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CLC number: TM732

On-line Access: 2016-05-04

Received: 2015-12-22

Revision Accepted: 2016-03-10

Crosschecked: 2016-04-14

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Yu-hang Xia

http://orcid.org/0000-0002-4586-4537

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Frontiers of Information Technology & Electronic Engineering  2016 Vol.17 No.5 P.479-488

http://doi.org/10.1631/FITEE.1500467


Carbon emission impact on the operation of virtual power plant with combined heat and power system


Author(s):  Yu-hang Xia, Jun-yong Liu, Zheng-wen Huang, Xu Zhang

Affiliation(s):  School of Electrical Engineering and Information, Sichuan University, Chengdu 610065, China; more

Corresponding email(s):   scxyh@foxmail.com

Key Words:  Virtual power plant (VPP), Carbon emissions, Electric boiler, Wind power, Combined heat and power (CHP)


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Yu-hang Xia, Jun-yong Liu, Zheng-wen Huang, Xu Zhang. Carbon emission impact on the operation of virtual power plant with combined heat and power system[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(5): 479-488.

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Abstract: 
A virtual power plant (VPP) can realize the aggregation of distributed generation in a certain region, and represent distributed generation to participate in the power market of the main grid. With the expansion of VPPs and ever-growing heat demand of consumers, managing the effect of fluctuations in the amount of available renewable resources on the operation of VPPs and maintaining an economical supply of electric power and heat energy to users have been important issues. This paper proposes the allocation of an electric boiler to realize wind power directly converted for supplying heat, which can not only overcome the limitation of heat output from a combined heat and power (CHP) unit, but also reduce carbon emissions from a VPP. After the electric boiler is considered in the VPP operation model of the combined heat and power system, a multi-objective model is built, which includes the costs of carbon emissions, total operation of the VPP and the electricity traded between the VPP and the main grid. The model is solved by the CPLEX package using the fuzzy membership function in Matlab, and a case study is presented. The power output of each unit in the case study is analyzed under four scenarios. The results show that after carbon emission is taken into account, the output of low carbon units is significantly increased, and the allocation of an electric boiler can facilitate the maximum absorption of renewable energy, which also reduces carbon emissions from the VPP.

The authors describe in the paper how to operate a VPP (Heat and power) taking into account also the minimizing of CO2 emission. The VPP concept is originally used any for smoothing of electric power generation so the idea of combining the heat and power generation in a VPP and optimising the operation concerning the CO2 emission is quite new.

碳排放对虚拟发电厂热电联合系统运行的影响

目的:现有的研究在对虚拟发电厂运行建模时,通常只考虑了用户的电能需求,而且在利用热电联产机组(CHP)对用户供热时,不仅增加了虚拟发电厂的整体碳排放量,还会造成大量的弃风。考虑到虚拟发电厂内部风电机组出力时段和用户热能需求的互补性,本文提出了考虑碳排放的虚拟发电厂热电联合系统运行模型。
创新点:提出了在虚拟发电厂中配置电锅炉消纳风电机组出力。利用风电机组和电锅炉不仅能够减少虚拟发电厂的整体碳排放,促进风电的消纳,还能突破传统热电联产机组的供热水平,降低虚拟发电厂的运行成本。
方法:将电锅炉应用到虚拟发电厂的热电联合系统中后,建立了一个包含虚拟发电厂碳排放成本、虚拟发电厂运行成本和虚拟发电厂与主网的电量交易成本的多目标模型。根据模糊隶属度函数将其转化为单目标模型,并利用CPLEX工具包对其求解。然后分析了四种场景下的虚拟发电厂内部机组出力情况(图5-8)、碳排放量和电量交易成本。
结论:引入电锅炉后能够将热电联产机组的热电生产过程解耦,最大化消纳风电机组出力,降低虚拟发电厂的运行成本,还能显著降低虚拟发电厂的整体碳排放量。

关键词:虚拟发电厂;碳排放;电锅炉;风电;热电联合

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Reference

[1]Ackermann, T., Andersson, G., Söder, L., 2001. Distributed generation: a definition. Electr. Power Syst. Res., 57(3):195-204.

[2]Arslan, O., Karasan, O.E., 2013. Cost and emission impacts of virtual power plant formation in plug-in hybrid electric vehicle penetrated networks. Energy, 60:116-124.

