Technologies and Practical Implementations of Air-conditioner Based Demand Response

Abstract

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.

Load-Altering Attacks Against Power Grids Under COVID-19 Low-Inertia Conditions

“…The air-conditioning (AC) industry market reached a 100 billion USD annual revenue in 2021 [25], primarily due to a steady raising in electricity consumption and peak demand for electricity. For example, in India, the usage of electricity attributed to ACs will reach 239 TWh/year by 2030 which will require an additional 500 MW generation capacity [26].…”

The progress, impact analysis, challenges and new perceptions for electric power and energy sectors in the light of the COVID-19 pandemic

“…Some emergent flexible resources, such as energy storage and demand-side management (DSM), are emphasized and discussed in [61] . The power balance is also challenged by uncertainties evolving from both the generation and demand side [62] . The balance of power system can be provided through a multistage generation scheduling procedure, including day-ahead scheduling, multi-day ahead planning, real-time dispatch and intra-day rolling dispatch.…”

Artificial Intelligence Based Air Conditioner Energy Saving Using a Novel Preference Map

“…Our AI solution works on 37,748 ACs and has achieved a median energy saving of 57.38% and maximum energy saving of up to 90% (when using Top-1 recommendation). A survey of AC control methods to reduce energy consumption for Energy DR Applications are available in [17]. A review of data driven computational Intelligence techniques for energy management of ACs and Energy DR is provided in [18].…”