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Open AccessArticle

Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty

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Department of Electronics and Electrical Systems, The University of Lahore, Lahore 54000, Pakistan
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Department of Computer Science, COMSATS University, Islamabad 44000, Pakistan
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Department of Electrical and Power Engineering, Sheffield Hallam University, Sheffield S1 1WB, UK
*
Author to whom correspondence should be addressed.
Energies 2018, 11(10), 2833; https://doi.org/10.3390/en11102833
Received: 24 July 2018 / Revised: 2 October 2018 / Accepted: 15 October 2018 / Published: 20 October 2018
This paper proposes a system model for optimal dispatch of the energy and reserve capacity considering uncertain load demand and unsteady power generation. This implicates uncertainty in managing the power demand along with the consideration of utility, user and environmental objectives. The model takes into consideration a day-ahead electricity market that involves the varying power demand bids and generates a required amount of energy in addition with reserve capacity. The lost opportunity cost is also considered and incorporated within the context of expected load not served. Then, the effects of combined and separate dispatching the energy and reserve are investigated. The nonlinear cost curves have been addressed by optimizing the objective function using robust optimization technique. Finally, various cases in accordance with underlying parameters have been considered in order to conduct and evaluate numerical results. Simulation results show the effectiveness of proposed scheduling model in terms of reduced cost and system stability. View Full-Text
Keywords: co-dispatch; electricity market; energy and reserve; uncertainty; energy loss factor; co-optimization co-dispatch; electricity market; energy and reserve; uncertainty; energy loss factor; co-optimization
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Hassan, M.W.; Rasheed, M.B.; Javaid, N.; Nazar, W.; Akmal, M. Co-Optimization of Energy and Reserve Capacity Considering Renewable Energy Unit with Uncertainty. Energies 2018, 11, 2833.

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