Abstract
—A crucial factor that may hinder the usage of renewable energies is the mismatch to load demand in the temporal dimension. In the smart-grid environment, demand response is regarded as a feasible solution to mitigate such a problem. In this study, a combinatory planning method is proposed for efficient integration of wind generation. The problem is formulated as a two-stage fuzzy chance-constrained programming model, which co-optimizes the installation of distributed wind generation along with network transformation and determination of optimal real-time prices to achieve the minimization of the total cost over planning horizons. The impact of both aleatory and epistemic uncertainties associated with wind generation, load growth, and responsive behaviors of customers has been considered. Results of the case study demonstrate the effectiveness of the proposed method and the necessity of considering different uncertainties in the planning.
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Notes on contributors
Bo Zeng
Bo Zeng received the B.S. and Ph.D. degrees in Electrical Engineering from North China Electric Power University (NCEPU), Beijing, China, in the year of 2009 and 2014, respectively. Presently, he is working as a Lecturer of the Department of Electrical and Electronic Engineering, at NCEPU. Dr. Zeng is the Member of IEEE and the Chinese Society for Electrical Engineering (CSEE). His research interests include distributed generation, demand side management, and active distribution system planning.
Jianhua Zhang
Jianhua Zhang received the B.S and M.S. degrees in Electrical Engineering from North China Electric Power University, Baoding, China in 1982 and 1984, respectively. From Mar. 1990 to Mar. 1991, he was a visiting scholar in the Queen's University of Belfast, U.K., during which he was rewarded the scholarship from the Royal Society. He is currently working as a Professor in the Department of Electrical and Electronic Engineering and directs the Power Transmission and Distribution Institute. He has been the IET Fellow from the year of 2005, and also the member in the PES Committee of China National “973 Project”. His special fields of interest include power system security assessment, power system planning and distributed generation.
Shaojie Ouyang
Shaojie Ouyang received his Bachelor degree in Business Administration from North China Electric Power University, Beijing, China, in 2012, where he is currently pursuing his Ph.D. degree on the same major. He is the Student Member of the Chinese Society of Electrical Engineering. His research fields of interests are power market and low-carbon electricity.
Xu Yang
Xu Yang received the B.S. degree in electrical engineering from the North China Electric Power University, Beijing, China, in 2012 and currently working towards the M.S. degree in Electrical Engineering at the same university. His research interests mainly include distribution system planning, operation and optimization, and integration of electric vehicles in power systems.
Jun Dong
Jun Dong received the Ph.D. degree in energy system and economics from École Polytechnique Fédérale de Lausanne, Switzerland, in 2004. She is currently a Professor in the School of Economics and Management of North China Electric Power University. She is also the recipient of the Program for New Century Excellent Talents in University, granted by the Ministry of Education in China. Her research interests mainly focus on energy policy, electricity market, and power economics.
Ming Zeng
Ming Zeng received his M.S. degree in Thermal Engineering from North China Electric Power University, Beijing, China, in 1984. Between 1992 and 1993, he was a senior visiting scholar of European Community Energy Research Institution. Currently, he is working as a Professor in the School of Economics and Management of North China Electric Power University. He is the recipient of the first prize of Soft Science Outstanding Research Achievements from China National Energy Administration in the year of 2011. His research interests include energy system economics, low-carbon electricity, power system planning, and electricity market.