Abstract:

Calculating the cost of distributed combined cooling, heating and power system (DCCHP), the data of source and load usually use the predicted values at present. However, the limitation of load forecasting method and renewable energy forecasting method can cause the data prediction error and affect the accuracy of the combined system cost calculation further. In this paper, a model of DCCHP which has complete components is established. Sampling the data of load and renewable energy outputs to simulate the predicted errors of the data, the typical scenarios can be built by the LHS scenarios reduction process. For each of typical scenarios, the cost is calculated and weighted by its occurrence probability to generate the cost considering the prediction error. Finally, simulation of a typical DCCHP and sensitivity analysis certify that for the predicted values of different accuracy the method proposed by this paper can calculate the system cost accurately and provide effective reference for practical system planning and design.

Key words:

DCCHP, distributed energy, cost, prediction error, latin hypercube sampling