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A platform for research: civil engineering, architecture and urbanism
Collaborative energy management in a micro-grid by multi-objective mathematical programming
Highlights Introduction of the collaborative paradigm for energy management in micro-grids. Formulation of a bi-Objective Mixed Integer Linear Programming model for it. Employment of the Augmented ϵ-constraint approach to solve the problem. Evaluation of the proposed method in comparison with the Weighted-Sum technique. Experiments prove the beneficial effects of collaborative energy management policies.
Abstract In micro-grids, distributed energy generation based on renewable sources allows reducing the fossil fuel emissions. In order to manage the limited availability of renewable sources and to meet users’ requirements, a proper scheduling of both tasks and storage activities is needed. Moreover, the difficulty of storing energy on a large scale represents an opportunity for the micro-grid actors to collaborate for better balancing energy supply and demand. Collaboration may be achieved through the application of suitable energy management policies tackling the specific consumers’ needs. We address the Energy Management Problem in a micro-grid with collaboration among users. Specifically, a building is considered where each apartment can use both Shared and Local energy resources, the former managed by a Building Manager (BM). The problem is formulated through Bi-objective Mixed Integer Linear Programming, maximizing both the BM and the apartments’ profits and solved through the Augmented ϵ-Constraint approach. Numerical results, obtained on a set of realistic scenarios, are compared to those of the Weighted Sum method and evaluated according to proper performance metrics. The approach flexibility, in terms of selected management policies, is also discussed. Finally, the superiority of the collaborative paradigm versus the non-collaborative one is experimentally proven.
Collaborative energy management in a micro-grid by multi-objective mathematical programming
Highlights Introduction of the collaborative paradigm for energy management in micro-grids. Formulation of a bi-Objective Mixed Integer Linear Programming model for it. Employment of the Augmented ϵ-constraint approach to solve the problem. Evaluation of the proposed method in comparison with the Weighted-Sum technique. Experiments prove the beneficial effects of collaborative energy management policies.
Abstract In micro-grids, distributed energy generation based on renewable sources allows reducing the fossil fuel emissions. In order to manage the limited availability of renewable sources and to meet users’ requirements, a proper scheduling of both tasks and storage activities is needed. Moreover, the difficulty of storing energy on a large scale represents an opportunity for the micro-grid actors to collaborate for better balancing energy supply and demand. Collaboration may be achieved through the application of suitable energy management policies tackling the specific consumers’ needs. We address the Energy Management Problem in a micro-grid with collaboration among users. Specifically, a building is considered where each apartment can use both Shared and Local energy resources, the former managed by a Building Manager (BM). The problem is formulated through Bi-objective Mixed Integer Linear Programming, maximizing both the BM and the apartments’ profits and solved through the Augmented ϵ-Constraint approach. Numerical results, obtained on a set of realistic scenarios, are compared to those of the Weighted Sum method and evaluated according to proper performance metrics. The approach flexibility, in terms of selected management policies, is also discussed. Finally, the superiority of the collaborative paradigm versus the non-collaborative one is experimentally proven.
Collaborative energy management in a micro-grid by multi-objective mathematical programming
Pisacane, Ornella (author) / Severini, Marco (author) / Fagiani, Marco (author) / Squartini, Stefano (author)
Energy and Buildings ; 203
2019-09-12
Article (Journal)
Electronic Resource
English
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