Bidding Strategy for Microgrid in Day-Ahead Market Based on Hybrid Stochastic/Robust Optimization

This paper proposes an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG, and price responsive loads. The microgrid coordinates the energy consumption or production of its components, and trades electricit...

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Vydané v:	IEEE transactions on smart grid Ročník 7; číslo 1; s. 227 - 237
Hlavní autori:	Guodong Liu, Yan Xu, Tomsovic, Kevin
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.01.2016
Predmet:	Batteries Distributed generation Electric power generation ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION ENERGY PLANNING, POLICY, AND ECONOMY Market bidding strategy Markets Mathematical models Microgrid Microgrids mixed-integer linear programming (MILP) Optimization Pricing Real time Real-time systems robust optimization Robustness stochastic optimization Stochastic processes Stochasticity Uncertainty uncertainty Market bidding strategy microgrid mixed-integer linear programming (MILP) robust optimization stochastic optimization
ISSN:	1949-3053, 1949-3061
On-line prístup:	Získať plný text
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Abstract	This paper proposes an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG, and price responsive loads. The microgrid coordinates the energy consumption or production of its components, and trades electricity in both day-ahead and real-time markets to minimize its operating cost as a single entity. The bidding problem is challenging due to a variety of uncertainties, including power output of intermittent DG, load variation, and day-ahead and real-time market prices. A hybrid stochastic/robust optimization model is proposed to minimize the expected net cost, i.e., expected total cost of operation minus total benefit of demand. This formulation can be solved by mixed-integer linear programming. The uncertain output of intermittent DG and day-ahead market price are modeled via scenarios based on forecast results, while a robust optimization is proposed to limit the unbalanced power in real-time market taking account of the uncertainty of real-time market price. Numerical simulations on a microgrid consisting of a wind turbine, a photovoltaic panel, a fuel cell, a micro-turbine, a diesel generator, a battery, and a responsive load show the advantage of stochastic optimization, as well as robust optimization.
AbstractList	This paper proposes an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG, and price responsive loads. The microgrid coordinates the energy consumption or production of its components, and trades electricity in both day-ahead and real-time markets to minimize its operating cost as a single entity. The bidding problem is challenging due to a variety of uncertainties, including power output of intermittent DG, load variation, and day-ahead and real-time market prices. A hybrid stochastic/robust optimization model is proposed to minimize the expected net cost, i.e., expected total cost of operation minus total benefit of demand. This formulation can be solved by mixed-integer linear programming. The uncertain output of intermittent DG and day-ahead market price are modeled via scenarios based on forecast results, while a robust optimization is proposed to limit the unbalanced power in real-time market taking account of the uncertainty of real-time market price. Numerical simulations on a microgrid consisting of a wind turbine, a photovoltaic panel, a fuel cell, a micro-turbine, a diesel generator, a battery, and a responsive load show the advantage of stochastic optimization, as well as robust optimization. In this paper, we propose an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage, dispatchable DG and price responsive loads. The microgrid coordinates the energy consumption or production of its components and trades electricity in both the day-ahead and real-time markets to minimize its operating cost as a single entity. The bidding problem is challenging due to a variety of uncertainties, including power output of intermittent DG, load variation, day-ahead and real-time market prices. A hybrid stochastic/robust optimization model is proposed to minimize the expected net cost, i.e., expected total cost of operation minus total benefit of demand. This formulation can be solved by mixed integer linear programming. The uncertain output of intermittent DG and day-ahead market price are modeled via scenarios based on forecast results, while a robust optimization is proposed to limit the unbalanced power in real-time market taking account of the uncertainty of real-time market price. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator, a battery and a responsive load show the advantage of stochastic optimization in addition to robust optimization.
Author	Tomsovic, Kevin Guodong Liu Yan Xu
Author_xml	– sequence: 1 surname: Guodong Liu fullname: Guodong Liu email: liug@ornl.gov organization: Oak Ridge Nat. Lab., Oak Ridge, TN, USA – sequence: 2 surname: Yan Xu fullname: Yan Xu email: xuy3@ornl.gov organization: Oak Ridge Nat. Lab., Oak Ridge, TN, USA – sequence: 3 givenname: Kevin surname: Tomsovic fullname: Tomsovic, Kevin email: tomsovic@utk.edu organization: Min H. Kao Dept. of Electr. Eng. & Comput. Sci., Univ. of Tennessee, Knoxville, TN, USA
BackLink	https://www.osti.gov/servlets/purl/1265375$$D View this record in Osti.gov
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Snippet	This paper proposes an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage,... In this paper, we propose an optimal bidding strategy in the day-ahead market of a microgrid consisting of intermittent distributed generation (DG), storage,...
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SubjectTerms	Batteries Distributed generation Electric power generation ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION ENERGY PLANNING, POLICY, AND ECONOMY Market bidding strategy Markets Mathematical models Microgrid Microgrids mixed-integer linear programming (MILP) Optimization Pricing Real time Real-time systems robust optimization Robustness stochastic optimization Stochastic processes Stochasticity Uncertainty
Title	Bidding Strategy for Microgrid in Day-Ahead Market Based on Hybrid Stochastic/Robust Optimization
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