计及碳交易和价格型需求响应的热电联合低碳经济调度

doi:10.16180/j.cnki.issn1007-7820.2023.10.010

Abstract

Abstract:

In view of the problems of thermoelectric conflict and abandoned wind power during winter heating, a low-carbon economic dispatch model for combined heat and power that takes into account carbon trading costs and price-based demand response is proposed, while electric boilers and heat storage devices are introduced to decouple the coupling limits of thermoelectricity to study the impact of different operation modes on optimal dispatch. Carbon trading costs are considered in the system to limit carbon emissions, and the user-side demand response is used to enhance the peak regulation capability of the grid and optimize the load curve, effectively cutting the peak-to-valley difference in load and providing space for wind power to go online. Finally, the CPLEX solver is used for solving and simulation analysis is carried out based on the improved IEEE-30 node system. The results show that the wind power consumption is increased by 83.72% and carbon emissions are reduced by 2 211 t under the scheduling method proposed in this study, which verifies the reliability of the scheduling model.

Key words: combined heat and power generation, abandoned wind power, carbon transaction cost, optimal scheduling, demand respons, thermoelectric coupling, carbon emissions, CPLEX

CLC Number:

TM734

WANG Yumei,ZHANG Jiqin,ZHOU Yongxin. Combined Heat and Power Low-Carbon Economic Scheduling Considering Carbon Trading and Price Demand Response[J].Electronic Science and Technology, 2023, 36(10): 74-81.

Figures/Tables 13

Figure 1.

Figure 2.

Table 1.

Table 2.

Table 3.

Figure 3.

Table 4.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Figure 9.

