Economic emission dispatch of hydro‐thermal‐wind using CMQLSPSN technique

Robert, L; Singh, Lal Raja Singh Ravi

doi:10.1049/iet-rpg.2019.1232

Cited by 5 publications

(6 citation statements)

References 32 publications

(38 reference statements)

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“…In order to minimise the power loss in the distribution system, Chinnaraj et al proposed to construct a renewable distribution and generation coefficient calculation model by using the LSA modified complex method, and studied the effectiveness of the model, which was found to redistribute the distribution and generation coefficients of the distribution system 7 . Robert et al proposed combining quantum behaviour with LSA to construct a multi-objective hybrid computational model to solve the problem of economic emission scheduling of different energy generating units, and simulation experiments were carried out on the model, and it was found that the model had better computational and scheduling performance than other traditional models 8 . Neffati et al proposed to construct a three-dimensional brain magnetic resonance image classification model using SVM, and validated the effectiveness of the model, and found that the model has better classification performance and robustness than other comparative models, and can assist medical staff in diagnosing the medical images 9 .…”

Section: Related Workmentioning

confidence: 99%

Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid

Qi,

Zhu,

et al. 2024

Sci Rep

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Due to theintricate and interdependent nature of the smart grid, it has encountered an increasing number of security threats in recent years. Currently, conventional security measures such as firewalls, intrusion detection, and malicious detection technologies offer specific protection based on their unique perspectives. However, as the types and concealment of attacksincrease, these measures struggle to detect them promptly and respond accordingly. In order to meet the social demand for the accuracy and computation speed of the power network security risk evaluation model, the study develops a fusion power network security risk evaluation algorithm by fusing the flash search algorithm with the support vector machine. This algorithm is then used as the foundation for building an improved power network security risk evaluation model based on the fusion algorithm.The study's improved algorithm's accuracy is 96.2%, which is higher than the accuracy of the other comparative algorithms; its error rate is 3.8%, which is lower than the error rate of the other comparative algorithms; and its loss function curve convergence is quicker than that of the other algorithms.The risk evaluation model's accuracy is 97.8%, which is higher than the accuracy of other comparative models; the error rate is 1.9%, which is lower than the error rate of other comparative models; the computing time of the improved power network security risk evaluation model is 4.4 s, which is lower than the computing time of other comparative models; and its expert score is high. These findings are supported by empirical analysis of the improved power network security risk evaluation model proposed in the study. According to the study's findings, the fusion algorithm and the upgraded power network security risk evaluation model outperform other approaches in terms of accuracy and processing speed. This allows the study's maintenance staff to better meet the needs of the community by assisting them in identifying potential security hazards early on and taking the necessary preventative and remedial action to ensure the power system's continued safe operation.

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Section: Related Workmentioning

confidence: 99%

Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid

Qi,

Zhu,

et al. 2024

Sci Rep

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“…Operating limits of the generators (a) Operating limits of the thermal generators may be stated in (29).…”

Section: Inequality Constraintsmentioning

confidence: 99%

Chaotic‐quasi‐opposition based whale optimization technique applied to multi‐objective complementary scheduling of grid connected hydro‐thermal–wind–solar‐electric vehicle system

Paul,

Roy,

Mukherjee

2024

Optim Control Appl Methods

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The sources of fossil fuel are impoverishing in upcoming future. In the current research scenario, sincere effort has been taken worldwide to explore the use of renewable energy sources in electrical power system for the economic benefits and environmental consciousness. The main contribution of the proposed work is first, to find optimal hydro‐thermal scheduling (HTS) with wind, solar, and electric vehicles (EVs) for variable load. The target is to find out maximum utilization of renewable energy sources for economic power generation with less emission. Thus, a new approach of EV to grid has been adopted with wind–solar based HTS system for improving grid reliability and resilience. Second, there is a requirement to overcome the local optima problems with less convergence speed. This is obtained by employing a relatively new methodology, known as chaotic‐quasi‐opposition‐based whale optimization algorithm (WOA) (CQOWOA). The proposed algorithm is tested on HTS and wind–solar‐electric vehicle‐based HTS (HTWSVS) for three different cases. Different nonlinearities like valve point effect of thermal units, transmission losses, spillage rate of hydro reservoir units and uncertainties of wind, solar as well as EV are considered to judge the effectiveness of the proposed CQOWOA technique on realistic problems. The presence of wind, solar, and EV energy sources with HTS is evident from the test results of CQOWOA, for multi‐objective problem where cost and emission both are reduced significantly. The robustness of the proposed solution has been verified by implementing the statistical analysis on two systems with least variation of mean and optimal values of cost with the tolerance of less than 0.025%. The comparative analysis of CQOWOA with the other optimization techniques validates its superiority on both the test systems by minimizing the generation cost and emission.

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“…The problem was solved through an efficient differential evolution algorithm (DE) that aimed to minimize the generation costs of all units installed in the EPS. In [13], a modified quantum-behavior lightning search algorithm was applied to solve the EED problem of minimizing the emission cost of a given power system with TG, small hydroelectric generation (HG), and WG generations. A particle swarm optimization algorithm with an artificial neural network was used to capture the probability factor of wind speed.…”

Section: Related Literaturementioning

confidence: 99%

“…Thus, solving the economic/environmental OPF (EEOPF) problem is still a timely topic in power systems research, and one that could guide us toward environmental preservation by decreasing the emission of those greenhouse gases (GHG) which result from producing electric power with fossil fuels [8][9][10]. In this study, probabilistic and stochastic approaches have been frequently used to include uncertainties in the EEOPF formulation, and thus obtain a more realistic (if complex) model [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Economic/Environmental Optimal Power Flow Using a Multiobjective Convex Formulation

et al. 2023

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This paper addresses the problem of economic/environmental optimal power flow with a multiobjective formulation using a second-order conic programming (SOCP) optimization model. This problem formulation considers renewable energy sources (RES), fossil-fuel-based power generation units, and voltage control. The proposed SOCP model is a stochastic scenario-based approach to deal with RES and load behavior uncertainties. An ε-constrained algorithm is used to handle the following three objective functions: (1) the costs of power generation, (2) active power losses in the branches, and (3) the emission of pollutant gases produced by fossil-fuel-based power generation units. For comparative purposes, the SOCP model is also presented using a linearized formulation, and numerical results are presented using a 118-bus system. The results confirm that changing the energy matrices directly affects the cost of objective functions. Additionally, using a linearized SOCP model significantly reduces reactive power violation in the generation units when compared to the nonlinearized SOCP model, but also increases the computational time consumed.

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Economic emission dispatch of hydro‐thermal‐wind using CMQLSPSN technique

Cited by 5 publications

References 32 publications

Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid

Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid

Chaotic‐quasi‐opposition based whale optimization technique applied to multi‐objective complementary scheduling of grid connected hydro‐thermal–wind–solar‐electric vehicle system

Economic/Environmental Optimal Power Flow Using a Multiobjective Convex Formulation

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