Multi-objective distributed generation integration in radial distribution system using modified neural network algorithm

This paper introduces a new approach based on a chaotic strategy and a neural network algorithm (NNA), called chaotic-based NNA (CNNA), to solve the optimal distributed generation allocation (ODGA), in the radial distribution system (RDS). This consists of determining the optimal locations and sizes of one or several distributed generations (DGs) to be inserted into the RDS to minimize one or multiple objectives while meeting a set of security limits. The robustness of the proposed method is demonstrated by applying it to two different typical RDSs, namely IEEE 33-bus and 69-bus. In this regard, simulations are performed for three DGs in the cases of unity power factor (UPF) and optimal power factor (OPF), considering single and multi-objective optimization, by minimizing the total active losses and improving the voltage profile, voltage deviation (VD) and voltage stability index (VSI). Compared to its original version and recently reported methods, the CNNA solutions are more competitive without increasing the complexity of the optimization algorithm, especially when the RDS size and problem dimension are extended

A review of optimal planning active distribution system:Models, methods, and future researches

Due to the widespread deployment of distributed energy resources (DERs) and the liberalization of electricity market, traditional distribution networks are undergoing a transition to active distribution systems (ADSs), and the traditional deterministic planning methods have become unsuitable under the high penetration of DERs. Aiming to develop appropriate models and methodologies for the planning of ADSs, the key features of ADS planning problem are analyzed from the different perspectives, such as the allocation of DGs and ESS, coupling of operation and planning, and high-level uncertainties. Based on these analyses, this comprehensive literature review summarizes the latest research and development associated with ADS planning. The planning models and methods proposed in these research works are analyzed and categorized from different perspectives including objectives, decision variables, constraint conditions, and solving algorithms. The key theoretical issues and challenges of ADS planning are extracted and discussed. Meanwhile, emphasis is also given to the suitable suggestions to deal with these abovementioned issues based on the available literature and comparisons between them. Finally, several important research prospects are recommended for further research in ADS planning field, such as planning with multiple micro-grids (MGs), collaborative planning between ADSs and information communication system (ICS), and planning from different perspectives of multi-stakeholders

Modified Genetic Algorithm To Determine The Location Of The Distribution Power Supply Networks In The City

The problem of combinatorial optimization in relation to the choice of location of power supplies in solving the problem of development of urban power distribution networks is considered. Two methods of placing power supplies and securing consumers for them have been developed to solve this problem. The first developed method is to place power supplies of the same size, and the second - different sizes. The fundamental difference between the created methods and the existing ones is that the proposed methods take into account all the material of the task and have specialized ways to encode possible solutions, modified crossbreeding and selection operators. Proposed methods effectively address the problem of low inheritance, topological impracticability of the found solutions, as a result of which the execution time was significantly reduced and the accuracy of calculations increased. In the developed methods the absence of the account of restrictions on placement of new power supplies which has allowed to solve a problem of application of methods for a narrow range of tasks is realized. A comparative analysis of the results obtained by placing power supplies of the same size and known methods was performed, and it was found that the developed method works faster than known methods. It is shown that the proposed approach provides a stable convergence of the search process for an acceptable number of steps without artificially limiting the search space and the use of additional expert information on the feasibility of possible solutions. The obtained results allow to offer effective methods for improving the quality of decisions made on the choice of location of power supply facilities in the design of urban electricit