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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Bibliographic Details
Published in:IEEE transactions on smart grid Vol. 7; no. 1; pp. 227 - 237
Main Authors: Guodong Liu, Yan Xu, Tomsovic, Kevin
Format: Journal Article
Language:English
Published: United States IEEE 01.01.2016
Subjects:
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
Online Access:Get full text
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Summary: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.
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USDOE
AC05-00OR22725
ISSN:1949-3053
1949-3061
DOI:10.1109/TSG.2015.2476669