Books
[1] F. Wang, K. Li, Y. Jia, Z. Mi, Y. Yu. Theory and technology of demand-side resource aggregation and response, Science Press, 2022.
Journal Papers
[1] K. Li, Y. Wang, N. Zhang, F. Wang, “Precision and Accuracy Co-optimization Based Demand Response Baseline Load Estimation Using Bi-directional Data”, IEEE Trans. Smart Grid, Early access, 2022.
[2] K. Li, Y. Wang, N. Zhang, F. Wang, C. Huang, “Spatio-temporal Granularity Co-optimization Based Monthly Electricity Consumption Forecasting”, CSEE J. Power Energy Syst., Early access, 2022.
[3] 刘春阳，李康平*，纪陵，米增强. 基于聚类-估计联动的需求响应集群基线负荷估计方法，电力系统自动化（已录用）.
[4] P. Tao, F. Xu, Z. Dong, C. Zhang, X. Peng, J. Zhao, K. Li, F. Wang. :”Graph convolutional network-based aggregated demand response baseline load estimation,” Energy, vol. 251, pp.123847, 2022.
[5] F. Wang, X. Lu, X. Chang, X. Cao, S. Yan, K. Li*, et al, “Household Profile Identification for Behavioral Demand Response: A Semi-supervised Learning Approach Using Smart Meter Data,” Energy, vol. 238, pp.121728, 2022.
[6] F. Wang, X. Ge, Z. Dong, J. Yan, K. Li*, X. Fei, et al. “Joint Energy Disaggregation of Behind-the-Meter PV and Battery Storage: A contextually Supervised Source Separation Approach,” IEEE Trans. Ind. Appl., vol.58, no.2, pp.1490-1501, Mar.Apr. 2022.
[7] K. Li, J. Yan, L. Hu, F. Wang and N. Zhang, “Two-stage Decoupled Estimation Approach of Aggregated Baseline Load under High Penetration of Behind-the-Meter PV System,” IEEE Trans. Smart Grid,vol.12, no. 6, pp. 4876-4885, Nov. 2021.
[8] W. Huang, X. Zhang, K. Li, N. Zhang, G. Strbac and C. Kang, “Resilience Oriented Planning of Urban Multi-Energy Systems With Generalized Energy Storage Sources,” IEEE Trans. on Power Syst., Early Access.
[9] Z. Li, K. Li, F. Wang, Z. Xuan, Z. Mi, W. Li, et al, “Monthly Electricity Consumption Forecasting: A Step-Reduction Strategy and Autoencoder Neural Network,” IEEE Ind. Appl. Mag., vol. 27, no. 2, pp. 90-102, Mar.-Apr.2021.
[10] X. Lu, K. Li, F. Wang, Z. Mi, and J. Lai, “Optimal Bidding Strategy of DER Aggregator Considering Bilateral Uncertainty via Information Gap Decision Theory,” IEEE Trans. Ind. Appl., vol. 57, no. 1, pp. 158–169, Jan. 2021.
[11] X. Lu, P. Zhang, K. Li, F. Wang, Z. Li, Z. Zhen, et al, “Data Center Aggregators’ Optimal Bidding and Benefit Allocation Strategy Considering the Spatiotemporal Transfer Characteristics,” IEEE Trans. Ind. Appl., vol. 57, no. 5, pp. 4486-4499, Sept.-Oct. 2021.
[12] X. Lu, X. Ge, K. Li, F. Wang, H. Shen, P. Tao, et al, “Optimal Bidding Strategy of Demand Response Aggregator Based on Customers Responsiveness Behaviors Modeling under Different Incentives,” IEEE Trans. Ind. Appl., vol. 57, no. 4, pp. 3329–3340, Jul.-Aug. 2021.
[13] Y. Fu, H. Chai, Z. Zhen, F. Wang, X. Xu, K. Li, et al, “Sky Image Prediction Model Based on Convolutional Auto-encoder for Minutely Solar PV Power Forecasting,” IEEE Trans. Ind. Appl., vol. 57, no. 4, pp. 3272–3281, Jul.-Aug. 2021.
[14] F. Wang, Z. Xuan, Z. Zhen, K. Li, T. Wang, and M. Shi, “A day-ahead PV Power Forecasting Method Based on LSTM-RNN Model and Time Correlation Modification Under Partial Daily Pattern Prediction Framework,”, vol. 212, p. 112766, May. 2020. (ESI highly cited paper )
[15] S. Yan, K. Li, F. Wang, X. Ge, X. Lu, Z. Mi, et al, “Time-frequency Features Combination-based Household Characteristics Identification Approach Using Smart Meter Data,” IEEE Trans. Ind. Appl., vol. 56, no. 3, pp. 2251-2262, May-Jun. 2020.
