An overview of energy management using fuzzy cognitive maps

Abstract

Soft computing, especially fuzzy cognitive maps (FCMs), has become increasingly applicable to energy management and policy-making. In recent decades, there has been a worldwide effort to minimize energy consumption and manage energy flow in private and public buildings. We present a critical overview of today’s applications of FCM-based methods in the energy domain. We analyzed FCM methods related to energy planning, efficiency, sustainability, transition, forecasting, energy policy, and scenario analysis. We highlight FCM's applicability in the energy domain, especially its contribution to the academic and research communities. Specific drawbacks and limitations were identified while using FCM methods on several challenging applications, primarily when learning algorithms are used. A new approach addressing these issues is provided and defined as the advanced fuzzy cognitive maps (AFCM) approach. These drawbacks are considered when providing future research challenges of FCMs for building energy management and efficiency. Finally, research gaps are identified, and we suggest solutions, especially AFCM is advanced fuzzy cognitive maps.