Optimization Control of Ice Storage Air-Conditioning System

2013 ◽  
Vol 655-657 ◽  
pp. 1492-1495
Author(s):  
Ting Wu ◽  
Gang Wu ◽  
Zhe Jing Bao ◽  
Wen Jun Yan
Keyword(s):  
Control Strategy ◽  
Air Conditioning ◽  
Particle Swarm Optimization Algorithm ◽  
Ice Storage ◽  
Optimal Control Strategy ◽  
Air Conditioning System ◽  
Control Scheme ◽  
Optimization Control ◽  
Building Cooling ◽  
Operation Cost

Ice storage air-conditioning system can bring benefits to power supplier and consumers for its advantage of shifting power consumption at peak hours during day to the off-peak hours at night. In this paper, we adopted an improved particle swarm optimization algorithm to develop an optimal control strategy for ice storage air-conditioning system with the aim of minimizing operation cost subject to various operational constrains. Comparing with the usual chiller-priority and ice-storage-priority control strategy, the proposed control scheme can not only meet the building cooling load but also achieve the minimum operation cost.

Optimal Control Strategy for Ice-Storage System Based on Hourly Dynamic Load Simulation

2013 ◽  
Vol 671-674 ◽  
pp. 2515-2519
Author(s):  
Xue Mei Wang ◽  
Zhen Hai Wang ◽  
Xing Long Wu
Keyword(s):  
Optimal Control ◽  
Air Conditioning ◽  
Control Strategies ◽  
Storage System ◽  
Simulation Software ◽  
Ice Storage ◽  
Optimal Control Strategy ◽  
Air Conditioning System ◽  
Energy Plus ◽  
Load Simulation

This project aims to study the optimal control model of the ice-storage system which is theoretically close to the optimal control and also applicable to actual engineering. Using Energy Plus, the energy consumption simulation software, and the simple solution method of optimal control, researchers can analyze and compare the annual operation costs of the ice-storage air-conditioning system of a project in Beijing under different control strategies. Researchers obtained the power rates of the air-conditioning system in the office building under the conditions of chiller-priority and optimal contro1 throughout the cooling season. Through analysis and comparison, they find that after the implementation of optimal control, the annually saved power bills mainly result from non-design conditions, especially in the transitional seasons.

scholarly journals Optimization of floor radiant air conditioning heating system in building heating design

2020 ◽  
Author(s):  
Hongpu Liang
Keyword(s):  
Control Strategy ◽  
Air Conditioning ◽  
Operation Time ◽  
Heating System ◽  
Basic Structure ◽  
Living Environment ◽  
Moderate Degree ◽  
Optimal Control Strategy ◽  
Air Conditioning System ◽  
Qinghai Province

Abstract For areas with hot summer and cold winter, air conditioning is an essential tool to improve the living environment, but the traditional air conditioning needs to consume a lot of energy in cooling and heating, the fan operation noise is large and the sense of blowing will be uncomfortable. This paper briefly introduced the basic structure of a ground-source heat pump-floor radiant air conditioning system and the control strategy which was used for regulating the operation of the air conditioning system. Then, in order to ensure the appropriate comfort and reduce energy consumption, the control strategy was optimized. An experimental room in Xining, Qinghai province, was taken as an example for analysis. The results showed that the thermal comfort under the control strategy proposed in this study was more stable at the moderate degree and the temperature was slightly higher under the traditional control strategy, although the indoor temperature fluctuation under the optimal control strategy was large and the temperature was slightly lower than that under the traditional control strategy; under the control strategy proposed in this study, the air conditioning system had shorter operation time and less power consumption.

A multi-objective operation strategy optimization for ice storage systems based on decentralized control structure

2020 ◽  
Vol 42 (1) ◽  
pp. 62-81
Author(s):  
Yanhuan Ren ◽  
Junqi Yu ◽  
Anjun Zhao ◽  
Wenqiang Jing ◽  
Tong Ran ◽  
...  
Keyword(s):  
Energy Saving ◽  
Decentralized Control ◽  
Optimization Algorithm ◽  
Control Strategy ◽  
Load Distribution ◽  
Air Conditioning ◽  
Control Structure ◽  
Ice Storage ◽  
Swarm Optimization ◽  
Multi Objective

Improving the operational efficiency of chillers and science-based planning the cooling load distribution between the chillers and ice tank are core issues to achieve low-cost and energy-saving operations of ice storage air-conditioning systems. In view of the problems existing in centralized control architecture applied in heating, ventilation, and air conditioning, a distributed multi-objective particle swarm optimization improved by differential evolution algorithm based on a decentralized control structure was proposed. The energy consumption, operating cost, and energy loss were taken as the objectives to solve the chiller’s hourly partial load ratio and the cooling ratio of ice tank. A large-scale shopping mall in Xi’an was used as a case study. The results show that the proposed algorithm was efficient and provided significantly higher energy-savings than the traditional control strategy and particle swarm optimization algorithm, which has the advantages of good convergence, high stability, strong robustness, and high accuracy. Practical application: The end equipment of the electromechanical system is the basic component through the building operation. Based on this characteristic, taken electromechanical equipment as the computing unit, this paper proposes a distributed multi-objective optimization control strategy. In order to fully explore the economic and energy-saving effect of ice storage system, the optimization algorithm solves the chillers operation status and the load distribution. The improved optimization algorithm ensures the diversity of particles, gains fast optimization speed and higher accuracy, and also provides a better economic and energy-saving operation strategy for ice storage air-conditioning projects.

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