Optimal Measurement Placement for Power System State Estimation Using Hybrid Genetic Algorithm and Simulated Annealing

Kerdchuen, Kaan; Ongsakul, Weerakorn

doi:10.1109/icpst.2006.321730

Cited by 11 publications

(4 citation statements)

References 12 publications

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“…In future work, more recent trends in optimization techniques may be applied in the optimization phase of the methodological framework proposed in this study. These classes of methods include hybrid heuristic optimization algorithms [51,52] and multiobjective evolutionary algorithms [53,54].…”

Section: Techno-economic and Emissions Analysis Resultsmentioning

confidence: 99%

Optimal Sizing and Techno-Economic Analysis of Hybrid Renewable Energy Systems—A Case Study of a Photovoltaic/Wind/Battery/Diesel System in Fanisau, Northern Nigeria

et al. 2020

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Hybrid Renewable Energy Systems (HRESs) have been touted as an appropriate way for supplying electricity to remote and off-grid areas in developing countries, especially in sub-Saharan Africa (SSA), where rural electrification challenges are the most pronounced. This study proposes a two-step methodology for optimizing and analyzing a stand-alone photovoltaic/wind/battery/diesel hybrid system to meet the electricity needs of Fanisua, an off-grid and remote village of northern Nigeria. In the first step, the MATLAB environment was used to run simulations and optimize the system via the genetic algorithm. Then, techno-economic and emissions analysis was carried out in the second step to compare the proposed system to the existing traditional modes of rural electrification in sub-Saharan Africa, namely, the grid-extension and diesel generator. The break-even distance parameter was adopted in the comparison with grid-extension. Besides, the hypothetical project of replacing the diesel generator by the optimal system was analyzed using the Simple Payback Period (SPP) and Net Present Value (NPV) parameters. The resulting optimal design architecture included an 89.271-kW photovoltaic array, a 100.31-W diesel generator, and 148 batteries with a total annualized cost (TAC) and cost of energy (COE) of USD 43,807 and USD 0.25/kWh, respectively. The break-even distance found was 16.2 km, while the NPV and SPP of the hypothetical project were USD 572,382 and 2.8 years, respectively. The savings in carbon dioxide (CO2) emissions of the proposed system compared to the grid extension and the diesel generator were found to be 85,401.08 kg/year and 122,062.85 kg/year, respectively. This study highlighted the role that solar PV-based HRESs could play in the sustainable electricity supply in rural areas of sub-Saharan Africa.

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Section: Techno-economic and Emissions Analysis Resultsmentioning

confidence: 99%

Optimal Sizing and Techno-Economic Analysis of Hybrid Renewable Energy Systems—A Case Study of a Photovoltaic/Wind/Battery/Diesel System in Fanisau, Northern Nigeria

et al. 2020

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“…The author in [43] proposed a modified SAM in which a new perturb function is implemented to increase the randomness and increase the probability of determining OPPP solutions. Various improvements to SAM have been suggested to dates, such as pragmatic multi-stage SAM [56], novel multi-stage SAM [57], hybrid SAM [58], and hybrid genetic algorithm and SAM [59] to escalate the prospect of SAM for determination of the global solution within a reasonable timeframe. But stochastic and local search combination will make it still hard to find the best global solution for OPPP for every modified SAM.…”

Section: Simulated Annealing Methodsmentioning

confidence: 99%

Modified branch‐and‐bound algorithm for unravelling optimal PMU placement problem for power grid observability: A comparative analysis

Babu¹,

Raj

Dey

et al. 2021

CAAI Trans on Intel Tech

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Safe operation of the power grid requires a complete and robust control network to ensure full observability. However, redundancy measurements can create problems in expense, management, and control. The optimal phasor measurement unit (PMU) positioning problem (OPPP) is proposed to limit the number of PMUs deployed in the power grid and ensure the whole grid's observability in the meantime. A modified branchand-bound algorithm (MBBA) to unravel the OPPP is presented. Original BBA, which uses a single search order to create a binary tree, gives only one solution to the OPPP, although more than one optimal solution exists. The proposed MBBA method consists of two different stages: the vertexes in the search tree are investigated by depth-first search (DFS) in stage 1, and the search route continues as the breadth-first search. In stage 1, the LP relaxing problems are solved by dual simplex, and in stage 2, the basic viable solution from stage 1 is used to configure the primary simplex until the optimum solution is found. OPPP is formulated as a binary decision variable MBBA model, minimizing linear objective function subject to linear matrix observability constraints. The MBBA model is unravelled using a linear integer-based external approximation scheme. IEEE test systems are used to check the feasibility of the proposed approach. Matlab software performs simulation based on a number of graph theory-based methods such as DFS, graphtheoretical method, simulated annealing, and recursive N-algorithms. These algorithms are compared to the algorithmic perspective of the proposed MBBA method. IEEE test network results confirm the validity of the proposed methodology.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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“…The P À h observable concept is used to check the network observability. The test results indicated that GA/ SA is superior to TS, GA and SA in terms of higher frequency of the best fit and faster computational time [20]. In [21] was presented the comparison between the original PSO and the GA when solving power system state estimation.…”

Section: Introductionmentioning

confidence: 98%

Power system state estimation solution using modified models of PSO algorithm: Comparative study

2016

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Optimal Measurement Placement for Power System State Estimation Using Hybrid Genetic Algorithm and Simulated Annealing

Cited by 11 publications

References 12 publications

Optimal Sizing and Techno-Economic Analysis of Hybrid Renewable Energy Systems—A Case Study of a Photovoltaic/Wind/Battery/Diesel System in Fanisau, Northern Nigeria

Optimal Sizing and Techno-Economic Analysis of Hybrid Renewable Energy Systems—A Case Study of a Photovoltaic/Wind/Battery/Diesel System in Fanisau, Northern Nigeria

Modified branch‐and‐bound algorithm for unravelling optimal PMU placement problem for power grid observability: A comparative analysis

Power system state estimation solution using modified models of PSO algorithm: Comparative study

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