Day-ahead optimal bidding strategy of microgrid with demand response program considering uncertainties and outages of renewable energy resources

In restructured electricity markets, microgrids are becoming smarter, more reliable and more economic electricity providers with respect to the incorporation of advanced smart grid technologies, distributed energy resources, efficient energy storage systems, and demand response programs (DRPs). More...

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Vydáno v:Energy (Oxford) Ročník 190; s. 116441
Hlavní autoři: Das, Saborni, Basu, Mousumi
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Elsevier Ltd 01.01.2020
Elsevier BV
Témata:
Alternative energy sources
confidence interval
Confidence intervals
Demand response program
Distributed generation
Electric power grids
electrical equipment
Electricity
energy
Energy industry
Energy management
Energy resources
Energy sources
Energy storage
Forced outage probability
Mapping
markets
Mixed integer
Nonlinear programming
Outages
profits and margins
Renewable energy
renewable energy sources
Renewable integrated microgrid
Renewable resources
risk
Risk management
Smart grid
Smart grid technology
Storage systems
Uncertainty
Value of stochastic solution
Value of stochastic solution
Uncertainty
Demand response program
Renewable integrated microgrid
Forced outage probability
Risk management
ISSN:0360-5442, 1873-6785
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Shrnutí:In restructured electricity markets, microgrids are becoming smarter, more reliable and more economic electricity providers with respect to the incorporation of advanced smart grid technologies, distributed energy resources, efficient energy storage systems, and demand response programs (DRPs). Moreover, better bidding strategies, prepared by MG operators, boost the profits of MG market players. But, highly intermittent nature of renewable energy resources and their higher rate of outages make bidding strategies inefficient. To solve these issues, this study suggests an optimal bidding strategy considering uncertainty of renewable energy resources and DRP based on their outage probabilities. Tent chaos mapping is used to generate load scenarios and all possible renewable power output scenarios within the confidence intervals in non-repetitive and adaptive manner. Reserve and penalty costs for incorrect estimation of renewable energies are invoked to design more robust bidding. Moreover, the risk of participation in the competitive energy market is assessed using CVaR criteria. The proposed bidding model is optimized using mixed integer nonlinear programming. ‘Value of stochastic solution’ is used to investigate the efficiency of the stochastic programming in uncertainty integration into the bidding problem. •Bidding scheme with risk management of microgrid is proposed.•Forced outage and uncertainty modeling of renewable units are furnished.•Demand response program considers load elasticity and outages of renewable units.•Reserve/penalty cost of over/under estimation of renewable outputs are considered.•Bidding profits vary with Tent chaotic mapped scenarios of uncertain parameters.
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ISSN:0360-5442
1873-6785
DOI:10.1016/j.energy.2019.116441