A fuzzy mathematical model-based approach to customer-side energy management for power companies

[1] Yener, Y., Can, G. F. (2021). A fmea based novel intuitionistic fuzzy approach proposal: intuitionistic fuzzy advance mcdm and mathematical modeling integration. Expert Systems with Applications, (2008):115413. Search in Google Scholar

[2] Badia, G., Noguera, C. (2020). A General Omitting Types Theorem in Mathematical Fuzzy Logic. IEEE Transactions on Fuzzy Systems, PP(99), 1-1. Search in Google Scholar

[3] Xiao, Xian-Yong, Yuan-Qian, et al. (2016). Premium Power Valuation Method Based on Customer Perception of Utility for High-Technology Manufacturing Customers. IEEE Transactions on Power Delivery. Search in Google Scholar

[4] Kostkova, K., Omelina, L., Kycina, P., et al. (2013). An introduction to load management. Electric Power Systems Research, 184-191. Search in Google Scholar

[5] Abbas, A. O., Chowdhury, B. H. (2020). Using Customer-Side Resources for Market-Based Transmission and Distribution Level Grid Services – A Review. International Journal of Electrical Power & Energy Systems, 125. Search in Google Scholar

[6] Mohseni, S., Brent, A. C., Kelly, S., et al. (2021). Modelling utility-aggregator-customer interactions in interruptible load programmes using non-cooperative game theory. International Journal of Electrical Power & Energy Systems, 133(1), 107183. Search in Google Scholar

[7] Mechee, M. S., Mahdi, A. A. (2021). A Numerical Study for Solving Mathematical Fuzzy Population Model. Journal of Physics: Conference Series, 1999(1), 012109-. Search in Google Scholar

[8] Yousif, J., Saini, D. K. (2021). Fuzzy and Mathematical Effort Estimation Models for Web Applications. Search in Google Scholar

[9] Nien, S. H., Chen, L. H. (2021). Formulating Intuitionistic Fuzzy Regression Models: A Mathematical Programming Approach. Search in Google Scholar

[10] Nci, M., Büyük, M., Demir, H., et al. (2021). A review and research on fuel cell electric vehicles: Topologies, power electronic converters, energy management methods, technical challenges, marketing and future aspects. Renewable and Sustainable Energy Reviews, 137, 110648. Search in Google Scholar

[11] Parise, G., Parise, L., Martirano, L., et al. (2016). Wise Port and Business Energy Management: Port Facilities, Electrical Power Distribution. IEEE Transactions on Industry Applications, 52(1), 18-24. Search in Google Scholar

[12] Cheng, P. H., Huang, T. H., Chien, Y. W., et al. (2020). Demand-side management in residential community realizing sharing economy with bidirectional PEV while additionally considering commercial area. International Journal of Electrical Power & Energy Systems, 116, 105512. Search in Google Scholar

[13] Yuan, D., Lu, Z., Zhang, J., et al. (2019). A hybrid prediction-based microgrid energy management strategy considering demand-side response and data interruption. International Journal of Electrical Power & Energy Systems, 113, 139-153. Search in Google Scholar

[14] Wang, Y., Wang, L., Liu, B., et al. (2021). Research on Blind Super-Resolution Technology for Infrared Images of Power Equipment Based on Compressed Sensing Theory. Sensors, (12). Search in Google Scholar

[15] Liu, J., Tang, Q., Qiu, W., et al. (2021). Probability-Based Failure Evaluation for Power Measuring Equipment. Energies, 14. Search in Google Scholar

[16] Shi, C., Fei, J., Zhang, X., et al. (2020). Continuous Trust Evaluation of Power Equipment and Users Based on Risk Measurement. Scientific Programming. Search in Google Scholar

[17] Zhai, Y., Yang, X., Peng, Y., et al. (2020). Multiscale Entropy Feature Extraction Method of Running Power Equipment Sound. Entropy, 22(6), 685. Search in Google Scholar

[18] Zhao, H., Liu, B., Wang, L. (2021). Blur Kernel Estimation and Non-Blind Super-Resolution for Power Equipment Infrared Images by Compressed Sensing and Adaptive Regularization. Sensors, 21(14), 4820. Search in Google Scholar

