Research on Integrated Methods for Optimal Operational Management of Distributed Energy Systems

近年来，为了减少能源消耗和环境影响，越来越多地安装分布式能源系统。一般来说，商业部门的能源需求的季节性和每小时的变化要大于工业部门。因此，在商业领域中，为了积极推进节能，运营管理是一个非常重要的课题，本研究的目的是开发能源需求预测、能源系统最优运营规划和能源系统最优控制的综合方法，作为积极推进节能的最优运营管理系统，并将其应用于现有的能源系统。主要研究成果如下：1.提出了基于时间序列分析和神经网络的能源需求预测方法。它们已经过修订，以便通过最大限度地减少不必要的费用， ...更多信息 预测值和测量值之间的误差以及预测值的变化。此外，通过将它们与影响能源需求的一些因素（如气温）的预测相结合，提高了它们的精度。2.利用非线性规划方法，提出了一种最优运行规划方法，称为“模态修剪法”。它与基于模型预测控制的最优控制方法分层结合。这些方法使人们能够合理地确定控制变量的设定值和操纵变量的最佳值。3.开发了一个通用的能源系统动态仿真系统。以某空调供热系统为例，建立了该系统的动态仿真模型。在一定的条件下，通过上述最优运行计划和控制的分层组合进行了动态仿真，并验证了仿真结果。少

In recent years, distributed energy systems have been installed increasingly for the purpose of reducing energy consumption and environmental effect. In general, seasonal and hourly variations in energy demands are larger in the commercial sector than in the industrial one. Therefore, operational management is a very important subject to promote energy saving positively in the commercial sector.The objectives of this research are to develop integrated methods for the prediction of energy demands, the optimal operational planning of energy systems, and the optimal control of energy systems as an optimal operational management system to promote energy saving positively, and to apply them to an existing energy system. The following are the main results obtained by the research :1.Prediction methods based on the time series analysis and neural network have been developed to predict energy demands. They have been revised so that they are suitable for operational planning by minimizing not o … More nly the errors between predicted and measured values but also the variations in predicted values. In addition, their accuracy has been improved by combining them with the prediction of some factors, such as air temperature, which affect energy demands.2.An optimal operational planning method has been developed by using a nonlinear programming method which enables one to derive a global quasi-optimal solution, named "Modal Trimming Method." It has been combined hierarchically with an optimal control method based on the model predictive control. These methods enable one to rationally determine the set values of controlled variables and the optimal values of manipulating variables.3.A general-purpose system for dynamic simulation of energy systems has been developed. An existing heat supply system for air conditioning has been studied as an example, and its dynamic simulation model has been created. The dynamic simulation has been conducted under certain conditions by the aforementioned hierarchical combination of the optimal operational planning and control, and simulation results have been validated. Less