Mixed-Integer Linear Programming for Decentralized Multi-Carrier Optimal Energy Management of a Micro-Grid

Increasing the load demand and penetration of renewable energy sources (RESs) poses real challenges for optimal energy management of distribution networks. Moreover, considering multi-carrier energy systems has increased the efficiency of systems, and provides an opportunity for using the advantages...

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Vydáno v:Applied Sciences Ročník 12; číslo 7; s. 3262
Hlavní autoři: Faghiri, Mohammad, Samizadeh, Shadi, Nikoofard, Amirhossein, Khosravy, Mahdi, Senjyu, Tomonobu
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 23.03.2022
Témata:
Alternative energy sources
Biology (General)
Chemistry
Demand side management
Electricity
Electricity distribution
Energy management
Energy resources
Engineering (General). Civil engineering (General)
Equilibrium
Fuel cells
Industrial plant emissions
Linear programming
multi-agent system
multi-energy carrier
Natural gas
Operating costs
optimal energy management
optimal energy management; multi-agent system; multi-energy carrier; renewable energy sources; uncertainty
Optimization
Physics
Power plants
QC1-999
QD1-999
QH301-705.5
renewable energy sources
Renewable resources
Systems stability
T
TA1-2040
Technology
uncertainty
ISSN:2076-3417, 2076-3417
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Shrnutí:Increasing the load demand and penetration of renewable energy sources (RESs) poses real challenges for optimal energy management of distribution networks. Moreover, considering multi-carrier energy systems has increased the efficiency of systems, and provides an opportunity for using the advantages of RESs. In this regard, we adopted a new framework based on the new challenges in the multi-carrier energy micro-grid (MEMG). In the proposed method, a comprehensive MEMG was modeled that benefits from a large assortment of distributed energy resources (DERs), such as micro-turbines, fuel cells, wind turbines, and energy storage. Considering many DERs is necessary, because these resources could cover one another’s disadvantages, which have a great impact on the total cost of the MEMG and decrease the emission impacts of fossil-fuel-based units. Furthermore, waste power plants, inverters, rectifiers, and emission constraints are considered in the proposed method for modeling a practical MEMG. Additionally, for modeling the uncertainty of stochastic parameters, a model based on a multilayer neural network was used in this paper. The results of this study indicate that using a decentralized model, along with stochastic methods for predicting uncertainty, can reduce operational costs in micro-grids and computational complexity compared with optimal centralized programming methods. Finally, the equations and results obtained from the proposed method were evaluated by experiments.
Bibliografie:ObjectType-Article-1
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content type line 14
ISSN:2076-3417
2076-3417
DOI:10.3390/app12073262