[19] Han, K. B., Jung, J., Kang, B. O. (2021). Real-Time Load Variability Control Using Energy Storage System for Demand-Side Management in South Korea. Energies, 14. Search in Google Scholar

[20] Chapman, A. C., Verbič, G., Hill, D. J. (2016). Algorithmic and Strategic Aspects to Integrating Demand-Side Aggregation and Energy Management Methods. IEEE Transactions on Smart Grid, 7(6), 2748-2760. Search in Google Scholar

[21] Ding, Z., Sarikprueck, P., Lee, W. J. (2016). Medium-Term Operation for an Industrial Customer Considering Demand-Side Management and Risk Management. IEEE Transactions on Industry Applications, 52(2), 1127-1135. Search in Google Scholar

[22] Suleiman, Muhannad, T, et al. (2015). Potential of ground source heat pump systems in cooling-dominated environments: Residential buildings. Geothermics, 57, 104-110. Search in Google Scholar

[23] Dong, M., Nassif, A. B., Li, B. (2018). A Data-Driven Residential Transformer Overloading Risk Assessment Method. IEEE Transactions on Power Delivery, PP(1), 1-1. Search in Google Scholar

[24] Yuan-Qian, Xiao, Xian-Yong, et al. (2016). Premium Power Valuation Method Based on Customer Perception of Utility for High-Technology Manufacturing Customers. IEEE Transactions on Power Delivery, 31(4), 1655-1662. Search in Google Scholar

[25] Bego, Andres, Lin, et al. (2015). Customer-side electricity load management for sustainable manufacturing systems utilizing combined heat and power generation system. International journal of production economics. Search in Google Scholar

[26] Wang, Q., Bu, S., He, Z. (2020). Achieving Predictive and Proactive Maintenance for High-Speed Railway Power Equipment with LSTM-RNN. IEEE Transactions on Industrial Informatics, PP(99), 1-1. Search in Google Scholar

[27] Huang Ke, Li Jiarong, Yang Luyu, et al. (2020). Energy management of grid-connected photovoltaic microgrid system based on KC-LSSVM-MAFSA. Guizhou Power Technology, 023(006), 26-34. Search in Google Scholar

[28] Ahammed, M. T., Khan, I. (2022). Ensuring power quality and demand-side management through IoT-based smart meters in a developing country. Energy, 250. Search in Google Scholar

[29] Jang, M., Jeong, H. C., Kim, T., et al. (2021). Load Profile-Based Residential Customer Segmentation for Analyzing Customer Preferred Time-of-Use (TOU) Tariffs. Energies, 14. Search in Google Scholar

[30] Kaushal, J., Basak, P. (2020). Power quality control through automated demand side management in microgrid equipped with battery energy storage for protection. IET Generation Transmission & Distribution, 14(12). Search in Google Scholar

[31] Ghassemi, A., Scott, M. J. (2020). A Mathematical Approach to Improve Energy-Water Nexus Reliability Using a Novel Multi-Stage Adjustable Fuzzy Robust Approach. Search in Google Scholar

[32] He, L., Zhang, X., Li, Z., et al. (2022). A Chinese Named Entity Recognition Model of Maintenance Records for Power Primary Equipment Based on Progressive Multitype Feature Fusion. Complexity. Search in Google Scholar

[33] Cho, S. G., Chang, S., Sung, D. (2020). Application of Tuned Mass Damper to Mitigation of the Seismic Responses of Electrical Equipment in Nuclear Power Plants. Energies, 13. Search in Google Scholar

[34] Dehbozorgi, M. R., Rastegar, M., Dabbaghjamanesh, M. (2020). Decision tree-based classifiers for root-cause detection of equipment-related distribution power system outages. IET Generation Transmission & Distribution, 14(3). Search in Google Scholar

[35] Wang, Z. (2021). GIS fast-acting live detection of power equipment in complex area based on linear electron accelerator. International Journal of Electrical Engineering Education, 002072092110052. Search in Google Scholar