Modeling the risk-based decisions of the microgrid in day-ahead energy and reserve markets considering stochastic dispatching of electrical and thermal energy storages

Bahramara, Salah; Shahrokhi, Saman; Sheikhahmadi, Pouria; Khezri, Rahmat; Muyeen, S. M.

doi:10.1016/j.ecmx.2022.100201

Cited by 3 publications

(3 citation statements)

References 34 publications

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“…The practical results showed that the model was effective in preventing MGO decision-making from being affected by uncertainty. 10 With the increasing growth of computer technology, there are more and more algorithms applied in the field of scheduling optimization. Zhu et al proposed a workshop scheduling method based on discrete African buffalo optimization to improve the low-carbon scheduling level in the field of production scheduling.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In formula (10), 𝜇 represents the control parameter. If h n is a parameter that is greater to or equal to zero but less to/or equal to one and 𝜇 equal to 4, a model is in a completely chaotic state.…”

Section: Application Study Of Optimized Particle Swarm Algorithm In I...mentioning

confidence: 99%

“…Bahramara and her team developed a bi‐stage stochastic model towards power management of micro‐grid and main‐grid under uncertain conditions. The practical results showed that the model was effective in preventing MGO decision‐making from being affected by uncertainty 10 …”

Section: Literature Reviewmentioning

confidence: 99%

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Research on intelligent dispatching of micro‐grid according to optimized particle swarm algorithm

Nie

Zhang

2023

Adv Control Appl

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In the process of grid connection of irregular output micro‐grid systems, it is of great research significance to make micro‐grid scheduling operate more effectively and economically. To minimize the environmental and total operating costs of the micro‐grid intelligent scheduling system during grid connection, this study proposes a micro‐grid intelligent scheduling model based on an optimized particle swarm optimization algorithm. The optimized particle swarm algorithm mainly improves the problem of the particle swarm algorithm being prone to local optima, making it reduce the possibility of local convergence. Comparative tests were conducted on the improved IPSO algorithm, and the results showed that the non‐dominated solution concentration pollution emissions obtained by the improved IPSO algorithm were at least 18326 Ib, which was lower than the comparison algorithm. In the empirical analysis of the intelligent scheduling model based on the improved IPSO algorithm, the convergence and satisfaction of the model were 0.0054 and 0.922, respectively, which were superior to the comparison algorithm. The above results indicate that the intelligent scheduling model for micro‐grid based on the improved IPSO algorithm has good economy and stability. Compared with traditional energy dispatch methods, this energy dispatch mode has higher economic benefits and is of great significance for promoting the development of micro‐grid.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Application Study Of Optimized Particle Swarm Algorithm In I...mentioning

confidence: 99%

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Research on intelligent dispatching of micro‐grid according to optimized particle swarm algorithm

Nie

Zhang

2023

Adv Control Appl

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Adaptive change in national markets of electricity as benchmark for microgrids: the case study of Poland and the UK

Wasniewski

2024

2024 29th International Conference on Automation and Computing (ICAC)

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Comprehensive Review on Modelling and Optimization of Budget Allocation for Procurement of Alternative Gas Sources in Power Plant Industry

Oluwagbemiga,

Bamidele,

Olufemi

2024

2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG)

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Modeling the risk-based decisions of the microgrid in day-ahead energy and reserve markets considering stochastic dispatching of electrical and thermal energy storages

Cited by 3 publications

References 34 publications

Research on intelligent dispatching of micro‐grid according to optimized particle swarm algorithm

Research on intelligent dispatching of micro‐grid according to optimized particle swarm algorithm

Adaptive change in national markets of electricity as benchmark for microgrids: the case study of Poland and the UK

Comprehensive Review on Modelling and Optimization of Budget Allocation for Procurement of Alternative Gas Sources in Power Plant Industry

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