Journal
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
Volume 4, Issue 4, Pages 555-570Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TETCI.2020.2991728
Keywords
Air conditioner; computational intelligence; coordinated control; energy management; evolutionary computation; HVAC; zone thermal model
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Funding
- Department of Science & Technology (DST), Government of India [DST/INT/UK/P-138/2016]
- National Research Foundation (NRF) Singapore
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Effective design of air-conditioner (AC) management system has the potential to reduce the cost of electricity consumption and help users to participate in demand response (DR) program as interruptible loads. However, optimizing the operation of AC is complex and, as a potential solution, computational intelligence (CI) techniques based model predictive algorithms are being explored in the literature. This article aims to provide an overview of the CI techniques that are established in addressing relevant and timely open problems of AC management for residential buildings. To do so, first, we provide a brief background on different DR mechanisms and AC management systems. Second, a review of recent advances in CI-based model prediction and optimal control techniques of AC systems for DR management is presented. The discussion reveals that the interest in CI techniques with adaptive learning algorithms is increasing due to their ability to adjust in varying conditions. Then, we provide a brief description of a testbed, which is used for testing various newly developed CI-based AC management techniques in a residential setting. Finally, key issues related to the coordination of a large number of AC systems, modeling accuracy, and computational tractability are highlighted along with their challenges and future research directions.
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