Solutions for energy losses reduction in power networks with renewable energy sources

Abagiu, Sorin; Lepadat, Ionel; Helerea, Elena

doi:10.1109/icate.2016.7754635

Cited by 10 publications

(5 citation statements)

References 6 publications

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“…If yes, output the result. If not, proceed to step (6). (6) The iteration number t = t + 1 and return to step (2).…”

Section: Implementation Of Line Loss Optimization Algorithmmentioning

confidence: 99%

“…Existing research on PV access into distribution systems mainly focuses on modeling of distributed PVs and their impact on distribution networks, as well as site selection and capacity determination of distributed PVs [4,5]. Abagiu et al [6] analyzes the influencing factors of grid-connected PV power plants and establishes the simulation model. The result points out that when the connected and operated PV power plant reaches the rated voltage level, the power loss of the distribution network will decrease, and the minimum power loss can be achieved by controlling the terminal voltage of the transformer.…”

Section: Introductionmentioning

confidence: 99%

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Line Loss Calculation and Optimization in Low Voltage Lines with Photovoltaic Systems Using an Analytical Model and Quantum Genetic Algorithm

2024

Teh. vjesn.

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With the increasing integration of distributed photovoltaic (PV) generation into distribution networks, challenges such as power reverse flow and high line losses have emerged, leading to greater uncertainty in power systems. To address these issues, this paper presents an analytical model for calculating line losses in low-voltage distribution networks with PV generation, utilizing power flow calculations. A simulation model of a 15 node low-voltage network is developed using SIMULINK to validate the accuracy of the analytical model under the scenario of uniform load distribution (ULD). Additionally, a line loss optimization algorithm based on quantum genetic algorithms (QGA) is proposed for low-voltage distribution networks with distributed PV generation, along with an optimization model. The objective function of the optimization model is based on the reduction in line losses resulting from the integration of the PV system. The example results demonstrate the consistency between the line loss optimization using QGA and the analytical results, highlighting the significant advantages of QGA in terms of speed and accuracy. This research provides valuable insights for line loss optimization in low-voltage distribution networks with distributed PV generation and serves as a theoretical reference for future studies in this field.

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“…If yes, output the result. If not, proceed to step (6). (6) The iteration number t = t + 1 and return to step (2).…”

Section: Implementation Of Line Loss Optimization Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Line Loss Calculation and Optimization in Low Voltage Lines with Photovoltaic Systems Using an Analytical Model and Quantum Genetic Algorithm

2024

Teh. vjesn.

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“…In addition, if the nodal admittance matrix ( 6) is substituted into (7), the results of ( 8) and ( 9) yield the following:…”

Section: Load Flow Analysismentioning

confidence: 99%

“…On the other hand, given the policies implemented by the regulatory entities of the electrical sector, the values regarding energy losses in distribution networks must be continuously reduced by utilities to improve the quality, and the distribution efficiency of electrical energy [6,7]. To this effect, utilities need to design efficient maintenance and operation plans that allow for reaching the expected energy losses with minimal investment costs [8,9].…”

Section: Introduction 1general Context and Motivationmentioning

confidence: 99%

Optimal Phase-Balancing in Three-Phase Distribution Networks Considering Shunt Reactive Power Compensation with Fixed-Step Capacitor Banks

2022

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The black hole optimization (BHO) method is applied in this research to solve the problem of the optimal reactive power compensation with fixed-step capacitor banks in three-phase networks considering the phase-balancing problem simultaneously. A master–slave optimization approach based on the BHO in the master stage considers a discrete codification and the successive approximation power flow method in the slave stage. Two different evaluations are proposed to measure the impact of the shunt reactive power compensation and the phase-balancing strategies. These evaluations include a cascade solution methodology (CSM) approach and a simultaneous solution methodology (SSM). The CSM approach solves the phase-balancing problem in the first stage. This solution is implemented in the distribution network to determine the fixed-step capacitor banks installed in the second stage. In the SSM, both problems are solved using a unique codification vector. Numerical results in the IEEE 8- and IEEE 27-bus systems demonstrate the effectiveness of the proposed solution methodology, where the SSM presents the better numerical results in both test feeders with reductions of about 32.27% and 33.52%, respectively, when compared with the CSM. To validate all the numerical achievements in the MATLAB programming environment, the DIgSILENT software was used for making cross-validations. Note that the selection of the DIgISLENT software is based on its wide recognition in the scientific literature and industry for making quasi-experimental validations as a previous stage to the physical implementation of any grid intervention in power and distribution networks.

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“…Owing to economic restrictions, investment distribution networks are typically constructed with radial configurations since this allows reducing inversion in the infrastructure, simplifying also the protective devices' coordination [3]. However, the radial structure of these systems implies that they experience high power and energy losses when compared with transmission systems, being that the energy losses in these grids are between 6% and 18% of the total power input at the substation bus, while in transmissions networks, these are between 1.5% and 2.0% [4,5].…”

Section: Introductionmentioning

confidence: 99%

An Approximate Mixed-Integer Convex Model to Reduce Annual Operating Costs in Radial Distribution Networks Using STATCOMs

2021

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The problem of optimal siting and sizing of distribution static compensators (STATCOMs) is addressed in this research from the point of view of exact mathematical optimization. The exact mixed-integer nonlinear programming model (MINLP) is decoupled into two convex optimization sub-problems, named the location problem and the sizing problem. The location problem is addressed by relaxing the exact MINLP model, assuming that all the voltages are equal to 1∠0∘, which allows obtaining a mixed-integer quadratic programming model as a function of the active and reactive power flows. The solution of this model provides the best set of nodes to locate all the STATCOMs. When all the nodes are selected, it solves the optimal reactive power problem through a second-order cone programming relaxation of the exact optimal power flow problem; the solution of the SOCP model provides the optimal sizes of the STATCOMs. Finally, it refines the exact objective function value due to the intrinsic non-convexities associated with the costs of the STATCOMs that were relaxed through the application of Taylor’s series expansion in the location and sizing stages. The numerical results in the IEEE 33- and 69-bus systems demonstrate the effectiveness and robustness of the proposed optimization problem when compared with large-scale MINLP solvers in GAMS and the discrete-continuous version of the vortex search algorithm (DCVSA) recently reported in the current literature. With respect to the benchmark cases of the test feeders, the proposed approach reaches the best reductions with 14.17% and 15.79% in the annual operative costs, which improves the solutions of the DCVSA, which are 13.71% and 15.30%, respectively.

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Solutions for energy losses reduction in power networks with renewable energy sources

Cited by 10 publications

References 6 publications

Line Loss Calculation and Optimization in Low Voltage Lines with Photovoltaic Systems Using an Analytical Model and Quantum Genetic Algorithm

Line Loss Calculation and Optimization in Low Voltage Lines with Photovoltaic Systems Using an Analytical Model and Quantum Genetic Algorithm

Optimal Phase-Balancing in Three-Phase Distribution Networks Considering Shunt Reactive Power Compensation with Fixed-Step Capacitor Banks

An Approximate Mixed-Integer Convex Model to Reduce Annual Operating Costs in Radial Distribution Networks Using STATCOMs

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