2023年7月10日,

預測之間的能源供應和需求是至關重要的天氣的變化,入住率,人流量,業務工作負載和更多,消費能源需求會大幅波動。這對能源供應商,以確保供應很難滿足需求。例如,如果一個能源提供者產生比需要更多的能量,它浪費時間和金錢。相反,如果不能滿足消費者的需求,客戶會失去信任提供者。這就是為什麼許多能源供應商轉向預測分析從幾十個變量和目標。這些分析,根據2022年的一份報告由Popmodo幫助預測消費和提高公司的機會實現他們的可持續發展目標。如何預測分析在預測中發揮作用預測分析使用數據在過去發生了什麼使受過高等教育的猜測將來可能會發生什麼。更具體地說,通常通過使用統計模型、機器學習算法和其他數據分析技術,預測分析曆史數據中發現模式識別風險和機遇和預測潛在的場景。通過這種方式,預測分析有助於推動戰略決策。能源公司,試圖預測沒有預測分析尤為艱巨由於眾多因素發揮作用,包括能源、天氣條件和不一致的工作負載。 Predictive analytics efforts greatly improve the accuracy of these forecasts, especially when they involve regression analysis. Sometimes, what they think is going on and what’s actually happening are two different things.” Abiodun Iwayemi Engineering Manager, Efficiency Vermont Regression analysis is a mathematical way of sorting factors, such as which variables matter most, which can be ignored, how variables interact with each other and how certain you can be about all the variables. It works by determining the relationship between two or more variables. These relationships are written as a mathematical equation that can help predict the outcome should a variable change. “Regression allows us to gain insights into the structure of that relationship and provides measures of how well the data fits,” says Janice H. Hammond, a professor of manufacturing at Harvard Business School, in a Harvard Business School online article. “Such insights can prove extremely valuable for analyzing historical trends and developing forecasts.” Using Predictive Analytics Solutions to Forecast Energy Needs Energy and utility companies looking to take advantage of predictive analytics can deploy tools from vendors such as Amazon Web Services and IBM . For example, using machine learning, Amazon Forecast is already helping energy providers accurately anticipate and meet the needs of their customers.