Future distributed generation: An operational multi-objective optimization model for integrated small scale urban electrical, thermal and gas grids. (1st July 2017) - Lo Cascio, Ermanno; Borelli, Davide; Devia, Francesco; Schenone, Corrado
Highlights: Multi-objective optimization model for retrofitted and integrated natural gas pressure regulation stations. Comparison of different incentive mechanisms for recovered energy based on the characteristics of preheating process. Control strategies comparison: performances achieved with optimal control vs. ones obtained by thermal load tracking. Abstract: A multi-objective optimization model for urban integrated electrical, thermal and gas grids is presented. The main system consists of a retrofitted natural gas pressure regulation station where a turbo-expander allows to recover energy from the process. Here, the natural gas must be preheated in order to avoid methane hydrates. The preheating phase could be based on fossil fuels, renewable or on a thermal mix. Depending on the system configuration, the proposed optimization model enables a proper differentiation based on how the natural gas preheating process is expected to be accomplished. This differentiation is addressed by weighting the electricity produced by the turbo-expander and linking it to proper remuneration tariffs. The effectiveness of the model has been tested on an existing plant located in the city of Genoa. Here, the thermal energy is provided by means of two redundant gas-fired boilers and a cogeneration unit. Furthermore, the whole system is thermally integrated with a district heating network. Numerical simulation results, obtained with the commercial proprietary software Honeywell UniSim Design Suite, have been compared with the optimal solutions achieved. The effectiveness of the model, in terms of economic and environmental performances, is finally quantified. For specific conditions, the model allows achieving an operational costs reduction of about 17% with the respect to thermal-load-tracking control logic.