Aplicação de algoritmos evolutivos na alocação de recursos energéticos distribuídos
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Universidade Federal de Goiás
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This study investigates the integration of distributed generation and energy storage systems
in medium-voltage electrical networks. The proposed approach involves the development
of evolutionary algorithms to optimally determine connection points for various loads and
provide the optimal active power injections from multiple generating units at different
network locations. The allocation of Distributed Energy Resources (DERs) in Power
Systems presents an intrinsic balance between benefits and challenges. Among the benefits,
significant reductions in electrical losses, attraction of investments in the energy sector,
diversification and expansion of the energy matrix with a focus on renewable sources, and
positive socioeconomic impacts, such as job creation, stand out. However, challenges include
difficulties related to system usage tariffs, the need for revisions in operational procedures,
uncontrolled voltage profile elevation in cases of high penetration of arbitrarily allocated
DERs, increased short-circuit levels, and compromised performance of protection systems.
The optimization model formulation adopted the minimization of total active power losses
in the system as its objective function. The study considered solar-based distributed
generation and battery storage systems for simulations. Network operating conditions
were analyzed using power flow studies of the base case. The developed algorithms were
applied to two test systems: the IEEE 34-bus system and the Real Feeder System PD004.
The results highlight the efficiency, robustness, and rapid convergence of the Hybrid
Genetic Algorithm (HGA) compared to other implemented approaches, demonstrating its
superiority in solving the problem. The developed computational tool shows significant
practical potential for application in electric utility companies, serving as a strategic tool
for distribution network planning. Utilizing the algorithm’s results enables the optimized
connection of generating units and loads while respecting established generation limits.
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Algoritmos genéticos, Estratégias evolutivas, Geração distribuída, Recursos energéticos distribuídos, Sistemas de armazenamento de energia, Sistemas elétricos de potência, Genetic algorithms, Evolutionary strategies, Distributed generation, Distributed energy resources, Energy storage systems, Power systems