AS_03_2020

tecnica 93 Automazione e Strumentazione Aprile 2020 CONTROLLO tegy is based on the usage of PID controllers . In particular, a decentralized control structure envisages the control of the room temperature through a PID control which manipulates the fan coil devices command, while another PID control manipu- lates the air recirculation fan speed in order to control the room CO2 levels. Moreover, a hysteresis-based conversion is applied on the temperature loop so to adapt the continuous output of the temperature PID with the discrete commands (0, 1, 2, 3) accep- ted by the fan coil devices. In the following sub-sections, three advanced control techniques are presented. 4.1 Fan coil command modularization The present control strategy computes a correction signal that is added to the temperature PID control output before reaching the hysteresis-based conversion block which precedes the fan coil devices. Such a correction signal is presented in the fol- lowing equation: In such an equation, u FC (t) is the temperature PID output, #PPL is the number of people occupying the room, PPL MAX is a tuning parameter and e T(t) is the temperature error. By this formulation, the corrective action assigned is equal to the PID output itself – thus deactivating the fan coil devices – only if a number of people equal or greater to PPL MAX is measured and the room temperature is equal or greater than its set-point. On the other hand, the corrective action is equal to zero if no people are occupying the room or if the room temperature error is equal or greater than two degrees. In the other cases, the tempe- rature PID output will be reduced according to the presented formula. The presented control strategy has been tested on a multi-room model obtained as extension of the presented vali- dated single room mo- del to validate its per- formances over a three months time window. Compared to the base- line decentralized PID control structure, the rooms average tempe- rature has been reduced of 0.5 °C, the overhea- ting frequency reduced by 12%, the overhea- ting average temperature reduced by 0.13 °C and the overall thermal energy reduced of 1176 kWh. 4.2 Temperature set-point manipulation This second control strategy manipulates the room temperature set-point based on the people occupying the room. This mani- pulation, resulting in a temporary thermal comfort reduction, is imposed through the following equation: In such an equation, SpT is the room temperature set-point, #PPL is the number of people occupying the room and PPL min is a tuning parameter which defines the minimum number of people over which the temperature set-point variation is nul- lified. The maximum temperature set-point reduction is two degrees and corresponds to a completely empty room. The multi-room test of this control strategy presented an overall thermal energy reduction of 872 kWh over a three month time window. A further simulation – for which a time window of one week is presented in υ figure 3 – has been performed over the multi-room model in which both the first and the second advanced control techniques are applied at the same time. This simulation shows how the two control strategies present a positive synergy, which is able to signi- ficantly reduce the overall consumption while increasing the people thermal comfort. In fact, compared to the baseline decentralized PID control structure, the rooms average tempe- rature has been reduced of 1.2 °C, the overheating frequency Figure 3 - Advanced control strategies 1 and 2 performance