Phase Change Materials (PCMs) incorporated in refrigerators can be used to shift their energy consumption from peak periods, when the electric network energy demand is the highest, to off-peak periods. While PCMs can flatten the energy demand curve, they can achieve economic savings if Time-of-Use (TOU) electricity tariffs are applied. However, the hourly carbon emission factor is not commonly linked to the hourly tariff, and the final CO2 emitted due to the operations of the refrigerator would not be fully optimized. In this work, a method based on the Simulated Annealing optimization technique was proposed to identify the optimal working schedule of a cabinet refrigerator incorporating a PCM to reduce its indirect carbon emissions. Data from countries with different representative carbon intensity profiles were used. The normalized standard deviation and normalized range are the best statistical indexes to predict carbon emission reduction in the proposed solution. These parameters proved that countries with a higher hourly carbon intensity variation (Uruguay, France, Denmark, and Germany) benefit from the application of the algorithm. Cost and carbon emission reduction cannot be maximized simultaneously, and a trade-off is required.
Scheduling optimization of a cabinet refrigerator incorporating a phase change material to reduce its indirect environmental impact
Maiorino A.
Conceptualization
;Del Duca M. G.Formal Analysis
;Aprea C.Supervision
2021-01-01
Abstract
Phase Change Materials (PCMs) incorporated in refrigerators can be used to shift their energy consumption from peak periods, when the electric network energy demand is the highest, to off-peak periods. While PCMs can flatten the energy demand curve, they can achieve economic savings if Time-of-Use (TOU) electricity tariffs are applied. However, the hourly carbon emission factor is not commonly linked to the hourly tariff, and the final CO2 emitted due to the operations of the refrigerator would not be fully optimized. In this work, a method based on the Simulated Annealing optimization technique was proposed to identify the optimal working schedule of a cabinet refrigerator incorporating a PCM to reduce its indirect carbon emissions. Data from countries with different representative carbon intensity profiles were used. The normalized standard deviation and normalized range are the best statistical indexes to predict carbon emission reduction in the proposed solution. These parameters proved that countries with a higher hourly carbon intensity variation (Uruguay, France, Denmark, and Germany) benefit from the application of the algorithm. Cost and carbon emission reduction cannot be maximized simultaneously, and a trade-off is required.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.