A Birandom Chance-Constrained Linear Programming Model for CCHP System Operation Management: A Case Study of Hotel in Shanghai, China

Table 4

System cost variation based on change of sensitivity parameters.

Item	Parameter variation (%)	Winter		Transition		Summer
		Cost (RMB)	Change rate (%)	Cost (RMB)	Change rate (%)	Cost (RMB)	Change rate (%)
Electricity price	–20	1414768	–3.88	1096544	–11.21	1672504	–8.71
	–10	1443294	–1.94	1165733	–5.60	1752281	–4.35
	+10	1500346	1.94	1304112	5.60	1911834	4.35
	+20	1528872	3.88	1373301	11.21	1991610	8.71
Natural gas price	–20	1235970	–16.02	1126954	–8.74	1626379	–11.23
	–10	1353895	–8.01	1180938	–4.37	1729218	–5.61
	+10	1589745	8.01	1288906	4.37	1934897	5.61
	+20	1707670	16.02	1342890	8.74	2037736	11.23
Heating demand	+25	1635522	11.12	1276131	3.34	1838961	0.38
	+50	1824295	23.95	1317339	6.67	1845865	0.75
	+100	2312825	57.14	1399756	13.35	1859673	6.03
Cooling demand	+25	1476254	0.30	1267951	2.67	1968859	7.47
	+50	1480688	0.60	1300980	5.35	2108684	15.10
	+100	1489555	1.20	1367038	10.70	2438152	33.08
Electricity demand	+25	1672031	13.61	1469416	18.99	2146366	17.16
	+50	1872241	27.21	1703909	37.98	2460675	34.31
	+100	2272663	54.41	2279530	84.59	3089293	68.62