[3]Bezdek, J.C., 1981. Pattern Recognition with Fuzzy Objective Function Algorithms. Springer-Verlag, New York, USA, p.155-192.

[4]Driesen, J., Katiraei, F., 2008. Design for distributed energy resources. IEEE Power Energy Mag., 6(3):30-40.

[5]Guan, D., Hubacek, K., Weber, C.L., et al., 2008. The drivers of Chinese CO2 emissions from 1980 to 2030. Glob. Environ. Change, 18(4):626-634.

[6]Hernandez, L., Baladron, C., Aguiar, J.M., et al., 2013. A multi-agent system architecture for smart grid management and forecasting of energy demand in virtual power plants. IEEE Commun. Mag., 51(1):106-113.

[7]Kieny, C., Berseneff, B., Hadjsaid, N., et al., 2009. On the concept and the interest of virtual power plant: some results from the European project Fenix. Proc. IEEE Power & Energy Society General Meeting, p.1-6.

[8]Li, Z.M., Zhang, F., Liang, J., et al., 2015. Optimization on microgrid with combined heat and power system. Proc. CSEE, 35(14):3569-3576 (in Chinese).

[9]Lombardi, P., Stötzer, M., Styczynski, Z., et al., 2011. Multi-criteria optimization of an energy storage system within a Virtual Power Plant architecture. Proc. IEEE Power and Energy Society General Meeting, p.1-6.

[10]Lund, H., Münster, E., 2003. Modelling of energy systems with a high percentage of CHP and wind power. Renew. Energy, 28(14):2179-2193.

[11]Mashhour, E., Moghaddas-Tafreshi, S.M., 2011. Bidding strategy of virtual power plant for participating in energy and spinning reserve markets—Part II: numerical analysis. IEEE Trans. Power Syst., 26(2):957-964.

[12]Mohd, A., Ortjohann, E., Schmelter, A., et al., 2008. Challenges in integrating distributed energy storage systems into future smart grid. Proc. IEEE Int. Symp. on Industrial Electronics, p.1627-1632.

[13]Pandžić, H., Kuzle, I., Capuder, T., 2013. Virtual power plant mid-term dispatch optimization. Appl. Energy, 101:134-141.

[14]Perroni, C., Rutherford, T.F., 1993. International trade in carbon emission rights and basic materials: general equilibrium calculations for 2020. Scand. J. Econ., 95(3):257-278.

[15]Pudjianto, D., Ramsay, C., Strbac, G., 2007. Virtual power plant and system integration of distributed energy resources. IET Renew. Power Gener., 1(1):10-16.

[16]Raab, A.F., Ferdowsi, M., Karfopoulos, E., et al., 2011. Virtual power plant control concepts with electric vehicles. Proc. 16th Int. Conf. on Intelligent System Application to Power Systems, p.1-6.

[17]Ruiz, N., Cobelo, I., Oyarzabal, J., 2009. A direct load control model for virtual power plant management. IEEE Trans. Power Syst., 24(2):959-966.

[18]Saboori, H., Mohammadi, M., Taghe, R., 2011. Virtual power plant (VPP), definition, concept, components and types. Proc. Asia-Pacific Power and Energy Engineering Conf., p.1-4.

[19]Skarvelis-Kazakos, S., Rikos, E., Kolentini, E., et al., 2013. Implementing agent-based emissions trading for controlling Virtual Power Plant emissions. Electr. Power Syst. Res., 102:1-7.

[20]Teleke, S., Baran, M.E., Huang, A.Q., et al., 2009. Control strategies for battery energy storage for wind farm dispatching. IEEE Trans. Energy Conv., 24(3):725-732.

[21]Ummels, B.C., Gibescu, M., Pelgrum, E., et al., 2007. Impacts of wind power on thermal generation unit commitment and dispatch. IEEE Trans. Energy Conv., 22(1):44-51.

[22]Wille-Haussmann, B., Erge, T., Wittwer, C., 2010. Decentralised optimisation of cogeneration in virtual power plants. Solar Energy, 84(4):604-611.

[23]Xia, Y.H., Liu, J.Y., 2016a. Review of virtual power plant based on distributed generation. Electr. Power Autom. Equip., 36(4):100-106, 115 (in Chinese).

[24]Xia, Y.H., Liu, J.Y., 2016b. Optimal scheduling of virtual power plant with risk management. J. Power Technol., 96(1):49-56.

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