Technologies and Practical Implementations of Air-conditioner Based Demand Response

被引：43

作者：

Waseem, Muhammad ^{[1
]}

Lin, Zhenzhi ^{[1
]}

Ding, Yi ^{[1
]}

Wen, Fushuan ^{[1
,2
]}

Liu, Shengyuan ^{[1
]}

Palu, Ivo ^{[2
]}

机构：

[1] Zhejiang Univ, Sch Elect Engn, Hangzhou 310027, Peoples R China

[2] Tallinn Univ Technol, Dept Elect Power Engn & Mechatron, EE-19086 Tallinn, Estonia

来源：

JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY | 2021年 / 9卷 / 06期

基金：

国家重点研发计划; 中国国家自然科学基金;

关键词：

Load management; Power demand; Smart grids; Heat sinks; Air-conditioner (AC); commercial load; cooling demand; demand response (DR); energy consumption; residen-tialload; DIRECT LOAD CONTROL; MODEL-PREDICTIVE CONTROL; THERMOSTATICALLY CONTROLLED LOADS; ARTIFICIAL NEURAL-NETWORK; ENERGY-CONSUMPTION; CONTROL STRATEGY; THERMAL COMFORT; COMMERCIAL BUILDINGS; SIDE MANAGEMENT; INDOOR AIR;

D O I：

10.35833/MPCE.2019.000449

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Nowadays, the most notable uncertainty for an electricity utility lies in the electrical demand of end-users. Demand response (DR) has acquired considerable attention due to uncertain generation outputs from intermittent renewable energy sources and advancements of smart grid technologies. The percentage of the air-conditioner (AC) load over the total load demand in a building is usually very high. Therefore, controlling the power demand of ACs is one of significant measures for implementing DR. In this paper, the increasing development of ACs, and their impacts on power demand are firstly introduced, with an overview of possible DR programs. Then, a comprehensive review and discussion on control techniques and DR programs for ACs to manage electricity utilization in residential and commercial energy sectors are carried out. Next, comparative analysis among various programs and projects utilized in different countries for optimizing electricity consumption by ACs is presented. Finally, the conclusions along with future recommendations and challenges for optimal employment of ACs are presented in the perspective of power systems.

引用

页码：1395 / 1413

页数：19

共 278 条

[1] Artificial neural network (ANN) based model predictive control (MPC) and optimization of HVAC systems: A state of the art review and case study of a residential HVAC system
Afram, Abdul
Janabi-Sharifi, Farrokh
Fung, Alan S.
Raahemifar, Kaamran
[J]. ENERGY AND BUILDINGS, 2017, 141 : 96 - 113
[2] Theory and applications of HVAC control systems - A review of model predictive control (MPC)
Afram, Abdul
Janabi-Sharifi, Farrokh
[J]. BUILDING AND ENVIRONMENT, 2014, 72 : 343 - 355
[3] Conceptual framework for introducing incentive-based demand response programs for retail electricity markets
Alasseri, Rajeev
Rao, T. Joji
Sreekanth, K. J.
[J]. ENERGY STRATEGY REVIEWS, 2018, 19 : 44 - 62
[4] A summary of demand response in electricity markets
Albadi, M. H.
El-Saadany, E. F.
[J]. ELECTRIC POWER SYSTEMS RESEARCH, 2008, 78 (11) : 1989 - 1996
[5] Fuzzy control of HVAC systems optimized by genetic algorithms
Alcalá, R
Benítez, JM
Casillas, J
Cordón, O
Pérez, R
[J]. APPLIED INTELLIGENCE, 2003, 18 (02) : 155 - 177
[6] Combining the Demand Response of direct electric space heating and partial thermal storage using LP optimization
Ali, Mubbashir
Jokisalo, Juha
Siren, Kai
Lehtonen, Matti
[J]. ELECTRIC POWER SYSTEMS RESEARCH, 2014, 106 : 160 - 167
[7] Assessment and simulation of the responsive demand potential in end-user facilities:: Application to a university customer
Alvarez, C
Gabaldón, A
Molina, A
[J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2004, 19 (02) : 1223 - 1231
[8] Amini M.H., 2015, 2015 North American Power Symposium (NAPS), P1, DOI DOI 10.1109/NAPS.2015.7335100
[9] Amini MH, 2013, IEEE POW ENER SOC GE
[10] Optimizing sheddable and shiftable residential electricity consumption by incentivized peak and off-peak credit function approach
Ampimah, Benjamin Chris
Sun, Mei
Han, Dun
Wang, Xueyin
[J]. APPLIED ENERGY, 2018, 210 : 1299 - 1309

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