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Open AccessArticle

Optimal Allocation of Spinning Reserves in Interconnected Energy Systems with Demand Response Using a Bivariate Wind Prediction Model

1
School of Engineering and Digital Sciences, Nazarbayev University, 53 Kabanbay Batyr ave, 010000 Nur-Sultan, Kazakhstan
2
National Laboratory Astana, Center for Energy and Advanced Material Science, Nazarbayev University, 010000 Nur-Sultan, Kazakhstan
*
Author to whom correspondence should be addressed.
Energies 2019, 12(20), 3816; https://doi.org/10.3390/en12203816
Received: 23 July 2019 / Revised: 29 August 2019 / Accepted: 3 September 2019 / Published: 9 October 2019
(This article belongs to the Special Issue Power Electronics for Energy Saving)
The proposed study presents a novel probabilistic method for optimal allocation of spinning reserves taking into consideration load, wind and solar forecast errors, inter-zonal spinning reserve trading, and demand response provided by consumers as a single framework. The model considers the system contingencies due to random generator outages as well as the uncertainties caused by load and renewable energy forecast errors. The study utilizes a novel approach to model wind speed and its direction using the bivariate parametric model. The proposed model is applied to the IEEE two-area reliability test system (RTS) to analyze the influence of inter-zonal power generation and demand response (DR) on the adequacy and economic efficiency of energy systems. In addition, the study analyzed the effect of the bivariate wind prediction model on obtained results. The results demonstrate that the presence of inter-zonal capacity in ancillary service markets reduce the total expected energy not supplied (EENS) by 81.66%, while inclusion of a DR program results in an additional 1.76% reduction of EENS. Finally, the proposed bivariate wind prediction model showed a 0.27% reduction in spinning reserve requirements, compared to the univariate model. View Full-Text
Keywords: bivariate probability density function; demand response; equivalent assisting unit method; interconnected power systems; spinning reserves; renewable energy bivariate probability density function; demand response; equivalent assisting unit method; interconnected power systems; spinning reserves; renewable energy
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MDPI and ACS Style

Bapin, Y.; Bagheri, M.; Zarikas, V. Optimal Allocation of Spinning Reserves in Interconnected Energy Systems with Demand Response Using a Bivariate Wind Prediction Model. Energies 2019, 12, 3816.

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