Name
Abstract | ||
|---|---|---|
The energy demand of residential end users has been so far largely uncontrollable and inelastic with respect to the power grid conditions. In this paper, we describe a scheme to solve multiple knapsack problems (MKP) using heuristic algorithms. Keeping total energy consumption of each household appliance under certain threshold with maximum benefit is regarded as knapsack problem. Here, we design multiple knapsack problems for each hour of a day to schedule different numbers of appliance. To avoid peak hours, load is shifted in low and mid peak hours. Different algorithms are used to schedule household appliances. We use ant colony optimization (ACO) that is one of the meta-heuristic techniques to solve multiple knapsack problems which enables fast convergence rate for scheduling of appliances. Results show that propose scheme is an efficient method for home energy management to maximize user comfort and minimize electricity bills. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/NBiS.2015.11 | NBiS |
Keywords | Field | DocType |
Demand-side management, Residential users, Devices scheduling, Multiple knapsack problems, Heuristic techniques, Ant colony optimization algorithm (ACO), Renewable sources, Storage systems, Electric energy market | Ant colony optimization algorithms,Energy management,Mathematical optimization,Heuristic,Smart grid,Scheduling (computing),Computer science,Rate of convergence,Knapsack problem,Energy consumption | Conference |
ISSN | Citations | PageRank |
2157-0418 | 2 | 0.42 |
References | Authors | |
6 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| S. Rahim | 1 | 5 | 1.54 |
| S. A. Khan | 2 | 6 | 1.62 |
| Nadeem Javaid | 3 | 1043 | 222.46 |
| Nusrat Shaheen | 4 | 11 | 2.04 |
| Zafar Iqbal | 5 | 65 | 17.87 |
| Ghazanfar Rehman | 6 | 8 | 1.27 |