Self-adaptive Genetic Algorithm and Fuzzy Decision Based Multi-objective Optimization in Microgrid with DGs

Xie, Shanyi; Zhai, Ruicong; Liu, Xianhu; Li, Baoguo; Long, Kai; Ai, Qian

doi:10.2174/1874129001610010046

Cited by 11 publications

(6 citation statements)

References 16 publications

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“…where K(i) is the cost of repair and maintenance of unit i per kW of electrical power and P(i, t) is the output power of unit i per hour t. The starting cost is intended only for fossil fuel generation units. Given that the starting cost is only attributed to each period that the unit is turned on, how to calculate the starting cost of unit i at hour t is given in Equation (13).…”

Section: Formulation Of the Problemmentioning

confidence: 99%

“…In [13,14], a Fuzzy-PSO self-adaptation algorithm for power flow in a specific microgrid is presented considering economic and environmental issues. The results indicate that with the high participation of renewable resources, the reduction of pollution and microgrid costs is serious and the energy exchange between the microgrid and the network connected to it has many benefits.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Operation of Microgrids with Demand-Side Management Based on a Combination of Genetic Algorithm and Artificial Bee Colony

et al. 2022

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An important issue in power systems is the optimal operation of microgrids with demand-side management. The implementation of demand-side management programs, on the one hand, reduces the cost of operating the power system, and on the other hand, the implementation of such programs requires financial incentive policies. In this paper, the problem of the optimal operation of microgrids along with demand-side management (DSM) is formulated as an optimization problem. Load shifting is considered an effective solution in demand-side management. The objective function of this problem is to minimize the total operating costs of the power system and the cost of load shifting, and the constraints of the problem include operating constraints and executive restrictions for load shifting. Due to the dimensions of the problem, the simultaneous combination of a genetic algorithm and an ABC is used in such a way that by solving the OPF problem with an ABC algorithm and applying it to the structure of the genetic algorithm, the main problem will be solved. Finally, the proposed method is evaluated under the influence of various factors, including the types of production units, the types of loads, the unit uncertainty, sharing with the grid, and electricity prices all based on different scenarios. To confirm the proposed method, the results were compared with different algorithms on the IEEE 33-bus network, which was able to reduce costs by 57.01%.

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Section: Formulation Of the Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Operation of Microgrids with Demand-Side Management Based on a Combination of Genetic Algorithm and Artificial Bee Colony

et al. 2022

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“…The planning and design of the island micro grid can be realized from single-objective optimization to multi-objective optimization. Life cycle cost, power supply reliability, power supply quality and other indicators have been considered in the optimization [76,81,82,83]. Among the potential hazards were habitat loss, bird hits (from moving turbine components), acoustic and electromagnetic emissions.…”

Section: Island/marine Micro-grid Control and Managementmentioning

confidence: 99%

Offshore multi-purpose platforms for a Blue Growth: A technological, environmental and socio-economic review

Abhinav

Collu

Benjamins

et al. 2020

Science of The Total Environment

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Blue Growth" and "Blue Economy" is defined by the World Bank as: "the sustainable use of ocean resources for economic growth, improved livelihoods and jobs, while preserving the health of ocean ecosystem". Multi-purpose platforms (MPPs) can be defined as offshore platforms serving the needs of multiple offshore industries (energy and aquaculture), aim at exploiting the synergies and managing the tensions arising when closely co-locating systems from these industries.Despite a number of previous projects aimed at assessing, from a multidisciplinary point of view, the feasibility of multipurpose platforms, it is here shown that the state-of-the-art has focused mainly on single-purpose devices, and adopting a single discipline (either economic, or social, or technological, or environmental) approaches. Therefore, the aim of the present study is to provide a multidisciplinary state of the art review on, whenever possible, multi-purpose

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“…Due to the rapid development of information science and computer network technology, interdisciplinary research has promoted interdisciplinary integration [7]. Many people use many other research methods to study nancial market predictions, but this is very di cult [8].…”

Section: Introductionmentioning

confidence: 99%

Enterprise Financial Risk Prevention and Control and Data Analysis Method Based on Blockchain Technology

Liu

Chen

2022

Mobile Information Systems

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With the development of engineering technology and computer networks, artificial neural networks, which mimic human brain neural networks, are being used in financial market forecasting to improve the accuracy of stock predictions and are making significant progress. Therefore, there is a great need to actively investigate the method of financial data analysis based on blockchain technology. The purpose of this paper is to investigate the neural network method of financial data analysis based on blockchain technology. Shanghai Index and Shenzhen 200 Index are chosen as experimental data, which are divided into two subsets: training and test samples. The BP model is constructed based on blockchain technology to analyze MARE, RMSRE, MSPEE, RMSPE, and MARE errors. The results show that the mean absolute error rate (MARE), RMSPE, and MSPEE of training samples of blockchain-based BP model are 0.0056, 0.0787, and 0.0085, respectively. Blockchain-based BP model plays an important role in solving financial data analysis problems.

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Self-adaptive Genetic Algorithm and Fuzzy Decision Based Multi-objective Optimization in Microgrid with DGs

Cited by 11 publications

References 16 publications

Optimal Operation of Microgrids with Demand-Side Management Based on a Combination of Genetic Algorithm and Artificial Bee Colony

Optimal Operation of Microgrids with Demand-Side Management Based on a Combination of Genetic Algorithm and Artificial Bee Colony

Offshore multi-purpose platforms for a Blue Growth: A technological, environmental and socio-economic review

Enterprise Financial Risk Prevention and Control and Data Analysis Method Based on Blockchain Technology

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