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Typical example of this load type is the chiller load, AHU load, water pump load, battery charging station, etc. Certain amount of energy is stored in such type of devices and is generally switched on intermediately.
It is found that the chiller's COP can be maximized by adjusting the set point based on any given chiller load and wet-bulb temperature of the outdoor air.
The sizing of the thermal storage system as a function of demand load profile and on the basis of operating strategies can effectually achieve reduction in chiller load during electrical peak periods.
For a typical floor, chiller load due to heat gain through the building envelope varied from 1.0 kW h/m2 in Kunming to 23.5 kW h/m2 in Beijing, and the heating load ranged from 2.7 kW h/m2 in Hong Kong to 124.3 kW h/m2 in Harbin.
Similar(56)
Recently, optimization methods for optimal chiller loading have been proposed.
In terms of optimization, various metaheuristics have been proposed to the optimal chiller loading problem.
This study employs differential evolution algorithm to solve the optimal chiller loading problem for reducing energy consumption.
This paper employs a recent swarm intelligence technique to solve optimal chiller loading (OCL) problem, namely differential search (DS) algorithm.
This study proposes a new improved firefly algorithm (IFA) based on Gaussian distribution function to the optimal chiller loading design.
This paper proposes a new CSA approach using differential operator (DCSA) to solve the optimal chiller loading design problem.
The results of optimal chiller loading are analyzed on three case studies taken from literature to confirm the validity of the proposed algorithm.
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