References 20

[1]	胡弘, 韦化, 李昭昱. 风电接入下核电参与电力系统调峰的协调优化模型[J]. 电力自动化设备, 2020, 40(5):31-39.
	Hu Hong, Wei Hua, Li Zhaoyu. Coordinated optimization model considering nuclear power participating in peak load regulation of power system with wind power[J]. Electric Power Automation Equipment, 2020, 40(5):31-39.
[2]	许汉平, 李姚旺, 苗世洪, 等. 考虑可再生能源消纳效益的电力系统“源-荷-储”协调互动优化调度策略[J]. 电力系统保护与控制, 2017, 45(17):18-21.
	Xu Hanping, Li Yaowang, Miao Shihong, et al. Optimiz-ation dispatch strategy considering renewable energy consumptive benefits based on“source-load-energy storage” coordination in power system[J]. Power System Protection and Control, 2017, 45(17): 18-25.
[3]	李军徽, 邢志同, 穆钢, 等. 供热期调峰约束下电网弃风情况分析[J]. 太阳能学报, 2018, 39(3):596-602.
	Li Junhui, Xing Zhitong, Mu Gang, et al. Analysis on wind power curtailment under restriction of peak load regulation during heating period[J]. Acta Energiae Solaris Sinica, 2018, 39(3):596-602.
[4]	杨秋霞, 支成, 袁冬梅, 等. 基于启停电锅炉与储热装置协调供热的风电消纳低碳经济调度[J]. 太阳能学报, 2020, 41(9):21-28.
	Yang Qiuxia, Zhi Cheng, Yuan Dongmei, et al. Wind power accommodation low-carbon economic dispatch based on coordination between automatic start-stop electric boiler and heat accumulator[J]. Acta Energiae Solaris Sinica, 2020, 41(9):21-28.
[5]	刘海涛, 朱海南, 李丰硕, 等. 计及碳成本的电-气-热-氢综合能源系统经济运行策略[J]. 电力建设, 2021, 42(12):21-29. doi: 10.12204/j.issn.1000-7229.2021.12.003
	Liu Haitao, Zhu Hainan, Li Fengshuo, et al. Economic o-peration strategy of electric-gas-heat-hydrogen integra-ted energy system considering carbon cost[J]. Electric Power Construction, 2021, 42(12):21-29. doi: 10.12204/j.issn.1000-7229.2021.12.003
[6]	崔杨, 邓贵波, 王铮, 等. 计及碳交易的光热电站与风电系统低碳经济调度策略[J]. 电力自动化设备, 2021, 41(9): 232-239.
	Cui Yang, Deng Guibo, Wang Zheng, et al. Low-carbon economic scheduling strategy for power system with concentrated solar power plant and wind power considering carbon trading[J]. Electric Power Automation Equipment, 2021, 41 (9):232-239.
[7]	谷万江, 王飞, 田小蕾, 等. 考虑储能及碳交易成本的电热联合系统优化调度策略[J]. 电网与清洁能源, 2020, 36 (7):109-118.
	Gu Wanjiang, Wang Fei, Tian Xiaolei, et al. Optimal sc-heduling strategy of electric-thermal combined system considering energy storage and carbon trading cost[J]. Advances of Power System and Hydroelectric Engineering, 2020, 36(7):109-118.
[8]	王振浩, 许京剑, 田春光, 等. 计及碳交易成本的含风电电力系统热电联合调度[J]. 太阳能报, 2020, 41(12):245-253.
	Wang Zhenhao, Xu Jingjian, Tian Chunguan, et al. Com-bined heat and power scheduling strategy considering carbon trading cost in wind power system[J]. Acta Energiae Solaris Sinica, 2020, 41(12):245-253.
[9]	崔杨, 张汇泉, 仲悟之, 等. 计及价格型需求响应及CSP电站参与的风电消纳日前调度[J]. 电网技术, 2020, 44(1):183-191.
	Cui Yang, Zhang Huiquan, Zhong Wuzhi, et al. Day-ahe-ad scheduling considering participation of price-based demand response and CSP plant in wind power accommodation[J]. Power System Technology, 2020, 44(1):183-191.
[10]	杨冬锋, 徐扬, 姜超. 考虑多类型需求响应的电-热联合系统多时间尺度协调调度[J]. 太阳能学报, 2021, 42(10):282-289.
	Yang Dongfeng, Xu Yang, Jiang Chao. Multiple time-sc-ale coordinated scheduling of combined electric-thermal system considering multi-type demand response[J]. Acta Energiae Solaris Sinica, 2021, 42(10):282-289.
[11]	陈美玲, 高岩. 计及源荷双侧不确定性的综合能源系统优化配置[J]. 上海理工大学学报, 2022, 44(1):77-84,102.
	Chen Meiling, Gao Yan. Optimal configuration of integrated energy system with uncertain generation and load[J]. Journal of University of Shanghai for Scineceand Technology, 2022, 44(1):77-84,102.
[12]	王海云, 杨宇, 于希娟, 等. 基于需求侧响应的电热综合能源系统风电消纳低碳经济调度[J]. 燕山大学学报, 2021, 45(2):142-152.
	Wang Haiyun, Yang Yu, Yu Xijuan, et al. Wind power accommodation low-carbon economic dispatch of the integrated electrical and heating systems based on demand response[J]. Journal of Yanshan University, 2021, 45(2):142-152.
[13]	刘浩田, 陈锦, 朱熹, 等. 一种基于价格弹性矩阵的居民峰谷分时电价激励策略[J]. 电力系统保护与控制, 2021, 49(5):116-123.
	Liu Haotian, Chen Jin, Zhu Xi, et al. An incentive strategy of residential peak-valley price based on price elasticity matrix of demand[J]. Power System Protection and Control, 2021, 49(5):116-123.
[14]	周正威, 郝亚群, 张雪映. 基于需求响应的风电-抽水蓄能系统调度模型[J]. 电子科技, 2019, 32(4):77-80,84.
	Zhou Zhengwei, Hao Yaqun, Zhang Xueying. A dispatch model for wind power and pumped-storage system based on demand response[J]. Electronic Science and Technology, 2019, 32(4):77-80,84.
[15]	罗毅, 邱实. 基于负荷侧响应的含储热热电联产的风电消纳模型[J]. 太阳能学报, 2021, 42(2):90-96.
	Luo Yi, Qiu Shi. A wind power consumption model of CHP with thermal storage based on demand response[J]. Acta Energiae Solaris Sinica, 2021, 42(2):90-96.
[16]	陈林, 蔺红, 成后炉. 基于附加热源提高风电消纳的电热联合调度[J]. 太阳能学报, 2021, 42(10):258-264.
	Chen Lin, Lin Hong, Cheng Houlu. Electrothermal com-bined dispatching based on additional heat source improve wind power consumption[J]. Acta Energiae Solaris Sinica, 2021, 42(10):258-264.
[17]	彭元, 娄素华, 范越, 等. 考虑火电机组储热改造的电力系统低碳经济调度[J]. 电网技术, 2020, 44(9):3339-3345.
	Peng Yuan, Lou Suhua, Fan Yue, et al. Low-carbon eco-nomical dispatch of power system considering thermal energy storage in thermal power units[J]. Power System Technology, 2020, 44(9):3339-3345.
[18]	崔杨, 陈志, 严干贵, 等. 基于含储热热电联产机组与电锅炉的弃风消纳协调调度模型[J]. 中国电机工程学报, 2016, 36(15):4072-4081.
	Cui Yang, Chen Zhi, Yan Gangui, et al. Coordinated wind power accommodating dispatch model based on electric boiler and CHP with thermal energy storage[J]. Proceedings of the CSEE, 2016, 36(15):4072-4081.
[19]	Wang W, Huang S, Zhang G, et al. Optimal operation of an integrated electricity-heat energy system considering flexible resources dispatch for renewable integration[J]. Journal of Modern Power Systems and Clean Energy, 2021, 9(4):699-710. doi: 10.35833/MPCE.2020.000917
[20]	李家珏, 李平, 王刚, 等. 计及弃风消纳的热电联产系统的日前调度模型[J]. 太阳能学报, 2021, 42(9):295-301.
	Li Jiajue, Li Ping, Wang Gang, et al. Day-to-day schedu-ling model for cogeneration system accounting for wind power accommodation[J]. Acta Energiae Solaris Sinica, 2021, 42(9):295-301.

