Abstract
As the distributed generation (DG) in a power supply and the user load demand constantly change in an actual distribution network, multiobjective optimal network reconfiguration considering variations in load and DG has become a major concern, which is important and required to make system operations safe and economical. The aim is to minimize the sum of the active power loss, the sum of the load balancing index and the sum of the maximum node voltage deviation index simultaneously during the reconfiguration period. Here, this article proposes a new Chaos Disturbed Beetle Antennae Search (CDBAS) algorithm to reduce the computational time and solve the multiobjective optimal problem of network reconfiguration. To adopt the Chaos Disturbed Beetle Antennae Search algorithm for solving this multiobjective problem, grey target decision-making technology is used to rank the beetles. Additionally, to the enhance the system static voltage stability and voltage quality, a grey target decision-making model is established to achieve a layer relationship between each index and the switching operation index. The plausibility and effectiveness of the presented methodology is verified on the modified IEEE 33, 69 and 118-Bus Test Radial Distribution Network. Finally, compared with other research methods in the literature, the CDBAS algorithm outperforms other algorithms and produces a quality decision solution.
Highlights
The combination of residential, commercial and industrial loads creates differences and time variabilities on the feeders of a distribution network, which make the operational control of the distribution network very complicated and pose challenges for system safety and economy as well as user comfort
With the aim of adopting the Chaos Disturbed Beetle Antennae Search (CDBAS) algorithm for solving multiobjective optimization problems, a grey target decision-making theory is applied to achieve the power of the beetles, that is for sorting the beetles
EXPERIMENTAL DESIGN 1) BENCHMARK FUNCTIONS To verify the performance of the proposed CDBAS algorithm, 8 benchmark functions are tested in the simulation
Summary
The combination of residential, commercial and industrial loads creates differences and time variabilities on the feeders of a distribution network, which make the operational control of the distribution network very complicated and pose challenges for system safety and economy as well as user comfort. Some studies have focused on providing the multiobjective problem of network reconfiguration with different techniques, such as fuzzy evaluation theory [8]–[10] and cloud theory [11], and all of these approaches can obtain ideal solutions with better objectives [12], [13] These methods, which are subject to uncertainty theory, can improve the quality of the solutions, especially for traditional distribution systems, but they cannot achieve the optimal variability of load and DG for a distribution network. [15], [16] had the same objective and considered the same distributed generation with different techniques but did not address the calculation time, and other authors have studied multiobjective reconfiguration from the aspect of the convergence rate based on the security index to achieve the best result where the number of iterations is an obstacle [17], [18].
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