[16] K. Li, X. Cao, X. Ge, F. Wang, X. Lu, M. Shi, et al, “Meta-heuristic Optimization Based Two-stage Residential Load Pattern Clustering Approach Considering Intra-cluster Compactness and Inter-cluster Separation,” IEEE Trans. Ind. Appl., vol. 56, no. 4, pp. 3375-3384, Jul.-Aug. 2020.
[17] F. Wang*, B. Xiang, K. Li*, X. Ge, H. Lu, J. Lai, et al, “Smart Households’ Aggregated Capacity Forecasting for Load Aggregators Under Incentive-based Demand Response Programs,” IEEE Trans. Ind. Appl., vol. 56, no. 2, pp. 1086-1097, Mar.-Apr. 2020. (ESI highly cited paper )
[18] X. Lu, K. Li, H. Xu, F. Wang, Z. Zhou, and Y. Zhang, “Fundamentals and Business Model for Resource Aggregator of Demand Response in Electricity Markets,” Energy, vol. 204, p. 117885, Aug. 2020.
[19] F. Wang, X. Ge, P. Yang, K. Li*, Z. Mi, P. Siano, et al, “Day-ahead Optimal Bidding and Scheduling Strategies for DER Aggregator Considering Responsive Uncertainty Under Real-time Pricing,” Energy, vol. 213, pp. 118765, Dec. 2020.
[20] Z. Xuan, X. Gao, K. Li, F. Wang, X. Ge, and Y. Hou, “PV-Load Decoupling Based Demand Response Baseline Load Estimation Approach for Residential Customer with Distributed PV System,” IEEE Trans. Ind. Appl., vol. 56, no. 6, pp. 6128-6137, Nov.-Dec. 2020.
[21] F. Wang, Z. Xuan, Z. Zhen, Y. Li, K. Li, L. Zhao, et al, “A minutely Solar Irradiance Forecasting Method Based on Real-time Sky Image-irradiance Mapping Model,” Energy Convers. Manag., vol. 220, p. 113075, Sept. 2020.
[22] Z. Zhen, S. Pang, F. Wang*, K. Li*, Z. Li, H. Ren, et al, “Pattern Classification and PSO Optimal Weights Based Sky Images Cloud Motion Speed Calculation Method for Solar PV Power Forecasting,” IEEE Trans. Ind. Appl., vol. 55, no. 4, pp. 3331–3342, Jul.-Aug. 2019.
[23] K. Li, F. Wang, Z. Mi, M. Fotuhi-Firuzabad, N. Duić, and T. Wang, “Capacity and Output Power Estimation Approach of Individual Behind-the-meter Distributed Photovoltaic System for Demand Response Baseline Estimation,” Appl. Energy, vol. 253, p. 113595, Nov. 2019.
[24] K. Li, L. Liu, F. Wang, T. Wang, N. Duić, M. Shafie-khah, et al, “Impact Factors Analysis on the Probability Characterized Effects of Time of Use Demand Response Tariffs Using Association Rule Mining Method,” Energy Convers. Manag., vol. 197, p. 111891, Oct. 2019.
[25] K. Li, Q. Mu, F. Wang, Y. Gao, G. Li, M. Shafie-khah, et al, “A Business Model Incorporating Harmonic Control as a Value-added Service for Utility-owned Electricity Retailers,” IEEE Trans. Ind. Appl., vol. 55, no. 5, pp. 4441–4450, Sept.-Oct. 2019.
[26] F. Wang, X. Ge, K. Li* and Z. Mi, “Day-ahead Market Optimal Bidding Strategy and Quantitative Compensation Mechanism Design for Load Aggregator Engaging Demand Response,” IEEE Trans. Ind. Appl., vol. 55, no. 6, pp. 5564–5573, Nov.-Dec. 2019.
[27] F. Wang, K. Li, L. Zhou, H. Ren, J. Contreras, M. Shafie-khah, et al, “Daily Pattern Prediction Based Classification Modeling Approach for Day-ahead Electricity Price Forecasting,” Int. J. Electr. Power Energy Syst., vol. 105, pp. 529–540, Feb. 2019.
[28] F. Wang, K. Li, C. Liu, Z. Mi, M. Shafie-Khah, and J. P. S. Catalão, “Synchronous Pattern Matching Principle-based Residential Demand Response Baseline Estimation: Mechanism Analysis and Approach Description,” IEEE Trans. Smart Grid, vol. 9, no. 6, pp. 6972–6985, Nov. 2018.
