Urban Regional Building Energy Planning Model under the Guidance of Network Flow Theory

Abstract

The satisfactory construction of regional building energy planning models is a key technology in effective energy allocation. At present, the selection of energy planning is only based on artificial judgment criteria, which leads to a high subjectivity in energy planning. This research innovatively introduces the network flow theory into the urban regional building energy planning model. Combined with the actual characteristics of regional building energy planning, the regional building energy planning model was constructed and the regional energy distribution mode was optimized. The model includes the energy supply layer, energy conversion layer, and energy demand layer. At the same time, the minimum cost and maximum flow problem of the model was solved with the help of the BG iterative algorithm. The model includes the energy supply layer, energy conversion layer, and energy demand layer. We used the BG iterative algorithm to solve the minimum cost and maximum flow problem of the model. The accuracy, accuracy, recall rate, and specificity of the four minimum cost maximum flows tended to be stable with the increase of the number of iterations. After the application of BG iterative algorithm, the cost consumption of each part of the regional building energy planning model in summer will be significantly reduced, and the total consumption cost is 929 million dollars. The research results verify the high applicability of introducing the network flow theory and BG iterative algorithm to construct and solve the regional building energy planning model, which can be applied to the rational allocation of resources in the region.