Assessing the performance of residential energy management control algorithms: multi-criteria decision making using the analytical hierarchy process

Abstract

For homes to become active participants in a smart grid, intelligent control algorithms are needed to facilitate autonomous interactions that take homeowner preferences into consideration. Many control algorithms for demand response have been proposed in the literature. Comparing the performance of these algorithms has been difficult because each algorithm makes different assumptions or considers different scenarios, i.e., peak load reduction or minimizing cost in response to the variable price of electricity. This work proposes a flexible assessment framework using the Analytical Hierarchy Process to compare and rank residential energy management control algorithms. The framework is a hybrid mechanism that derives a ranking from a combination of subjective user input representing preferences, and objective data from the algorithm performance related to energy consumption, cost and comfort. The Analytical Hierarchy Process results in a single overall score used to rank the alternatives. The approach is illustrated by applying the assessment process to six residential energy management control algorithms.

Cyberattacks in Smart Grids: Challenges and Solving the Multi-Criteria Decision-Making for Cybersecurity Options, Including Ones That Incorporate Artificial Intelligence, Using an Analytical Hierarchy Process

“…In the energy sector, particularly in the context of smart grids, various multi-criteria approaches are employed to address complex decision problems [116]. While the analytical hierarchy process (AHP) is recognized as a significant and widely used MCDM technique [117,118], its application specifically to cybersecurity in smart grids is relatively limited (Section 1.3).…”