A distributed population games algorithm is proposed to solve the dispatch problem in microgrids to respond dynamically to the requirements of the system. This study extends the distributed replicator dynamics (RD) al...
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A distributed population games algorithm is proposed to solve the dispatch problem in microgrids to respond dynamically to the requirements of the system. This study extends the distributed replicator dynamics (RD) algorithm, it has four main contributions. First, the authors apply the distributed RD to a distributed generator dispatch over a communication topology in a microgrid test system. Second, they consider power losses of the networked microgrid on the distributed RD. Third, they propose an algorithm to estimate robust loss coefficients of the network considering different demand patterns through a combination of two heuristic optimisation algorithms. Finally, the uncertainties of wind power are considered as a renewable generation integration case. The simulation results show that the proposed distributed control algorithm of a microgrid is able to integrate the economic dispatch problem with frequency control considering the entire network topology.
This study presents a comprehensive approach to tackle the problem of optimal placement and coordinated tuning of power system supplementary damping controllers (OPCTSDC). The approach uses a recursive framework compr...
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This study presents a comprehensive approach to tackle the problem of optimal placement and coordinated tuning of power system supplementary damping controllers (OPCTSDC). The approach uses a recursive framework comprising probabilistic eigenanalysis (PE), a scenario selection technique (SST) and a new variant of mean-variance mapping optimisation algorithm (MVMO-SM). Based on probabilistic models used to sample a wide range of operating conditions, PE is applied to determine the instability risk because of poorly-damped oscillatory modes. Next, the insights gathered from PE are exploited by SST, which combines principal component analysis and fuzzy c-means clustering algorithm to extract a reduced subset of representative scenarios. The multi-scenario formulation of OPCTSDC is then solved by MVMO-SM. A case study on the New England test system, which includes performance comparisons between different modern heuristic optimisation algorithms, illustrates the feasibility and effectiveness of the proposed approach.
Since last few decades, a lot of work has been done on the evolutionary techniques to solve the optimisation problems. With the time passes, these techniques were modified, and also new algorithms were introduced to i...
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Since last few decades, a lot of work has been done on the evolutionary techniques to solve the optimisation problems. With the time passes, these techniques were modified, and also new algorithms were introduced to improve the performance. These techniques had been used by many researchers in synthesis of mechanisms to get the optimum results with minimum design errors. Improved harmony search (IHS) algorithm is developed from harmony search technique by improvising the harmony in HS algorithm. This technique is inspired by searching the best state of harmony in musical process in which a jazz musician make practice after practice to find the same. In this paper, IHS algorithm is utilized to synthesize four-bar path generation mechanism. A mathematical model was derived using vector loop closure equation, wherein the error function, representing positional error between actual and desired points, was considered for forming objective function. The penalty function was used to prevent violation of structural constraints corresponding to Grashof's criteria and input crank angle sequence. Three different cases were studied with ten, fifteen and eighteen precision points with and without prescribed timings. The results obtained from the study, compared with other evolutionary techniques from literature, and found significant competition.
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