机组	最大出力	最小出力	爬坡率	燃料成本系数
机组	P_max/MW	P_min/MW	R_i,u/ MW·h^-1	a_i/元· MW^-2	b_i/元· MW^-1	c_i/元
3	50	25	25	0.002 3	100	1 250
4	35	10	18	0.001 5	225	167
5	30	10	15	0.000 9	150	500
6	40	12	20	0.000 8	200	500

电价时段	电价/元· (MW·h)^-1	时段
峰	625	12∶00~14∶00,19∶00~22∶00
谷	375	23∶00~07∶00
平	500	08∶00~11∶00,15∶00~18∶00

机组	最大发电功率/MM	最小发电功率/MW	最大供热功率/MW	a_i /元·MW^-2	b_i /元·MW^-1	c_i /元	c_v	c_m	向上爬坡速率	向下爬坡速率
1	200	100	250	0.004 4	13.29	39.00	0.15	0.75	50	50
2	200	100	250	0.004 4	13.29	39.00	0.15	0.75	50	50

场景	综合成本/万元	风电消纳量/%	碳排放量/t
1	38.28	16.28	8 632
2	40.78	93.75	6 942
3	41.12	100.00	6 421

Combined Heat and Power Low-Carbon Economic Scheduling Considering Carbon Trading and Price Demand Response

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 13

References 20

Related Articles 7

Metrics

Comments

Recommended 0

[1]	LIU Jinzhi,ZHANG Huilin,MA Lixin,WANG Hao,TANG Zheng. Dynamic Optimal Scheduling Strategy for Integrated Energy Systems Considering Shiftable Loads [J]. Electronic Science and Technology, 2023, 36(4): 78-83.
[2]	GUO Chengwei,TIAN Shu,LIU Minghang. Research on Dispatching of Multi-Source Combined Power Generation System Containing Hydrogen Energy Storage [J]. Electronic Science and Technology, 2023, 36(2): 61-66.
[3]	WANG Yumei,WANG Lulu. Distribution Network Dispatching Optimization Strategy Energy Storage Based on Time-of-Use Electricity Price and User-Side [J]. Electronic Science and Technology, 2023, 36(2): 7-12.
[4]	SHI Zhenli,WEI Yewen. Multi-Objective Optimization of Active Distribution Network Based on Particle Swarm Optimization [J]. Electronic Science and Technology, 2022, 35(9): 7-14.
[5]	WANG Fuzhong,LI Runyu,ZHANG Hongwei,GUO Jiangzhen,ZHANG Li. Research on Flexible Load Control Strategy of Air Conditioning in Power Demand Side [J]. Electronic Science and Technology, 2021, 34(8): 58-63.
[6]	ZHANG Darui,WANG Ding,WANG Xianying. Fabrication and Properties of GaN Energy Conversion Devices [J]. Electronic Science and Technology, 2020, 33(3): 62-65.
[7]	ZHOU Zhengwei,HAO Yaqun,ZHANG Xueying. A Dispatch Model for Wind Power and Pumped-storage System Based on Demand Response [J]. Electronic Science and Technology, 2019, 32(4): 77-81.