The Optimal Strategy for Power Suppression Policy: An Example for Daily Reduction of 2-Hour Electricity Consumption

計畫性減少用電措施之最佳策略：以日減二時型為例

10.29416/JMS.202210_29(4).0003

黃怡詔(Yi-Chao Huang)；黃鐘慶(Jong-Ching Hwang)；葉嘉育(Chia-Yu Yeh)

Energy policy ； Power Suppression ； Suppression Contract Capacity ； Integer programming ； 能源政策 ； 抑低用電 ； 抑低契約容量 ； 整數規劃

管理與系統

29卷4期（2022 / 10 / 01）

471 - 493

英文

The power company has developed the power suppression policies to guide industrial users to transfer their electricity consumption from peak time to off-peak time to stabilize the power supply. To coordinate with the production processes adjusted by the power company's program when users participate in the measure of reduction in electricity consumption, this study established an integer programming model, calculated the Customer Baseline Load, Average Suppression Demand and Realistic Suppression Capacity with Excel, and used Lingo 12.0 to solve the integer programming model to calculate the maximum electricity charge saved, and obtain the best contract capacity and best suppression contract capacity. The aim of this paper is to provide the optimal strategy for power suppression policy. After constructing the power suppression model, we made use of electricity data of one factory in Southern Taiwan to verify the integer programming model. The empirical results show that this model can effectively save the electricity charge about 8.95%. Hence, this paper developed a good power-saving model which can assist enterprises to save energy cost, and made it easy for power companies to achieve power-saving policies.

隨著國內產業發展快速，對於電力之需求也逐漸增加，因此電力公司發展「計畫性減少用電措施」和「臨時性減少用電措施」，希望能在尖峰用電期間引導用戶移轉用電至離峰時間以穩定供電。配合電力公司減少用電方案，用電戶將原下午一點到三點的生產量往後延以配合日減二時減電方案，本研究以減電方案的規則建立整數規劃模型，接續根據工廠歷史資料計算出工廠調整工作時間後的基準用電容量、抑低用電平均需量和實際抑低容量，再使用Lingo求解本研究發展的整數規劃模型，即可計算出工廠最大節省電費並得到工廠與台電簽訂契約容量和抑低契約容量的最佳值。本研究最後以高壓需量用戶某一年度用電需量作為實證資料，在參與日減二時型減少用電計畫後，經整數規劃模型計算後，除可得到最佳契約容量與最佳抑低契約容量的數值外，並計算出參加減電計畫可節省約8.95%的電費，實證結果證明此模型能有效節省電費，並獲得工廠與台電簽訂契約容量與抑低契約容量的最佳值。