[29] F. Wang*, K. Li*, N. Duić, Z. Mi, B.M. Hodge, M. Shafie-khah, et al, “Association Rule Mining Based Quantitative Analysis Approach of Household Characteristics Impacts on Residential Electricity Consumption Patterns,” Energy Convers. Manag., vol. 171, pp. 839–854, Sep. 2018.
[30] F. Wang, H. Xu, T. Xu, K. Li, M. Shafie-khah, and J. P. S. Catalão, “The Values of Market-based Demand Response on Improving Power System Reliability Under Extreme Circumstances,” Appl. Energy, vol. 193, pp. 220–231, May. 2017.
Conference Proceedings
[1] Xin Chen, Zhenghui Li, Fei Wang, Kangping Li, João P. S. Catalão, “Monthly Net Electricity Consumption Prediction Under High Penetration of Distributed Photovoltaic System,” 2021 International Conference on Smart Energy Systems and Technologies (SEST), Sept. 6-8, Vaasa, Finland.
[2] Yuqing Wang, Zhenghui Li, Fei Wang, Zhao Zhen, Payman Dehghanian, João P. S. Catalão, Kangping Li, Mahmud Fotuhi-Firuzabad, “Greedy Clustering-based Monthly Electricity Consumption Forecasting Model,” 2021 IEEE Industry Applications Society Annual Meeting, Oct. 10-14, Vancouver, BC, Canada.
[3] Jichuan Yan, Xinxin Ge, Xiaoxing Lu, Fei Wang, Kangping Li, Hongtao Shen, Peng Tao, “Joint Energy Disaggregation of Behind-the-Meter PV and Battery Storage: A Contextually Supervised Source Separation Approach,” 2021 IEEE/IAS 57th Industrial and Commercial Power Systems Technical Conference (I&CPS), Apr. 27-30, Las Vegas, NV, USA.
[4] Xiangchu Xu, Kangping Li, Fei Wang, Zengqiang Mi, Yulong Jia, Yanwei Jing, “A Multi-timescale Response Capability Evaluation Model of EV Aggregator Considering Customers’ Response Willingness,” 2020 IEEE Industry Applications Society Annual Meeting, Oct. 10-16, Detroit, MI, USA.
[5] Xiaoxing Lu, Kangping Li, Fei Wang, Zhao Zhen, Jingang Lai, Miadreza Shafie-khah, João P. S. Catalão, “Optimal Bidding Strategy of an Aggregator Based on Customers’ Responsiveness Behaviors Modeling,” 2020 IEEE Industry Applications Society Annual Meeting, Oct. 10-16, Detroit, MI, USA.
[6] Hua Chai, Zhao Zhen, Kangping Li, Fei Wang, Payman Dehghanian, Miadreza Shafie-khah, João P. S. Catalão, “Convolutional Auto-encoder Based Sky Image Prediction Model for Minutely Solar PV Power Forecasting,” 2020 IEEE Industry Applications Society Annual Meeting, Oct. 10-16, Detroit, MI, USA.
[7] Xinxin Ge, Kangping Li, Fei Wang, Zhao Zhen, Tieqiang Wang, “Dissatisfaction Cost Minimization-Based Decentralized Demand Response Approach Considering ISO’s Operation Requirements,” 2020 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia), Jul. 13-15, Weihai, China.
[8] Peng Zhang, Kangping Li, Fei Wang, Zhao Zhen, Tieqiang Wang, “Optimal Bidding Strategy for Data Center Aggregators Considering Spatio-Temporal Transfer Characteristics,” 2020 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia), Jul. 13-15, Weihai, China.
[9] Peng Zhang, Kangping Li, Fei Wang, Zengqiang Mi, Hongyu Chen, Shengqiang Chang, “A Cooperation Model of Data Center Cluster and Electricity Retailer Base on Demand Response,” 2020 IEEE/IAS 56th Industrial and Commercial Power Systems Technical Conference (I&CPS), Jun. 29 – Jul, 28, Las Vegas, NV, USA.
[10] Zhenghui Li, Kangping Li, Fei Wang, Zengqiang Mi, Wanwei Li, Payman Dehghanian, “Auto-encoder Neural Network-Based Monthly Electricity Consumption Forecasting Method Using Hourly Data,” 2020 IEEE/IAS 56th Industrial and Commercial Power Systems Technical Conference (I&CPS), Jun. 29 – Jul, 28, Las Vegas, NV, USA.
