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Many electricity markets around the world are still at developmental and transitional stages. To complete the transition and achieve the key objectives of perfect market design, designers often choose direct electricity procurement of large consumers (LCs) as a pilot. The trading mechanism is critical because it lays the foundation for the exploration of formulating a trading model and the succeeding solution; however, the existing trading mechanisms of direct electricity procurement struggle to cope with new challenges that electric power systems are facing. This paper proposes a novel two-stage trading mechanism, considering both the fairness and efficiency of direct electricity procurement. Based on the proposed trading mechanism, an agent-based trading model with multiple participants is developed. The simulation results of the transactions between LCs and generation companies (GenCos) illustrate the feasibility and effectiveness of the proposed mechanism. With this mechanism, LCs and GenCos will have more choices in the trading process and can benefit from the reduction of the average market price. The two-stage trading model provides a new choice for market designers and participants of direct electricity procurement.
Jian Zhang; Yanan Zheng; Mingtao Yao; Huiji Wang; Zhaoguang Hu. An Agent-Based Two-Stage Trading Model for Direct Electricity Procurement of Large Consumers. Sustainability 2019, 11, 5031 .
AMA StyleJian Zhang, Yanan Zheng, Mingtao Yao, Huiji Wang, Zhaoguang Hu. An Agent-Based Two-Stage Trading Model for Direct Electricity Procurement of Large Consumers. Sustainability. 2019; 11 (18):5031.
Chicago/Turabian StyleJian Zhang; Yanan Zheng; Mingtao Yao; Huiji Wang; Zhaoguang Hu. 2019. "An Agent-Based Two-Stage Trading Model for Direct Electricity Procurement of Large Consumers." Sustainability 11, no. 18: 5031.
With the development of the smart grid in China, new opportunities for responsive industrial loads to participate in the provision of ancillary services (AS) will become accessible. This paper summarizes AS in China and analyzes the necessary characteristics and advantages of industrial users to provide AS according to their response mechanism. Cement manufacturing and aluminum smelter processes are selected as two representatives of responsive industrial loads. An agent-based model that includes generation, industrial user, and grid agents is proposed. Using two case studies, we analyze the integrated power management of conventional units and industrial loads in day-ahead and real-time AS scheduling based on real device parameters, price mechanisms and production data. The simulation results indicate that the participation of responsive industrial loads in the provision of AS, in China, can improve the coal consumption rate and the system-wide load factor as well as reduce the total system cost for the provision of AS significantly.
Mingtao Yao; Zhaoguang Hu; Froylan Sifuentes; Ning Zhang. Integrated Power Management of Conventional Units and Industrial Loads in China’s Ancillary Services Scheduling. Energies 2015, 8, 3955 -3977.
AMA StyleMingtao Yao, Zhaoguang Hu, Froylan Sifuentes, Ning Zhang. Integrated Power Management of Conventional Units and Industrial Loads in China’s Ancillary Services Scheduling. Energies. 2015; 8 (5):3955-3977.
Chicago/Turabian StyleMingtao Yao; Zhaoguang Hu; Froylan Sifuentes; Ning Zhang. 2015. "Integrated Power Management of Conventional Units and Industrial Loads in China’s Ancillary Services Scheduling." Energies 8, no. 5: 3955-3977.
With the development of smart grid, demand-side resources (DSR) will play an increasingly important role in the power balance of supply and demand. In addition, the requirement of a low-carbon smart grid means some policy backgrounds, such as carbon emissions trading (CET), should not be ignored. Under these circumstances, it is a good idea to construct a novel unit commitment (UC) model. This paper proposes a model that not only takes advantage of various resources on the demand side, such as electric vehicles, demand response, and distributed generation, but also reflects the effects of CET on generation schedule. Then, an improved particle swarm optimization (IPSO) algorithm is applied to solve the problem. In numerical studies, we analyze the impacts of DSR and CET on the results of UC, respectively. In addition, two meaningful experiments are conducted to study the approaches to allocate emission quotas and the effects of price transmission mechanism.
Ning Zhang; Zhaoguang Hu; Daihong Dai; Shuping Dang; Mingtao Yao; Yuhui Zhou. Unit Commitment Model in Smart Grid Environment Considering Carbon Emissions Trading. IEEE Transactions on Smart Grid 2015, 7, 420 -427.
AMA StyleNing Zhang, Zhaoguang Hu, Daihong Dai, Shuping Dang, Mingtao Yao, Yuhui Zhou. Unit Commitment Model in Smart Grid Environment Considering Carbon Emissions Trading. IEEE Transactions on Smart Grid. 2015; 7 (1):420-427.
Chicago/Turabian StyleNing Zhang; Zhaoguang Hu; Daihong Dai; Shuping Dang; Mingtao Yao; Yuhui Zhou. 2015. "Unit Commitment Model in Smart Grid Environment Considering Carbon Emissions Trading." IEEE Transactions on Smart Grid 7, no. 1: 420-427.
As a major CO2 emission source, the low-carbon development of the power sector requires the sector’s own efforts and the cooperation with other industries, especially in the context of rapid development of renewable generation technologies. The industrial demand response resources (IDRR) will be helpful to improve wind power penetration and bring low-carbon benefits if they are utilized to provide ancillary services (AS) for the power system. In this paper, demand response (DR) characteristics of industrial users are firstly analyzed according to their production process and electricity consumption distribution. In order to have an in-depth study of the response mechanism of industrial loads to provide AS, cement and aluminum smelter are selected as two typical IDRR, and the AS type they provided and response mechanism are analyzed. Based on the data of these two industries in certain provinces of China, low-carbon benefits considering IDRR to provide AS are analyzed.
Mingtao Yao; Zhaoguang Hu; Ning Zhang; Wei Duan; Jian Zhang. Low-carbon benefits analysis of energy-intensive industrial demand response resources for ancillary services. Journal of Modern Power Systems and Clean Energy 2015, 3, 131 -138.
AMA StyleMingtao Yao, Zhaoguang Hu, Ning Zhang, Wei Duan, Jian Zhang. Low-carbon benefits analysis of energy-intensive industrial demand response resources for ancillary services. Journal of Modern Power Systems and Clean Energy. 2015; 3 (1):131-138.
Chicago/Turabian StyleMingtao Yao; Zhaoguang Hu; Ning Zhang; Wei Duan; Jian Zhang. 2015. "Low-carbon benefits analysis of energy-intensive industrial demand response resources for ancillary services." Journal of Modern Power Systems and Clean Energy 3, no. 1: 131-138.