sources, and optimize the profitability of integrating distributed generation and storage resources into the power supply. In this article, the microgrid design challenge is approached through the focus on a nonlinear optimization model. The Biogeography-based optimization algorithm is employed to tackle this complex problem. Moreover, the planning solution is crafted to address uncertainties, incorporating factors such as wind speed, solar radiation, and consumption load variability within the distribution network. To validate the efficacy of the proposed methodology, the standard 33-bus test system is scrutinized. The outcomes underscore the remarkable efficiency of the proposed solution, showcasing its potential for practical applications in optimizing microgrid performance.
The objective of this study is to strategize the allocation of resources within the distribution microgrid. The primary goals are to diminish active power loss and voltage discrepancies, enhance resilience, decrease the expense of procuring energy from the main network, augment the incorporation of distributed renewable energy sources, and optimize the profitability of integrating distributed generation and storage resources into the power supply. In this article, the microgrid design challenge is approached through the focus on a nonlinear optimization model. The Biogeography-based optimization algorithm is employed to tackle this complex problem. Moreover, the planning solution is crafted to address uncertainties, incorporating factors such as wind speed, solar radiation, and consumption load variability within the distribution network. To validate the efficacy of the proposed methodology, the standard 33-bus test system is scrutinized. The outcomes underscore the remarkable efficiency of the proposed solution, showcasing its potential for practical applications in optimizing microgrid performance.
