# Demand Side Management in Nearly Zero Energy Buildings Using Heuristic Optimizations

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## Abstract

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## 1. Introduction

- nZEB: a ZEB connected to grid having a nearly zero energy balance. This means that the energy consumption in any building or sector is slightly greater than the total renewable energy.
- net zero energy building (NZEB): a ZEB connected to grid having zero energy balance. The total energy consumption and generation are almost equal.
- positive energy building (PEB): has a positive energy balance. The energy consumption in PEB is less than the energy generation from renewable sources where surplus energy is sold back to the grid.

## 2. Related Work

## 3. Problem Description

## 4. System Model

- a CHP production plant with a 1.2 heat to power ratio.
- a boiler of 120-kW capacity.
- one BSS with charge and discharge efficiencies of 90%.
- a gas connection for the CHP and boiler to run.
- the total payable cost depends on the electricity price, the natural gas price and the operation cost.

#### 4.1. Power Output of Renewable Energy Sources

#### 4.2. Load Categorization

- Inflexible appliances: This type of appliance is also referred to as fixed or regular appliances because of their constant power usage pattern and length of operation time. Typically, inflexible loads include fridge, fan, light, etc., which are considered to be required run loads and cannot be shifted to later hours. These appliances usually do not participate in the DR, so they cannot contribute to the optimization process in order to achieve lower electricity bill. Therefore, regular loads execute their job on respective time slots and have no relation with the appliance scheduler.
- Flexible appliances: Flexible loads are also known as shiftable or burst loads. Flexible appliances include the dish washer, washing machine, spin dryer, etc. The power consumption pattern of this type of appliance can be altered to later hours in response to some incentives. Appliances are shifted to later hours due to two main reasons: either appliances are preferred to alter the consumption pattern from on-peak hours to off-peak hours or when the price for the grid is high, appliances are shifted to low price hours for bill reduction.

#### 4.3. Energy Consumption Model

#### 4.4. Capacity Constraints

#### 4.5. Thermal Storage Constraints

#### 4.6. Electric Storage Constraints

#### 4.7. Energy Balance

#### 4.8. Start and End Time Horizon

#### 4.9. Power Demand

#### 4.10. Peak to Average Ratio

#### 4.11. Waiting Time

#### 4.12. Objective Function

## 5. Heuristic Techniques

#### 5.1. Teaching Learning-Based Optimization

#### 5.2. Enhanced Differential Evolution

#### 5.3. Enhanced Differential Teaching Learning Algorithm

Algorithm 1: Enhanced differential teaching learning algorithm. |

## 6. Feasible Region of Objective Function

#### Feasible Region of Trade-Off

## 7. Simulations and Discussion

#### 7.1. Electricity Demand

#### 7.2. Electricity Cost

#### 7.3. Peak to Average Ratio

#### 7.4. User Discomfort

#### 7.5. Heat Demand

#### 7.6. Execution Time and Performance Tradeoffs

## 8. Life Cycle Energy Analysis

## 9. Conclusions and Future Work

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## References

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**Figure 11.**Hourly electricity demand. Teaching learning-based optimization (TLBO); enhanced differential evolution (EDE); and enhanced differential teaching learning algorithm (EDTLA).

Task | Power (kW) | Earliest Starting Time (h) | Latest Finishing Time (h) | Time Window Length (h) | Duration (h) |
---|---|---|---|---|---|

Dish washer | 1.5 | 9 | 17 | 8 | 2 |

Cloth washer | 1.5 | 9 | 12 | 3 | 1.5 |

Spin dryer | 2.5 | 13 | 18 | 5 | 1 |

Cooker hob | 3 | 8 | 9 | 0.5 | 0.5 |

Cooker oven | 5 | 18 | 19 | 0.5 | 0.5 |

Microwave | 1.7 | 8 | 9 | 0.5 | 0.5 |

Lighting | 0.84 | 18 | 24 | 6 | 6 |

Laptop | 0.1 | 18 | 24 | 6 | 2 |

Desktop | 0.3 | 18 | 24 | 6 | 3 |

Cleaner | 1.2 | 9 | 17 | 8 | 0.5 |

Fridge | 0.3 | 0 | 24 | - | 24 |

Electric car | 3.5 | 18 | 8 | 14 | 3 |

Resource | Capacity | Efficiency (%) | Operation/Maintenance Cost (%) |
---|---|---|---|

CHP | 20 kW | 40 | 2.7 cents/kWh |

Boiler | 120 kW | 85 | 2.7 cents/kWh |

Storage | 10 kWh | 90 | 0.5 cents/kWh |

Technique | Total Load (kW/day) | Total Cost ($/day) | CO${}_{2}$ Emissions (kg) | PAR Reduction (%) | Cost Reduction (%) |
---|---|---|---|---|---|

Unscheduled | 1056 | 135.88 | 551.3 | - | - |

GA | 1056 | 116.37 | 551.3 | 17.30 | 14.70 |

TLBO | 1056 | 89.4784 | 551.3 | 30.76 | 33.82 |

EDE | 1056 | 118.66 | 551.3 | 15.38 | 12.76 |

EDTLA | 1056 | 82.14 | 551.3 | 43.61 | 36.02 |

Technique | Grid Energy (kW/day) | RESs Generation (kW/day) | Total Cost ($/day) | PAR Reduction (%) | Cost Reduction (%) | CO${}_{2}$ Reduction (%) |
---|---|---|---|---|---|---|

Unscheduled | 630 | 426 | 92.63 | - | - | 40.35 |

GA | 566 | 490 | 84.2461 | 11.29 | 36.76 | 46.41 |

TLBO | 570 | 486 | 48.1144 | 14.51 | 64.70 | 46.03 |

EDE | 600 | 456 | 62.2162 | 11.02 | 52.94 | 56.82 |

EDTLA | 580 | 476 | 44.8372 | 29.41 | 67.44 | 54.94 |

Algorithm | Time (s) | Time with RES (s) |
---|---|---|

Unscheduled | 0.09314 | 0.195858 |

GA | 3.4122 | 4.6754 |

TLBO | 8.0142 | 8.2490 |

EDE | 1.2841 | 2.4903 |

EDTLA | 8.9164 | 9.9490 |

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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**MDPI and ACS Style**

Javaid, N.; Hussain, S.M.; Ullah, I.; Noor, M.A.; Abdul, W.; Almogren, A.; Alamri, A.
Demand Side Management in Nearly Zero Energy Buildings Using Heuristic Optimizations. *Energies* **2017**, *10*, 1131.
https://doi.org/10.3390/en10081131

**AMA Style**

Javaid N, Hussain SM, Ullah I, Noor MA, Abdul W, Almogren A, Alamri A.
Demand Side Management in Nearly Zero Energy Buildings Using Heuristic Optimizations. *Energies*. 2017; 10(8):1131.
https://doi.org/10.3390/en10081131

**Chicago/Turabian Style**

Javaid, Nadeem, Sardar Mehboob Hussain, Ibrar Ullah, Muhammad Asim Noor, Wadood Abdul, Ahmad Almogren, and Atif Alamri.
2017. "Demand Side Management in Nearly Zero Energy Buildings Using Heuristic Optimizations" *Energies* 10, no. 8: 1131.
https://doi.org/10.3390/en10081131