<p>The optimal power flow (OPF) solution for the IEEE 30-bus system is being achieved while taking thermal power (TP) sources into account. In this study, the OPF solution of conventional power systems incorporating FACTS devices with frequency security constraint is investigated. By incorporating FACTS devices into the existing power systems the proposed work improves the power system’s capacity to transfer power and hence reduce generation costs. The objectives are to reduce generation costs and emissions. In order to illustrate that generation and consumption are in balance, the system frequency must be kept within a safe range. Therefore, in addition to ensuring the lowest producing cost under operating conditions, the OPF approach needs to provide a stable frequency. Moreover, in order to attain frequency stability, frequency security constraint is applied to the power dispatch problem. Three scenarios have been examined in this article: (i) the OPF of conventional system in the absence of a frequency security constraint, (ii) the OPF of conventional system in the presence of a frequency security constraint and (iii) OPF of conventional system with the combined effect of UPFC and a frequency based security constraint. The test outcomes indicate that the OPF problem is better addressed when UPFC is combined with frequency security constraints. To get the best solution, the driving training-based optimization (DTBO) technique has been used. After incorporating UPFC with frequency based security constraints, the fuel cost, emissions and frequency deviation are reduced by 0.28%, 9.4% &amp; (OS<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>1.47%, SS<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>12.9%) at 50% load; 0.12%, 6.61% and (OS<InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>1.8%, SS<InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>11.4%) at 60% load; 4.66%, 1.68% and (OS<InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>0.45%, SS<InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>1.38%) at 70% load; 0.41%, 2.1% and (OS<InlineEquation ID="IEq7"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>1.3%, SS<InlineEquation ID="IEq8"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>27.2%) at 80% load; 2.3%, 5% and (OS<InlineEquation ID="IEq9"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>0.22%, SS<InlineEquation ID="IEq10"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>1.6%) at 90% load; 2.32%, 1.53% and (OS<InlineEquation ID="IEq11"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>0.55%, SS<InlineEquation ID="IEq12"> <EquationSource Format="TEX">\(-\)</EquationSource> </InlineEquation>6.35%) at 100% load. According to the simulation outcome, it can be depicted that the DTBO is better than the biography-based optimization (BBO) and grey wolf optimization (GWO). The suggested algorithm has produced better results, which have been confirmed by statistical methods such as box plot, error bar and one-way ANOVA (analysis of variance) test.</p> Graphical abstract <p></p>

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Solution of frequency deviation and multi objective probabilistic optimal power flow of transmission network incorporating UPFC controller using driving training based optimization

  • Adhit Roy,
  • Susanta Dutta,
  • Soumen Biswas,
  • Anagha Bhattacharya,
  • Provas Kumar Roy

摘要

The optimal power flow (OPF) solution for the IEEE 30-bus system is being achieved while taking thermal power (TP) sources into account. In this study, the OPF solution of conventional power systems incorporating FACTS devices with frequency security constraint is investigated. By incorporating FACTS devices into the existing power systems the proposed work improves the power system’s capacity to transfer power and hence reduce generation costs. The objectives are to reduce generation costs and emissions. In order to illustrate that generation and consumption are in balance, the system frequency must be kept within a safe range. Therefore, in addition to ensuring the lowest producing cost under operating conditions, the OPF approach needs to provide a stable frequency. Moreover, in order to attain frequency stability, frequency security constraint is applied to the power dispatch problem. Three scenarios have been examined in this article: (i) the OPF of conventional system in the absence of a frequency security constraint, (ii) the OPF of conventional system in the presence of a frequency security constraint and (iii) OPF of conventional system with the combined effect of UPFC and a frequency based security constraint. The test outcomes indicate that the OPF problem is better addressed when UPFC is combined with frequency security constraints. To get the best solution, the driving training-based optimization (DTBO) technique has been used. After incorporating UPFC with frequency based security constraints, the fuel cost, emissions and frequency deviation are reduced by 0.28%, 9.4% & (OS \(-\) 1.47%, SS \(-\) 12.9%) at 50% load; 0.12%, 6.61% and (OS \(-\) 1.8%, SS \(-\) 11.4%) at 60% load; 4.66%, 1.68% and (OS \(-\) 0.45%, SS \(-\) 1.38%) at 70% load; 0.41%, 2.1% and (OS \(-\) 1.3%, SS \(-\) 27.2%) at 80% load; 2.3%, 5% and (OS \(-\) 0.22%, SS \(-\) 1.6%) at 90% load; 2.32%, 1.53% and (OS \(-\) 0.55%, SS \(-\) 6.35%) at 100% load. According to the simulation outcome, it can be depicted that the DTBO is better than the biography-based optimization (BBO) and grey wolf optimization (GWO). The suggested algorithm has produced better results, which have been confirmed by statistical methods such as box plot, error bar and one-way ANOVA (analysis of variance) test.

Graphical abstract