Abstract
One of the challenges which the electrical power industry has been facing nowadays is the adaptation of the power system to the energy transition which has been taking place before our very eyes. With the increasing share of Renewable Energy Sources (RES) in energy production, the development of electromobility and the increasing environmental awareness of the society, the power system must constantly evolve to meet its expectations regarding a reliable electricity supply. This paper presents the issue of deploying energy storage facilities in the meshed power distribution network in order to reduce transmission losses. The presented multi-objective approach provides an opportunity to solve this issue using multi-objective optimisation methods such as Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multiobjective Particle Swarm Optimization (MPSO) and Biased Random Keys Genetic Algorithm (BRKGA). In order to increase the efficiency optimisation process, the Pareto Adaptive ϵ-dominance (paϵ-dominance) was used. It was demonstrated that the use of energy storages that cooperate with RES can significantly reduce transmission losses.
Highlights
The role of the power system is the continuous generation and supply of electricity to recipients, ensuring the appropriate quality parameters
In order to determine the quality of the solutions obtained through the used optimisation methods, all the found non-dominated solutions were collected into single set
The paper has demonstrated that evolutionary multi-objective optimisation methods are an effective tool in determining the location of BESS in the power system to minimise transmission losses
Summary
The role of the power system is the continuous generation and supply of electricity to recipients, ensuring the appropriate quality parameters. The optimisation of the location and size of the respective generating units was performed in such a way as to limit transmission losses and increase system reliability Despite their advantages, the stochastic changes in weather conditions mean that solar and wind energy sources are characterised by unpredictability and uncontrollability. In order to search for an appropriate solution, analysis using the modified particle swarm method MPSO was adopted This way, minimisation of fuel purchase costs and transmission losses was achieved. In the papers described above, the allocation of storages in the power system is treated as a multi-objective problem, in which one of the optimisation objectives is the minimisation of energy losses.
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