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Published in:
25-04-2024 | Original Paper
A multi-objective approach for optimal placement of renewable energy sources, voltage regulators and capacitors in radial unbalanced distribution systems
Authors: Lavanya Arubolu, Ravindra Kollu, Ramalinga Raju Manyala
Published in: Electrical Engineering | Issue 6/2024
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Abstract
The article introduces a comprehensive multi-objective approach for the optimal placement of renewable energy sources, voltage regulators, and capacitors in unbalanced radial distribution systems. It addresses the challenges posed by unbalanced loading and higher R/X ratios, which contribute to increased power loss and poor voltage profiles. The study reviews existing methods for optimizing distributed generation (DG) placement and identifies gaps in current approaches. The proposed method employs the Pareto Multi-objective Back Track Search Algorithm (PMBSA) to minimize total power loss, cumulative voltage deviation, voltage stability index, and total cost. The approach also considers the probabilistic nature of generation and load, making it more robust and accurate. The article compares the results of PMBSA with those obtained using standard non-dominated sorting genetic algorithm-II (NSGA-II) and weighted sum approach (WSA). Additionally, it highlights the importance of addressing voltage limit violations and improving voltage stability margins through the strategic placement of automatic voltage regulators (AVRs) and shunt capacitor banks. The study is organized into eight sections, including data resources, RES and AVR modeling, problem formulation, PMBSA overview, results, and conclusions. The detailed analysis and comparison of methods make this article a valuable resource for professionals seeking to optimize the integration of renewable energy sources in unbalanced distribution systems.
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Abstract
There are various challenges in integrating renewable energy sources (RES) into unbalanced distribution systems (UDS) due to the varying nature of loads and RES, as well as the degree of unbalance of the distribution systems. The challenges involved are modelling RES and loads and integrating these models into the complex power flow analysis of UDS. Most of the previous studies either focused on RES allocation in balanced distribution systems or RES allocation in UDS ignoring the varying nature of generation and load which could undermine or overestimate the potential benefits of RES allocation. Hence, in this work, a new approach for allocating photovoltaic and wind energy sources optimally in UDS considering varying nature of load and generation is proposed. The proposed approach employs pareto front-based multi-objective backtracking search algorithm (PMBSA) to get the best optimal size and location of RES by choosing minimisation of total real power loss (TPL), cumulative voltage deviation (CVD), voltage stability index (VSI) and total cost (TC) as objectives. Additionally, optimal allocation of automatic voltage regulators (AVR) and shunt capacitors is done in case there are any voltage limit violation problems. A probabilistic technique is employed to account for the time-varying nature of RES and load while solving optimal RES allocation problem. PMBSA is used in this work and interfaced with OpenDSS software to solve the UDS power flow problem. The proposed approach is implemented on IEEE 13-bus and 123-bus UDS, and the results indicate that, when PV and wind energy sources are optimally placed in a 123-node UDS, total cost, VSI index, power loss, and CVD reduce by 32.2%, 28.7%, 31.22%, and 4.5%, respectively, whereas when the traditional weighted sum approach is used for optimal allocation of RES, total cost, VSI index, power loss, and CVD reduce by 22.5%, 21.62%, 33.14%, and 3.33%, respectively, indicating the efficacy of the proposed approach.
