Air-Conditioner Group Power Control Optimization for PV integrated Micro-grid Peak-shaving

Mohammed Al-Azba; Zhaohui Cen; Yves Remond; Said Ahzi

doi:10.3934/jimo.2020112

Article Contents

2021, Volume 17, Issue 6: 3165-3181. Doi: 10.3934/jimo.2020112 open access

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Air-Conditioner Group Power Control Optimization for PV integrated Micro-grid Peak-shaving

a.
Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Doha 5825, Qatar
b.
ICube Laboratory, Université de Strasbourg–CNRS, Strasbourg 67000, France

^* Corresponding author: Zhaohui Cen
^* Corresponding author: Zhaohui Cen

Received: November 30, 2019

Revised: February 29, 2020

Early access: June 2020

Published: November 2021

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Abstract

Heating, Ventilation, and Air-Condition (HVAC) systems are considered to be one of the essential applications for modern human life comfort. Due to global warming and population growth, the demand for such HVAC applications will continue to increase, especially in arid areas countries like the Arabian Gulf region. HVAC systems' energy consumption is very high and accounts for up to 70% of the total load consumption in some rapidly growing GCC countries such as Qatar. Additionally, the local extremely hot weather conditions usually lead to typical power demand peak issues that require adequate mitigation measures to ensure grid stability. In this paper, a novel control scheme for a combined group of Air-Conditioners is proposed as a peak-shaving strategy to address high power demand issues for Photo-Voltaic(PV)-integrated micro-grid applications. Using the local daily ambient temperature as input, the AC group control optimization is formulated as a Mixed-Integer Quadratic Programming (MIQP) problem. Under an acceptable range of indoor temperatures, the units in the same AC group are coordinately controlled to generate desired power consumption performance that is capable of shaving load peaks for both power consumption and PV generation. Finally, various simulations are performed that demonstrate the effectiveness of the proposed control strategy.

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Mathematics Subject Classification: Primary: 49N90, 49N10; Secondary: 93C95.

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Figure 1. Baseline on-off AC control temperature profile

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Figure 2. AC Group Control ICT hardware infrastructure diagram

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Figure 3. Flowchart for AC group control program

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Figure 4. Outdoor Temperature in One day measured in Qatar

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Figure 5. On-Off Control Power profile subjected to different time delay

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Figure 6. Indoor Temperature Control profile Comparison

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Figure 7. Indoor temperature profiles of load-side peak shaving (The different curves are for the considered 40 AC units)

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Figure 8. Individual AC power control logic of load-side peak shaving

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Figure 9. Load-side shaving by AC group control

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Figure 10. Indoor temperature profiles under binary Mode

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Figure 11. Individual AC power control logic for PV peak shaving scenario under binary mode

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Figure 12. PV side Peak-shaving by AC group control under binary Mode

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Figure 13. Indoor temperature profiles under Ternary Mode (0-1-2)

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Figure 14. Individual AC power control logic under Ternary Mode (0-1-2)

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Figure 15. PV side Peak-shaving by AC group control with Ternary Mode (0-1-2)

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Table 1. House thermal model parameters definition

Parameter	Definition
$ {T}_{indoor} $	Indoor temperature of the house
$ {T}_{outdoor} $	Outdoor temperature of the house
$ {{\dot{Q}}_{d}} $	Heat flow from outdoor to the house
$ {{\dot{Q}}_{e}} $	Cooling Energy by AC system
$ R $	Thermal resistance from outdoor to the house
$ m $	Mass of the indoor air
$ {{C}_{p}} $	Heat capacities of the room air

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Table 2. Parameters values of the thermal model and optimization

Parameter	Value	Parameter	Value
A	-2.00123e-4	$ J_{SW} $	2
B	4.4028e-6	Cp($ J/Kg^oC $)	1005
E	0.002*$ T_{ref} $	$ m(kg) $	222
R($ ^oC/W $)	0.022	$ Q $	300

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