Smart community energy optimal scheduling method and system

Abstract

The invention discloses a smart community energy optimal scheduling method and system. The method comprises the following steps: acquiring resource configuration parameters, load demand and electricity price information of a demand side of a smart community; establishing an aggregated air conditioner approximate load model; evaluating the response potential of an aggregated air conditioner and therebound load after the response of the air conditioner under a temperature adjustment control mode; establishing a multi-time-scale energy optimal scheduling model; and converting a random variable in the multi-time-scale energy optimal scheduling model into a determined equivalence class, and solving the multi-time-scale energy optimal scheduling model to obtain an optimal scheduling result of each resource. The load of the air conditioner is adjusted through temperature adjustment control, and the influence on the comfort degree of users is reduced. A multi-time-scale energy optimal scheduling model is established, the output of certain resources and the output of uncertain resources can be coordinated, the power shortage of the community is reduced, and the economical efficiency of community operation is improved.

Description

technical field [0001] The invention belongs to the technical field of power demand side management, and relates to a smart community energy optimization scheduling method and system, in particular to a smart community energy optimization scheduling method and system considering the uncertainty of air-conditioning response. Background technique [0002] With the emergence of extreme weather such as global warming, building energy consumption continues to increase, and the power consumption per unit area of ​​hotels / hotels is 10 to 15 times that of ordinary houses. On the other hand, from an economic point of view, hotel management has entered the era of meager profits, which requires hotel managers to pay attention to energy conservation. According to statistics, the average power consumption of hotel buildings accounts for about 51.5% of the total energy consumption, and its average energy consumption is close to 169kWh / (m 2 · a) At the same time, the electricity cost of t...

AI Technical Summary

Problems solved by technology

However, there are still the following deficiencies in the current research: 1) most of them consider the decentralized individual air-conditioning loads to participate in energy scheduling, and lack the aggregation of air-conditioning loads; 3) There is a lack of consideration of response uncertainty in the process of air-conditioning load participation in dispatching

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