Table 5 Energy management techniques
Data guided management models | Methods and techniques | Purpose | Constraint | Advantage | Disadvantage |
|---|---|---|---|---|---|
Residential home energy management models [113] | Binary backtracking search algorithm, Mixed integer linear programming, Internal genetic algorithm, Outer particle swarm optimization, Integer linear programming | Energy consumption optimization and Electricity bill reduction | Consumer comfort is compromised | (1) Increased energy efficiency, (2) correctness and calculation speed, (3) Reduced electricity consumption | Solution is often not optimized |
Household appliance scheduling management [114] | Shuffled frog leaping algorithm, Teaching and learning based optimization algorithm | Gross bill reduction and peak power reduction | Consumer comfort is compromised | Problems related to combinatorial optimization are easily solved | Convergence operation is sometimes slow and premature |
Residential power scheduling management [115] | Integer linear programming | Establishment of sophisticated trade-off between bill and pay | Peak-to-average ratio is ignored | Capable of high-quality decision making | Unable to handle non-linear data and uncertainty |
Network based energy management models [116] | ZigBee, Wi-Fi, Z-Wave | Carbon footprint reduction | Consumer comfort is compromised | (1) Improves interoperability and energy efficiency, (2) Lessens carbon emissions, (3) Cost friendly | Transmission rate is lower comparatively |
Heuristic home energy management models [117] | Heuristic algorithms | Electricity cost optimization and execution time reduction | N/A | (1) Affordable waiting time, (2) Reduces peaks in demand and electricity cost | Takes longer time to make optimum decision |
Demand response management approaches [118] | Time of use pricing scheme, Real-time pricing scheme and Demand Response Algorithms | Potential social benefits and bill reduction | Consumer comfort is compromised | Ensures optimal consumption and prices | Requires high computational power |
Fuzzy control based management system [119] | Time of use pricing scheme, Real-time pricing scheme, Inclined block rate pricing scheme | Peak-to-average ratio optimization | High computational power needed | Energy consumption reduction | The system needs frequent update |