Economic-environmental energy and reserve scheduling of smart distribution systems: A multiobjective mathematical programming approach

In this paper a stochastic multi-objective economical/environmental operational scheduling method is proposed to schedule energy and reserve in a smart distribution system with high penetration of wind generation. The proposed multi-objective framework, based on augmented epsilon -constraint method,...

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Veröffentlicht in:	Energy conversion and management Jg. 78; S. 151 - 164
Hauptverfasser:	Zakariazadeh, Alireza, Jadid, Shahram, Siano, Pierluigi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Kidlington Elsevier 01.02.2014
Schlagworte:	Applied sciences decision making Demand Economics emissions Energy Energy distribution Energy use Exact sciences and technology linear programming markets Mathematical models Natural energy Reserve scheduling Reserves Scheduling wind Wind energy wind power Scheduling Demand response Optimization Emissions Wind energy Distribution Energy demand Multi-objective optimization Electric power production Wind power Energy management Distribution system Mathematical programming
ISSN:	0196-8904
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Abstract	In this paper a stochastic multi-objective economical/environmental operational scheduling method is proposed to schedule energy and reserve in a smart distribution system with high penetration of wind generation. The proposed multi-objective framework, based on augmented epsilon -constraint method, is used to minimize the total operational costs and emissions and to generate Pareto-optimal solutions for the energy and reserve scheduling problem. Moreover, fuzzy decision making process is employed to extract one of the Pareto-optimal solutions as the best compromise non-dominated solution. The wind power and demand forecast errors are considered in this approach and the reserve can be furnished by the main grid as well as distributed generators and responsive loads. The consumers participate in both energy and reserve markets using various demand response programs. In order to facilitate small and medium loads participation in demand response programs, a Demand Response Provider (DRP) aggregates offers for load reduction. In order to solve the proposed optimization model, the Benders decomposition technique is used to convert the large scale mixed integer non-linear problem into mixed-integer linear programming and non-linear programming problems. The effectiveness of the proposed scheduling approach is verified on a 41-bus distribution test system over a 24-h period.
AbstractList	In this paper a stochastic multi-objective economical/environmental operational scheduling method is proposed to schedule energy and reserve in a smart distribution system with high penetration of wind generation. The proposed multi-objective framework, based on augmented ε-constraint method, is used to minimize the total operational costs and emissions and to generate Pareto-optimal solutions for the energy and reserve scheduling problem. Moreover, fuzzy decision making process is employed to extract one of the Pareto-optimal solutions as the best compromise non-dominated solution. The wind power and demand forecast errors are considered in this approach and the reserve can be furnished by the main grid as well as distributed generators and responsive loads. The consumers participate in both energy and reserve markets using various demand response programs. In order to facilitate small and medium loads participation in demand response programs, a Demand Response Provider (DRP) aggregates offers for load reduction. In order to solve the proposed optimization model, the Benders decomposition technique is used to convert the large scale mixed integer non-linear problem into mixed-integer linear programming and non-linear programming problems. The effectiveness of the proposed scheduling approach is verified on a 41-bus distribution test system over a 24-h period. In this paper a stochastic multi-objective economical/environmental operational scheduling method is proposed to schedule energy and reserve in a smart distribution system with high penetration of wind generation. The proposed multi-objective framework, based on augmented epsilon -constraint method, is used to minimize the total operational costs and emissions and to generate Pareto-optimal solutions for the energy and reserve scheduling problem. Moreover, fuzzy decision making process is employed to extract one of the Pareto-optimal solutions as the best compromise non-dominated solution. The wind power and demand forecast errors are considered in this approach and the reserve can be furnished by the main grid as well as distributed generators and responsive loads. The consumers participate in both energy and reserve markets using various demand response programs. In order to facilitate small and medium loads participation in demand response programs, a Demand Response Provider (DRP) aggregates offers for load reduction. In order to solve the proposed optimization model, the Benders decomposition technique is used to convert the large scale mixed integer non-linear problem into mixed-integer linear programming and non-linear programming problems. The effectiveness of the proposed scheduling approach is verified on a 41-bus distribution test system over a 24-h period.
Author	Zakariazadeh, Alireza Jadid, Shahram Siano, Pierluigi
Author_xml	– sequence: 1 givenname: Alireza surname: Zakariazadeh fullname: Zakariazadeh, Alireza – sequence: 2 givenname: Shahram surname: Jadid fullname: Jadid, Shahram – sequence: 3 givenname: Pierluigi orcidid: 0000-0002-0975-0241 surname: Siano fullname: Siano, Pierluigi
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Keywords	Scheduling Demand response Optimization Emissions Wind energy Distribution Energy demand Multi-objective optimization Electric power production Wind power Energy management Distribution system Mathematical programming
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Snippet	In this paper a stochastic multi-objective economical/environmental operational scheduling method is proposed to schedule energy and reserve in a smart...
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SubjectTerms	Applied sciences decision making Demand Economics emissions Energy Energy distribution Energy use Exact sciences and technology linear programming markets Mathematical models Natural energy Reserve scheduling Reserves Scheduling wind Wind energy wind power
Title	Economic-environmental energy and reserve scheduling of smart distribution systems: A multiobjective mathematical programming approach
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