With the availability of distributed generation (DG), clusters that can autonomously manage their energy profile are emerging in the power grid. These autonomous clusters manage their load profiles by orchestrating th...With the availability of distributed generation (DG), clusters that can autonomously manage their energy profile are emerging in the power grid. These autonomous clusters manage their load profiles by orchestrating their energy resources, such as DG, storage, flexible energy consuming appliances, etc. The performance of such an autonomous cluster depends on the composition of its energy resources. In this paper, we study how the performance of a cluster is affected by adding energy resources such as generating units, storage systems or consuming appliances. First, we characterize the energy resources by parameters that describe their relevant properties. Afterwards, we describe a comprehensive set of performance indicators of a cluster that capture the economical, environmental, and social aspects. We present a model that shows how the energy resources influence the performance indicators of the cluster. We have tested our model with a case study, revealing its effectiveness to evaluate the value added by an energy resource to a cluster.展开更多
文摘With the availability of distributed generation (DG), clusters that can autonomously manage their energy profile are emerging in the power grid. These autonomous clusters manage their load profiles by orchestrating their energy resources, such as DG, storage, flexible energy consuming appliances, etc. The performance of such an autonomous cluster depends on the composition of its energy resources. In this paper, we study how the performance of a cluster is affected by adding energy resources such as generating units, storage systems or consuming appliances. First, we characterize the energy resources by parameters that describe their relevant properties. Afterwards, we describe a comprehensive set of performance indicators of a cluster that capture the economical, environmental, and social aspects. We present a model that shows how the energy resources influence the performance indicators of the cluster. We have tested our model with a case study, revealing its effectiveness to evaluate the value added by an energy resource to a cluster.
