This work aims at the setup of an experimental district for distributed smart polygeneration. The district is controlled and its behaviour is optimized by a software tool for supply and demand matching of electrical and thermal energy in an urban district. In particular, the tool has been developed for ENERDD, the experimental district that TPG is going to build in Savona, Italy. E-NERDD is an acronym for Energy and Efficiency Research Demonstration District. The district will be used within the project to demonstrate how different software tools and algorithms perform in thermodynamic, economic and environmental terms. The software tool originally developed and implemented in this work, called ENERDD Control System, is targeted on enabling the operation of the hardware, when connected in a district mode. Supply and demand are matched to reach a thermo-economic optimum. An optimization algorithm is organized into two different levels of optimization: a first level that solves a constrained minimization problem in planning power supply for each generator on the basis of day-before forecasting; and a second level that distributes among the different machines the gap between planned and real-time demand. The algorithm developed is demonstrated in three test cases in order to test it in different working conditions.
Smart Polygeneration Grid: Experimental Setup and Control System
CARATOZZOLO, FRANCESCO;FERRARI, MARIO LUIGI;TRAVERSO, ALBERTO;MASSARDO, ARISTIDE
2012-01-01
Abstract
This work aims at the setup of an experimental district for distributed smart polygeneration. The district is controlled and its behaviour is optimized by a software tool for supply and demand matching of electrical and thermal energy in an urban district. In particular, the tool has been developed for ENERDD, the experimental district that TPG is going to build in Savona, Italy. E-NERDD is an acronym for Energy and Efficiency Research Demonstration District. The district will be used within the project to demonstrate how different software tools and algorithms perform in thermodynamic, economic and environmental terms. The software tool originally developed and implemented in this work, called ENERDD Control System, is targeted on enabling the operation of the hardware, when connected in a district mode. Supply and demand are matched to reach a thermo-economic optimum. An optimization algorithm is organized into two different levels of optimization: a first level that solves a constrained minimization problem in planning power supply for each generator on the basis of day-before forecasting; and a second level that distributes among the different machines the gap between planned and real-time demand. The algorithm developed is demonstrated in three test cases in order to test it in different working conditions.
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