Asymmetric Loss Functions for Contract Capacity Optimization

Jun-Lin Lin, Yiqing Zhang, Kunhuang Zhu, Binbin Chen and Feng Zhang
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Jun-Lin Lin: Department of Information Management, Yuan Ze University, Taoyuan 32003, Taiwan
Yiqing Zhang: Department of Information Management, Yuan Ze University, Taoyuan 32003, Taiwan
Kunhuang Zhu: Department of Information Management, Yuan Ze University, Taoyuan 32003, Taiwan
Binbin Chen: Department of Information Management, Yuan Ze University, Taoyuan 32003, Taiwan
Feng Zhang: Department of Information Management, Yuan Ze University, Taoyuan 32003, Taiwan

Energies, 2020, vol. 13, issue 12, 1-13

Abstract: For high-voltage and extra-high-voltage consumers, the electricity cost depends not only on the power consumed but also on the contract capacity. For the same amount of power consumed, the smaller the difference between the contract capacity and the power consumed, the smaller the electricity cost. Thus, predicting the future power demand for setting the contract capacity is of great economic interest. In the literature, most works predict the future power demand based on a symmetric loss function, such as mean squared error. However, the electricity pricing structure is asymmetric to the under- and overestimation of the actual power demand. In this work, we proposed several loss functions derived from the asymmetric electricity pricing structure. We experimented with the Long Short-Term Memory neural network with these loss functions using a real dataset from a large manufacturing company in the electronics industry in Taiwan. The results show that the proposed asymmetric loss functions outperform the commonly used symmetric loss function, with a saving on the electricity cost ranging from 0.88% to 2.42%.

Keywords: contract capacity; asymmetric loss functions; long short-term memory (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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