考虑单个建筑盈利需求的协作式建筑群随机规划决策模型

A Stochastic Decision Model for the Collaborative Building Cluster Considering the Benefit Requirements of Buildings

摘要: 建筑群运营是建筑节能减排的有效方式。然而，现有研究只强调建筑群整体利益的最优，忽略群内单个建筑的盈利需求。这将阻碍建筑群的运营，尤其在建筑属于不同实体所有时，因为建筑所有者是追逐利益的。对此，研究考虑单个建筑的盈利需求，即建筑所有者要求建筑群运营为自己节约至少一定的建筑运营成本，否则它们将退出建筑群。此外，研究也考虑了建筑能源需求的不确定性。针对能源需求不确定的，考虑单个建筑盈利需求的建筑群协作运营优化问题，研究采用基于场景的随机规划构建随机混合整数规划模型，将单个建筑的盈利需求表示为约束。算例实验表明，与不考虑单个建筑盈利需求的建筑群运营相比，考虑这些盈利需求的建筑群运营能为建筑所有者提供它们所要求的运营成本节约量，例如15%的成本节约，同时保障建筑群的总运营成本不增加，仍然节约近31%的总运营成本。

Abstract: The building cluster’s operation is an important contributor to better energy efficiency and lower energy cost. Yet, the existing research only emphasizes the optimization of the entire building cluster’s collective benefit and neglects the benefit requirements of buildings in the cluster. This will curb the operation of the building cluster when buildings belong to different owners as such owners are profit-seeking. To handle this problem, this paper considers the benefit requirements from buildings, that is, building owners require that the operation of the building cluster provide at least a certain amount of operational cost savings. Otherwise, they would refuse to join in the operation of the building cluster. Additionally, this paper also takes into account the uncertainty in building energy demands. To study the operation of the building cluster with random energy loads considering the benefit requirement from buildings, this research adopts scenario-based stochastic programming to formulate a stochastic mixed-integer programming model. In this model, buildings’ benefit requirements are expressed as constraints. Numerical experimental results demonstrate that, compared to the collaborative operation of the building cluster without buildings’ benefit requirements, the one considering such requirements can provide building owners with the operational cost saves required by them, such as 15% of cost savings, and does not increase the total operational cost of the building cluster, which is still about 31% savings of cost.