Table 2 Summary of literature survey on HEC and socio-inspired approach.
References | Topic | Inputs | Outputs: Methodology/Results |
|---|---|---|---|
Both Energy conservation and Energy Bill Analysis | Arduino and GSM to get the unit consumption of each house | Addressed manual energy billing mechanism issues and power shutdown | |
An automatic EB calculation system has been proposed | |||
This study is lacking in providing the system on the consumer side to evaluate monthly EB and its optimization approach | |||
Both Energy Conservation and Energy Bill Analysis | PV source | Multi-agent reinforcement learning | |
Energy bill | PV generation and load scheduling to reduce EB | ||
Both Energy conservation and Energy Bill Analysis | Renewable sources | The load classical optimization method to develop the Greedy Randomized Adaptive Search Procedure (GRASP) algorithm | |
Energy bill | Adjusting the demand peaks and low computational time | ||
Linear modeling approach was used | |||
Both Energy conservation and Energy Bill Analysis | Energy audit | Energy audit-based approach is used to implement DSM | |
Survey | DSM aims to obtain minimal cost planning or integrated resource planning | ||
DSM was validated using BPSO with constraints of peak-to-average ratio and cost reduction | |||
MATLAB simulation tool is used | |||
Due to large rating devices used in the industry, more profit was obtained for load DSM | |||
Both Energy conservation and Energy Bill Analysis | In-house display information | To optimize the HEC using a feedback mechanism within the house display | |
The main challenge is if the feedback is noisy | |||
Both Energy conservation and Energy Bill Analysis | Energy-storable and non-storable appliances are considered | Addressed the energy wastage issue | |
Integrated solar PV sources for EB optimization | |||
Both Energy conservation and Energy Bill Analysis | SCADA | Proposed the appliance controlling algorithm for household EC and EB optimization based on dynamic energy pricing | |
Solar PV panels, Battery banks, hybrid vehicles | The study says that SCADA can balance the minimization of EB of users with adjusting peak load demand for utility and limiting carbon emissions | ||
Energy conservation | QS for households | Variables used: construction features, energy usage, and users’ income level attributes | |
The old AC replacement has a 32% annual energy-saving potential | |||
Around 14% of houses followed EE programs and adjusted the AC temperature above 26 °C | |||
EE and EC programs should be revised based on requirements | |||
Energy conservation | QS for households | Applied various techniques: descriptive statistics, machine learning, and regression analysis | |
The AC usage in households is mainly increased due to AC usage at the workplace, increased income, and maintained social status | |||
Energy conservation | Real-time energy and resource management pricing signals | Discussed the DSM effectively utilizing demand-side resources and distribution infrastructure | |
Simulated work aims to maximize social welfare by developing an optimization model | |||
The optimization model has been developed to decentralize work, further used to achieve social welfare | |||
Cost optimization | Review | Cost optimization using the Particle Swarm Optimization algorithm is applied | |
Load data | The application of the proposed work can be helpful for load forecasting, scheduling, and management | ||
Energy Bill Analysis | Energy consumption data | DSM framework, techniques, optimization models, and methods are discussed | |
Highlighted that the heuristic, stochastic optimization techniques and game theory are essential to deal with DSM for solving complex and dynamic energy load management problems | |||
Energy Bill Analysis | Solar PV source | Case study based on 2BHK residential flat | |
Renewable distributed generation can be integrated into the conventional grid system to reduce the EB | |||
Defined the objective cost function for EB optimization through a simulated linear programming approach | |||
Load Profile classification | Load profile data | Worked on a systematic framework for load profile classification like human-readable and machine-readable | |
The data mining techniques like classification and regression trees are used to extract the features in the frequency domain | |||
A hierarchical classification tree is a more effective and systematic method for load profile classification | |||
Cost optimization in microgrid | Real data of non-dispatchable resources and non-responsive loads | Aims for optimum operation strategy of microgrid by cost optimization and demand response regulation | |
Implemented a multi-period imperialist competition algorithm with an expert heuristic approach | |||
ANN and the Markov-chain method are applied to predict non-dispatchable power generation and load demand under uncertain conditions | |||
Socio-inspired optimization | Group of families | This work highlighted that the social evolution and learning way is faster to influence behavioral change than the genetic evolution and learning method | |
The work has provided ground to explore the metaheuristic optimization approach to solve real-world, specific, and complex problems | |||
Socio-inspired optimization | Group of families | Discussed Multi-Cohort Intelligence (CI) metaheuristic algorithm using intra-group and inter-group learning mechanisms | |
The prominent features and limitations of the Multi-CI algorithm have been discussed | |||
The Multi-CI algorithm can be further used to solve real-world and constrained test problems | |||
MATLAB tool is used for simulation | |||
Socio-inspired optimization | Group of families | Proposed a socio-inspired optimization-based ideology algorithm | |
Proposed work applied self-interested, competitive behavior evolution and learning approaches in political applications to improve their rank | |||
This work improved the optimization performance regarding objective function values and computational time | |||
MATLAB tool is used for simulation |
