Electricity Management Policy Applying Data Science and Machine Learning Techniques to Improve Electricity Costs

This paper studies the actual electricity case of a national university in northern Taiwan, pointing out that many schools will face certain asymmetrical information and practical problems development power systems, such as energy-savings carbon-reduction policies, collecting fees each division, reducing loss outages, expanding system capacity, maintaining distribution equipment. These are closely related to costs, which include general fees, unexpected losses caused by purchases replacement equipment, maintenance proposes corresponding improvement plans for above-mentioned assists school managers using symmetrical formulate best strategies improve costs.