Computational Intelligent Algorithms in Smart Energy Management Systems for Home Energy Management: A Systematic Review of Optimisation Techniques
Abstract
The proliferation of rooftop photovoltaic (PV) generation, residential battery energy storage systems (ESS), and plug-in hybrid/electric vehicles (PHEV) has transformed the household from a passive electricity consumer into an active, schedulable participant in the smart grid. Realising this potential requires a Home Energy Management System (HEMS) capable of solving a mixed-integer, nonlinear, and typically multi-objective scheduling problem in near-real time. Over the past decade, a large and fast-growing body of literature has proposed heuristic, metaheuristic, and hybrid computational intelligence algorithms to solve this problem, yet the field lacks a recent, systematic synthesis that classifies these approaches, quantifies their coverage of key objectives and distributed energy resources (DERs), and identifies concrete, evidence-based research gaps. This paper presents a systematic review of 27 primary studies on HEMS optimisation published between 2016 and 2024, drawn from IEEE, Elsevier, Springer, and MDPI venues. We propose a five-family taxonomy rule-based and mathematical programming, classical metaheuristics (GA, PSO, BPSO), nature-inspired metaheuristics, Differential Evolution (DE) and its improved variants, and quantum-inspired hybrid algorithms and use it to structure a comprehensive comparative analysis of each study's optimisation method, objective functions, DER configuration, reported results, and limitations. The synthesis reveals that single- or…
How strong is the evidence?
Evidence Hub reads this as a systematic review. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
Read the paper
Related studies
- Chaos and quantum thermalization
- The Dalton quantum chemistry program system
- Cord Blood Leptin and Adiponectin as Predictors of Adiposity in Children at 3 Years of Age: A Prospective Cohort Study
- Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes
- Stable adiabatic quantum batteries
- A novel self-lipid antigen targets human T cells against CD1c(+) leukemias
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.