Energy-Saving Control of Central Air-Conditioning System Based on an Improved-SSA

doi:10.16183/j.cnki.jsjtu.2022.018

Abstract

Abstract:

There are many terminals in the central air-conditioning system of which load demands vary frequently. Although conventional proportional integral derivative control or fixed parameter control can meet the load demand, there is a problem of energy waste caused by excess cooling. This paper proposes a central air-conditioning system energy-saving control method based on an improved sparrow search algorithm (ISSA) for the air-water system in the central air-conditioning system. The ISSA applies t-distribution to strengthening the search ability and enables the individual to learn from the best group based on the roulette wheel selection, which enhances the ability of the algorithm to jump out of the local optimum and improves the accuracy and stability of control parameters effectively. For the 12 test functions, most of the optimization accuracy and stability have been improved by more than 2 orders of magnitude. Compared with the original control strategy, the ISSA has shown a good energy-saving potential for energy optimization of air conditioning subsystems, reducing energy consumption by 25.13%. The feasibility of the ISSA in actual engineering problems has also been verified.

Key words: central air-conditioning system, optimal control, sparrow search algorithm (SSA), roulette wheel

CLC Number:

XIONG Lei, MIAO Yurun, FAN Xinzhou, YAO Ye. Energy-Saving Control of Central Air-Conditioning System Based on an Improved-SSA[J]. Journal of Shanghai Jiao Tong University, 2023, 57(4): 495-504.

Figures/Tables 7

Fig.1

Tab.1

Test functions of ISSA

测试函数	范围	最小值
$F 1 (s) = ∑ α = 1 δ s α 2$	[-100, 100]	0
$F 2 (s) = ∑ α = 1 δ \| s α \| + ∏ α = 1 δ \| s α \|$	[-10, 10]	0
$F 3 (s) = ∑ α = 1 δ ∑ ψ = 1 α s ψ 2$	[-100, 100]	0
$F 4 (s) = m a x α {\| s α \|, 1 ≤ α ≤ δ}$	[-100, 100]	0
$F 5 (s) = ∑ α = 1 δ (s α + 0.5) 2$	[-100, 100]	0
$F 6 (s) = ∑ α = 1 δ - 1 [100 (s α + 1 - s α 2) 2 + (s α - 1) 2]$	[-30, 30]	0
$F 7 (s) = ∑ α = 1 δ \| s α \| α + 1$	[-1, 1]	0
$F 8 (s) = ∑ α = 1 δ s α 2 + ∑ α = 1 δ (s α / 2) 2 + ∑ α = 1 δ (s α / 2) 4$	[-5, 5]	0
$F 9 (s) = ∑ α = 1 δ (s α 2 - 10 c o s 2 π s α + 10)$	[-5.12, 5.12]	0
$F 10 (s) = 14000 ∑ α = 1 δ s α 2 - ∏ α = 1 δ c o s s α α + 1$	[-600, 600]	0
$F 11 (s) = - 20 e x p - 0.2 1 δ ∑ α = 1 δ s α 2 - e x p 1 n ∑ α = 1 δ c o s 2 π s α + 20 + e$	[-32, 32]	0
$F 12 (s) = π δ [10 s i n π y 1 + ∑ α = 1 δ - 1 (y α - 1) 2 (1 + 10 s i n 2 π y α + 1)] + ∑ i = 1 δ u α$	[-50, 50]	0
$y α = 1 + s α + 1 4, u α = 100 (s α - 10) 4, s α > 10 0, - 10 ≤ s α ≤ 10 100 (- s α - 10) 4, s α < - 10$	[-50, 50]	0