1. Chan, P.,Hui, C. W.,Li, W.,Sakamoto, H.,Hirata, K.,Li, P.(2006).Long-Term Electricity Contract Optimization with Demand Uncertainties.Energy,31,2469-2485.
2. Chang, Y. G.,Ren, H. Z.,Wang, S. J.(2015).Modelling and Optimizing an Open-Pit Truck Scheduling Problem.Discrete Dynamics in Nature and Society,2015,Article ID 745378.
3. Fernández, M. A.,Zorita, A. L.,García-Escudero, L. A.,Duque, O.,Moríñigo, D.,Riesco, M.,Muñoz, M.(2013).Cost Optimization of Electrical Contracted Capacity for Large Customers.Electrical Power and Energy Systems,46,123-131.
4. Filippi, C.,Mansini, R.,Stevanato, E.(2017).Mixed Integer Linear Programming Models for Optimal Crop Selection.Computers and Operations Research,81,26-39.
5. Fischetti, M.,Monaci, M.,Salvagnin, D.(2016).Mixed-Integer Linear Programming Heuristics for the Prepack Optimization Problem.Discrete Optimization,22,195-205.
6. Guo, H. D.,Deng, S. X.,Yang, J. B.,Liu, J. W.,Nie, C. D.(2020).Analysis and Prediction of Industrial Energy Conservation in Underdeveloped Regions of China Using a Data Pre-Processing Grey Model.Energy Policy,139
7. Jahromi, A. E.,Yazdeli, R. I.(2015).A Mixed Integer-Programming Model for Periodic Routing of Special Vessels in Offshore Oil Industry.International Journal of Industrial Engineering: Theory, Applications and Practice,22(5),524-528.
8. Kim, J. S.,Edgar, T. F.(2014).Optimal Scheduling of Combined Heat and Power Plants Using Mixed-Integer Nonlinear Programming.Energy,77,675-690.
9. Kler, A. M.,Potanina, Y. M.(2017).An Approach to Optimization of the Choice of Boiler Steel Grades as to a Mixed-integer Programming Problem.Energy,127,128-135.
10. Ko, R.,Jo, H. C.,Joo, S. K.(2019).Energy Storage System Capacity Sizing Method for Peak Demand Reduction in Urban Railway System with Photovoltaic Generation.Journal of Electrical Engineering & Technology,14,1771-1775.
11. Lee, H. C.,Chang, C. T.(2018).Comparative Analysis of MCDM Methods for Ranking Renewable Energy Sources in Taiwan.Renewable and Sustainable Energy Reviews,92,883-896.
12. Lee, T. Y.,Chen, C. L.(2007).Iteration Particle Swarm Optimization for Contract Capacities Selection of Time-of-Use Rates Industrial Customers.Energy Conversion and Management,48,1120-1131.
13. Lima, D. A.,Céspedes G., A. M.,Telles, É.,Bittencourt, E. M. M.(2018).Peak Demand Contract for Big Consumers Computed Based on the Combination of a Statistical Model and a Mixed Integer Linear Programming Stochastic Optimization Model.Electric Power Systems Research,154,122-129.
14. Lu, Y. H.,Wang, S. G.,Sun, Y. J.,Yan, C. C.(2015).Optimal Scheduling of Buildings with Energy Generation and Thermal Energy Storage Under Dynamic Electricity Pricing Using Mixed-Integer Nonlinear Programming.Applied Energy,147,49-58.
15. Maknoon, M. Y.,Soumis, F.,Baptiste, P.(2017).An Integer Programming Approach to Scheduling the Transshipment of Products at Cross-Docks in Less-than-Truckload Industries.Computers and Operations Research,82,167-179.
16. Melo, M.,Bueno, L.,Campello, S.(2012).Industry Energy Efficiency Analysis in Northeast Brazil: Proposal of Methodology and Case Studies.International Journal of Industrial Engineering: Theory, Applications and Practice,19(11),428-443.
17. Mulder, G.,Ridder, F. D.,Six, D.(2010).Electricity Storage for Grid-Connected Household Dwellings with PV Panels.Solar Energy,84,1284-1293.
18. Nguyen, M. Y.,Choi, N. H.,Yoon, Y. T.(2009).DP Formulation of Microgrid Operation with Heat and Electricity Constraints.Journal of Power Electronics,9(6),919-928.
19. Ogunjuyigbe, A. S. O.,Ayodele, T. R.,Oladimeji, O. E.(2016).Management of Loads in Residential Buildings Installed with PV System Under Intermittent Solar Irradiation Using Mixed Integer Linear Programming.Energy and Buildings,130,253-271.
20. Omu, A.,Hsieh, S.,Orehounig, K.(2016).Mixed Integer Linear Programming for the Design of Solar Thermal Energy Systems with Short-Term Storage.Applied Energy,180,313-326.
21. Onifade, T. T.(2016).Hybrid Renewable Energy Support Policy in the Power Sector: The Contracts for Difference and Capacity Market Case Study.Energy Policy,95,390-401.
22. Saidur, R.,Islam, M. R.,Rahim, N. A.,Solangi, K. H.(2010).A Review on Global Wind Energy Policy.Renewable and Sustainable Energy Reviews,14(7),1744-1762.
23. Stoyan, S. J.,Dessouky, M. M.(2012).A Stochastic Mixed-Integer Programming Approach to the Energy-Technology Management Problem.Computers & Industrial Engineering,63,594-606.
24. Tang, L. X.,Liu, J. Y.,Yang, F.,Li, F.,Li, K.(2015).Modeling and Solution for the Ship Stowage Planning Problem of Coils in the Steel Industry.Naval Research Logistics,62(7),564-581.
25. Tasy, M. T.,Lin, W. M.,Lee, J. L.(2001).Optimal Contract Decision of Industrial Customers.Electrical Power and Energy Systems,23,795-803.
26. Torrent-Fontbona, F.,López, B.(2015).Power Re-Allocation for Reducing Contracted Electric Power Costs.Energy and Buildings,89,112-122.
27. Vetterli, J.,Benz, M.(2012).Cost-Optimal Design of an Ice-storage Cooling System Using MixedInteger Linear Programming Techniques Under Various Electricity Tariff Schemes.Energy and Buildings,49,226-234.
28. Wang, Y.,Zhang, N.,Zhuo, Z. Y.,Kang, C. Q.,Kirschen, D.(2018).Mixed-Integer Linear Programming-Based Optimal Configuration Planning for Energy Hub: Starting from Scratch.Applied Energy,210,1141-1150.
29. Yang, H. T.,Peng, P. C.(2012).Improved Taguchi Method Based Contract Capacity Optimization for Industrial Consumer with Self-Owned Generating Units.Energy Conversion and Management,53,282-290.
30. Yin, J. T.,Yang, L. X.,Tang, T.,Gao, Z. Y.,Ran, B.(2017).Dynamic Passenger Demand Oriented Metro Train Scheduling with Energy-Efficiency and Waiting Time Minimization: Mixed-Integer Linear Programming Approaches.Transportation Research Part B,97,182-213.
31. Zuo, L. L.,Zhang, X. R.,Wu, C. C.,Yu, Y.(2016).Unit Commitment for a Compressor Station by Mixed Integer Linear Programming.Journal of Natural Gas Science and Engineering,30,338-342.