[11] Xiaoxing Lu, Kangping Li, Fei Wang, Zengqiang Mi, Jingang Lai, “Optimal Bidding Strategy of DER Aggregator Considering Bilateral Uncertainty via Information Gap Decision Theory,” 2020 IEEE/IAS 56th Industrial and Commercial Power Systems Technical Conference (I&CPS), Jun. 29 – Jul, 28, Las Vegas, NV, USA.
[12] Zhao Zhen, Zhiming Xuan, Kangping Li, Fei Wang, Yuzhang Lin, Min Shi, Rui Yin, Tieqiang Wang, “Surface Irradiance Distribution Mapping Model for Photovoltaic Power Station Based on Ground-based Sky Images,” 2020 IEEE/IAS 56th Industrial and Commercial Power Systems Technical Conference (I&CPS), Jun. 29 – Jul, 28, Las Vegas, NV, USA.
[13] Zhenghui Li, Kangping Li, Zhiming Xuan, Zhao Zhen and Fei Wang, “Decomposition-Accumulation Principle-Based Monthly Electricity Consumption Forecasting Approach Using EMD-XGBoost Hybrid Model”, 2019 IEEE Sustainable Power & Energy Conference, Nov.21-Nov.23, Beijing, China.
[14] Biao Xiang, Kangping Li, Xinxin Ge, Zhao Zhen, Xiaoxing Lu and Fei Wang, “Day-ahead Probabilistic Forecasting of Smart Households’ Demand Response Capacity under Incentive-based Demand Response Program”, 2019 IEEE Sustainable Power & Energy Conference, Nov.21-Nov.23, Beijing, China.
[15] Kangping Li, Xinxin Ge, Xiaoxing Lu, Fei Wang and Zengqiang Mi, “Meta-Heuristic Optimization Based Two-stage Residential Load Pattern Clustering Approach Considering Intra-cluster Compactness and Inter-cluster Separation”, 2019 IEEE IAS Annual Meeting, Sep.29-Oct.3, Baltimore, USA.
[16] Biao Xiang, Kangping Li, Xinxin Ge, Fei Wang, Jingang Lai and Payman Dehghanian, “Smart Households’ Available Aggregated Capacity Day-ahead Forecast Model for Load Aggregators under Incentive-based Demand Response Program”, 2019 IEEE IAS Annual Meeting, Sep.29-Oct.3, Baltimore, USA.
[17] Xinxin Ge, Kangping Li, Fei Wang and Zengqiang Mi, “Day-ahead Market Optimal Bidding Strategy and Quantitative Compensation Mechanism Design for Load Aggregator Engaging Demand Response”, 2019 IEEE PES General Meeting, Aug. 4-8, 2019, Atlanta, USA.
[18] Xinxin Ge, Kangping Li, Fei Wang and Zengqiang Mi, “Day-ahead Market Optimal Bidding Strategy of Load Aggregator Engaging Demand Response Program Considering Price Uncertainty”, 2019 IEEE 55th Industrial and Commercial Power Systems Technical Conference(I&CPS ), May. 5-8, 2019, Calgary, AB, Canada.
[19] Kangping Li, Jianfeng Che, Bo Wang, Jingjing Zhang, Fei Wang and Zengqiang Mi, “A Meta-Heuristic Optimization Based Residential Load Pattern Clustering Approach Using Improved Gravitational Search Algorithm”, The 9th Conference on Innovative Smart Grid Technologies (2018 ISGT North America ), Feb. 19-22, 2018, Washington, DC, USA.
[20] Kangping Li, Bo Wang, Zheng Wang, Fei Wang, Zengqiang Mi and Zhao Zhen, “A Baseline Load Estimation Approach for Residential Customer based on Load Pattern Clustering”, The 9th International Conference on Applied Energy (ICAE2017 ), 21-24 August 2017, Cardiff, UK.
[21] Kangping Li, Fei Wang, Zhao Zhen, et al., “Analysis on residential electricity consumption behavior using improved k-means based on simulated annealing algorithm,” in 2016 IEEE Power and Energy Conference at Illinois (PECI 2016 ), February 2016.
[22] Kangping Li, Fei Wang, Zhao Zhen, Yujing Sun, Zengqiang Mi, Hongbin Sun, Chun Liu, Bo Wang and Jing Lu, “Photovoltaic plant operating statuses identification model based on support vector machine using loss quantity of electricity feature parameters,” in International Conference on Renewable Power Generation (RPG 2015 ), 2015, pp. 1–6.