Tab.1

Tab.2

Tab.3

Fig.2

Fig.3

Fig.4

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测试函数	ISSA1		ISSA2		ISSA
测试函数	平均值	标准差	平均值	标准差	平均值	标准差
F₁	4.81×10^-14	1.52×10^-13	1.09×10^-16	2.93×10^-16	1.72×10^-16	8.11×10^-16
F₂	5.78×10^-6	1.34×10^-5	5.97×10^-8	1.60×10^-7	2.86×10^-7	9.22×10^-7
F₃	1.25×10^-11	4.12×10^-11	3.19×10^-12	8.58×10^-12	9.38×10^-16	5.1×10^-15
F₄	6.55×10^-8	1.64×10^-7	1.96×10^-8	6.41×10^-8	5.76×10^-9	1.85×10^-8
F₅	1.06×10^-7	1.79×10^-7	1.04×10^-9	1.10×10^-9	6.47×10^-10	5.67×10^-10
F₆	4.20×10^-6	6.38×10^-6	4.83×10^-7	4.32×10^-7	7.47×10^-7	8.02×10^-7
F₇	4.24×10^-17	2.09×10^-16	6.63×10^-19	2.68×10^-18	6.85×10^-18	3.19×10^-17
F₈	3.52×10^-10	1.31×10^-9	8.19×10^-13	2.41×10^-12	5.55×10^-13	1.68×10^-12
F₉	3.01×10^-14	1.05×10^-13	4.91×10^-14	1.25×10^-13	2.75×10^-11	9.29×10^-11
F₁₀	3.74×10^-16	1.09×10^-15	1.47×10^-14	5.49×10^-14	3.70×10^-18	1.34×10^-18
F₁₁	1.68×10^-6	3.16×10^-6	4.72×10^-10	1.91×10^-9	4.53×10^-19	2.38×10^-9
F₁₂	2.06×10^-8	3.77×10^-8	7.35×10^-11	8.93×10^-11	2.71×10^-11	9.78×10^-11

测试函数	DE		GA		SBO		SSA		ISSA
测试函数	平均值	标准差	平均值	标准差	平均值	标准差	平均值	标准差	平均值	标准差
F₁	3.88×10^-5	1.08×10^-5	7.09×10	1.34×10²	1.44×10^-3	3.46×10^-4	1.86×10^-12	8.75×10^-12	1.72×10^-16	8.11×10^-16
F₂	7.58×10^-4	1.49×10^-4	1.79×10	9.34×10^-1	5.78×10^-2	2.16×10^-2	4.76×10^-5	1.77×10^-4	2.86×10^-7	9.22×10^-7
F₃	2.55×10^-3	5.98×10^-4	8.05×10³	9.54×10³	1.97×10	5.77×10	5.94×10^-9	3.04×10^-8	9.38×10^-16	5.10×10^-15
F₄	2.57	1.13	4.68×10	4.64	5.68	1.32	7.50×10^-7	2.07×10^-6	5.76×10^-9	1.85×10^-8
F₅	3.92×10^-5	1.21×10^-5	3.07×10	5.09×10	1.69×10^-3	6.45×10^-4	2.31×10^-6	5.52×10^-6	6.47×10^-10	5.67×10^-10
F₆	7.71×10	4.46×10	2.22×10³	3.94×10³	1.66×10²	1.57×10²	1.51×10^-5	2.69×10^-5	7.47×10^-7	8.02×10^-7
F₇	4.57×10^-23	2.07×10^-22	9.41×10^-7	4.91×10^-6	4.52×10^-11	3.29×10^-11	4.95×10^-16	2.13×10^-15	6.85×10^-18	3.19×10^-17
F₈	1.72×10²	2.32×10²	1.77×10²	2.32×10	3.14	2.66	9.80×10^-10	3.84×10^-9	5.55×10^-13	1.68×10^-12
F₉	6.73×10	1.14×10	6.59×10	5.93	2.59×10	8.05	8.22×10^-12	3.02×10^-11	2.75×10^-11	9.29×10^-11
F₁₀	3.89×10^-4	2.63×10^-4	1.53	8.73×10^-1	4.57×10^-2	1.81×10^-2	9.88×10^-14	4.47×10^-12	3.70×10^-18	1.34×10^-18
F₁₁	1.58×10^-3	2.16×10^-3	2.26	1.07	1.70	1.59	1.97×10^-6	8.11×10^-6	4.53×10^-19	2.38×10^-9
F₁₂	3.20×10^-6	5.53×10^-6	2.45	2.42	3.46	4.26	2.00×10^-6	2.41×10^-6	2.71×10^-11	9.78×10^-11