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An efficient Energy Management System for long term planning and real time scheduling of flexible polygeneration systems

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  • La Fata, Alice
  • Brignone, Massimo
  • Procopio, Renato
  • Bracco, Stefano
  • Delfino, Federico
  • Barilli, Riccardo
  • Ravasi, Martina
  • Zanellini, Fabio

Abstract

The ever-increasing participation of new energy sources, storage systems and controllable loads to electricity markets has introduced more complexity in the operation of power plants, microgrids (MGs) and networks. To face these issues, it is often necessary to design Distributed Energy Systems to optimize the power exchange. Usually, MG operation is managed by an Energy Management System (EMS) dealing with large amounts of parameters to be taken into account and that may drive to problems difficult to be faced and requiring long computational timings. In this direction, this paper describes the Mixed Integer Linear Programming MATLAB Based Energy Management System (MB-EMS) developed at the University of Genoa, aimed at optimizing the operating costs of a generic polygeneration system, considering different electrical and thermal production units, energy storage systems, non-programmable loads and flexible loads. Many important technical details are accounted: the duration and costs related to maintenance interventions and CO2 emissions costs are considered for all production units as well as constraints and incentives related to the High-Efficiency Cogeneration systems. Constraints related to the minimum and maximum State-Of-Charge of energy storage systems, plus their deterioration, with the consequent optimization of their utilization, are also modelled. Specific test cases for all functionalities are presented. Moreover, a test related to a real MG performed over a time horizon of one year with a time step of 1 h is performed and solved in a short computational time. The linearization of constraints reduces the computational effort, avoiding the need of clustering or averaging parameters for similar production units. Consequently, calculations are rapidly performed, also when dealing with long term planning problems (a realistic test case with time horizon of one year and time step of 15 min can be simulated in some seconds). In this sense, the developed tool can be used both in real time operation and in long term planning problems.

Suggested Citation

  • La Fata, Alice & Brignone, Massimo & Procopio, Renato & Bracco, Stefano & Delfino, Federico & Barilli, Riccardo & Ravasi, Martina & Zanellini, Fabio, 2022. "An efficient Energy Management System for long term planning and real time scheduling of flexible polygeneration systems," Renewable Energy, Elsevier, vol. 200(C), pages 1180-1201.
    • Handle: RePEc:eee:renene:v:200:y:2022:i:c:p:1180-1201
    DOI: 10.1016/j.renene.2022.10.030
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    1. La Fata, Alice & Brignone, Massimo & Procopio, Renato & Bracco, Stefano & Delfino, Federico & Barbero, Giulia & Barilli, Riccardo, 2024. "An energy management system to schedule the optimal participation to electricity markets and a statistical analysis of the bidding strategies over long time horizons," Renewable Energy, Elsevier, vol. 228(C).
    2. Pang, Xinfu & Wang, Yibao & Yu, Yang & Liu, Wei, 2024. "Optimal scheduling of a cogeneration system via Q-learning-based memetic algorithm considering demand-side response," Energy, Elsevier, vol. 300(C).

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