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Journal ArticleDOI

Optimal offering and bidding strategies of renewable energy based large consumer using a novel hybrid robust-stochastic approach

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TLDR
A linear model with integer variables is developed to derive offering and bidding curves, which are robust against the uncertainty associated with the load demand of the large consumer, and results show that the higher amount of uncertain parameter is considered, the higher procurement price has resulted for theLarge consumer.
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This article is published in Journal of Cleaner Production.The article was published on 2019-04-01. It has received 143 citations till now. The article focuses on the topics: Bidding & Robust optimization.

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Citations
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Journal ArticleDOI

Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm

TL;DR: This study combined support vector machine and improved dragonfly algorithm to forecast short-term wind power for a hybrid prediction model and has shown better prediction performance compared with the other models such as back propagation neural network and Gaussian process regression.
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Blockchain-Based Securing of Data Exchange in a Power Transmission System Considering Congestion Management and Social Welfare

TL;DR: The obtained results of the simulation confirm the effectiveness of using blockchain to enhance the social welfare for power system users and show that ISO can modify its polices and use the potential and benefits of distributed generation units to increase social welfare and reduce line density by concluding contracts in accordance with the production values given.
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System identification of PEM fuel cells using an improved Elman neural network and a new hybrid optimization algorithm

TL;DR: An optimized improved Elman neural network based on a new hybrid optimization algorithm is proposed for increasing their efficiency in the next designs of the proton exchange membrane fuel cell.
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Co-optimized bidding strategy of an integrated wind-thermal-photovoltaic system in deregulated electricity market under uncertainties

TL;DR: Simulation results illustrate that not only the integrated participation of wind-thermal-photovoltaic resources increases the producer's expected profit, but also decreases the amount of the produced pollution by the thermal units.
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Tri-objective optimal scheduling of smart energy hub system with schedulable loads

TL;DR: The optimal scheduling problem of an EHS is modeled as a tri-objective optimization problem in which the operation cost, the emission pollution, and the deviation of the electrical load profile from its desired value is minimized.
References
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Journal ArticleDOI

Robust discrete optimization and network flows

TL;DR: This work proposes a robust integer programming problem of moderately larger size that allows controlling the degree of conservatism of the solution in terms of probabilistic bounds on constraint violation, and proposes an algorithm for robust network flows that solves the robust counterpart by solving a polynomial number of nominal minimum cost flow problems in a modified network.
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Optimal Bidding Strategy for Microgrids Considering Renewable Energy and Building Thermal Dynamics

TL;DR: An optimal day-ahead price-based power scheduling problem for a community-scale microgrid (MG) is studied and the great benefits in exploiting the building thermal dynamics and the flexibility of the proposed scheduling method in achieving different practical design tradeoffs are presented.
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Optimal bidding strategy of electricity retailers using robust optimisation approach considering time-of-use rate demand response programs under market price uncertainties

TL;DR: In this article, a robust optimisation approach is proposed for decision making of electricity retailers, considering the effect of DRP on total procurement cost, an optimal bidding strategy is proposed of electricity retailer with the time-based model of demand response programs (DRP) in the electricity market.
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IGDT Based Robust Decision Making Tool for DNOs in Load Procurement Under Severe Uncertainty

TL;DR: A decision making framework is proposed based on IGDT model to solve the information gap decision theory problem and the effectiveness of the proposed tool is assessed and demonstrated by applying it on a large distribution network.
Journal ArticleDOI

Stochastic energy procurement of large electricity consumer considering photovoltaic, wind-turbine, micro-turbines, energy storage system in the presence of demand response program

TL;DR: In this article, a stochastic energy procurement problem for large electricity consumer (LEC) with multiple energy procurement sources (EPSs) considering the effects of demand response program (DRP) and energy storage system (ESS) was proposed.
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