Research on two-stage planning optimization approach for community integrated energy systems considering off-design conditions

doi:10.3969/j.issn.2097-0706.2022.10.001

Abstract

Abstract:

The community integrated energy system（CIES）can significantly improve energy utilization efficiency and facilitate the consumption of renewable energy through multi-energy complementary and collaborative optimization scheduling.It has become a new energy utilization approach to balance multi-energy supply and demand on user side.Taking a community in Xiong’an New District as the research object，a two-stage optimization approach for the CIES considering off-design conditions is proposed.At the first stage，non-dominated sorting genetic algorithm（NSGA-II）with elite preservation strategy is taken to optimize the equipment type and capacity of the community energy station.It is a multi-objective planning optimization problem，aiming at coordinately scheduling the economic costs and environmental costs.At the second stage，operation optimization is made.Considering the uncertainty of wind and PV outputs and taking the system economy，environmental cost and users’ comfort as optimization objects，the multiple Pareto fronts obtained at the first stage are solved by Benders decomposition optimization method and the optimal outputs of different generators in various plans are obtained.The comprehensive costs of different plans are the important indicator for determining the best planning scheme.Case studies show that the designed planning scheme takes the operation uncertainty into consideration at the second stage，and realizes the refined operation simulation by fully considering the characteristics of equipment under variable working conditions.The approach can effectively reduce the system operating cost and guarantee the reliability of power supply，which is practical for instructing the CIES planning.

Key words: CIES, off-design condition model, planning optimization, NSGA-II, renewable energy consumption

CLC Number:

TK01：TM07

WEN Gangcheng, SHI Xin, ZHANG Yi, FANG Fang. Research on two-stage planning optimization approach for community integrated energy systems considering off-design conditions[J]. Integrated Intelligent Energy, 2022, 44(10): 1-11.

Figures/Tables 14

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Table 1

Parameters of the CIES devices

设备	符号	值	设备	符号	值
光伏	$P P V, m a x$ /kW	1 000	风机	$P W T, m a x$ /kW	1 500
	$E 0$ /(W·m^-2)	1		$v i n$ /(m·s^-1)	3
	$α P V$	-0.4		$v o u t$ /(m·s^-1)	25
	T₀/℃	25		$v R -$ /(m·s^-1)	11
	$T c, N O C T$ /℃	48		$v R +$ /(m·s^-1)	12
	$T α, N O C T$ /℃	20	CHP	$P C H P, m a x e$ /kW	1 200
	$η s$	0.15	CHP	$N C H P, m i n h$ /%	30
	$E T, N O C T$ /(W·m^-2)	0.8	GB	$P G B, m a x h$ /kW	1 400
	$f P V$	0.9	GB	$N G B, m i n h$ /%	30
地源热泵	$P H P, m a x h$ /kW	600	蓄电设备	$P E S, m a x$ /kW	300
蓄热设备	$P H S, m a x$ /kW	300

Table 1

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Table 3

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方案	容量/kW								年投资成本/ 万元	年运行成本/ 万元	年碳排放量/ t
方案	CHP	PV	WT	EB	GSHP	GB	ES	HS	年投资成本/ 万元	年运行成本/ 万元	年碳排放量/ t
1	1 100	960	1 240	0	1 120	700	900	400	194.486	268.214 8	1 892.84
2	1 080	900	1 170	0	1 050	750	740	0	177.296	278.064 5	1 954.35
3	1 020	700	1 010	0	1 000	830	420	0	158.728	286.928 6	2 047.87

方案	类型	供电占比/%				供热占比/%			购电成本/元	购气成本/元	运行成本/元	碳排放成本/元	总成本/ 元	年综合成本/万元
方案	类型	CHP	WT	PV	电网	CHP	GB	HS	购电成本/元	购气成本/元	运行成本/元	碳排放成本/元	总成本/ 元	年综合成本/万元
1	高峰日	51.0	33.0	5.7	10.4	45.1	11.1	43.7	2 171.1	20 180.2	1 254.4	631.0	24 236.6	472.16
	工作日	49.2	33.5	5.8	11.6	43.6	11.5	44.8	2 385.1	19 333.6	1 229.8	616.5	23 565.0
	休息日	44.4	36.7	6.4	12.5	37.0	14.5	48.5	2 322.2	16 596.7	1 149.1	540.0	20 608.1
2	高峰日	53.4	31.5	5.4	9.7	46.7	13.0	40.4	2 033.8	21 138.3	1 244.3	650.5	25 066.8	464.02
	工作日	51.9	32.0	5.5	10.6	45.4	13.4	41.2	2 166.0	20 361.3	1 220.9	635.7	24 384.0
	休息日	47.6	34.8	6.1	11.5	39.1	16.2	44.7	2 103.2	17 680.1	1 139.1	560.7	21 483.2
3	高峰日	57.1	27.5	4.3	11.2	49.3	13.2	37.5	2 491.3	22 252.8	1 206.2	691.6	26 641.9	467.97
	工作日	56.0	28.0	4.3	11.7	48.4	13.6	38.0	2 461.4	21 580.4	1 185.0	676.4	25 903.1
	休息日	52.4	31.1	4.8	11.7	42.3	16.7	41.0	2 118.0	18 988.5	1 110.2	596.7	22 813.5