A MINLP model of optimal scheduling for a district heating and cooling system: A case study of an energy station in Tianjin. (15th December 2017)

• Record Type: Journal Article
• Authors: Deng, Na; Cai, Rongchang; Gao, Yuan; Zhou, Zhihua; He, Guansong; Liu, Dongyi; Zhang, Awen
• Is Part Of: Energy. Volume 141(2017)
• Page Start: 1750
• Page End: 1763
• Publication Date: 2017-12-15
• Subjects: District heating and cooling system -- Water thermal energy storage -- Actual operation data -- Optimal scheduling -- Mixed-integer nonlinear model -- Operation cost analysis; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2017.10.130
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Rational scheduling strategy is the key to play the economy of district heating and cooling (DHC) system. However, very limited studies have been conducted on it using a suitable model or based on actual operational data, which made the obtained results not realistic or feasible. This paper proposes an actual operational-based optimal scheduling strategy to minimize the daily operation cost of an energy station in Tianjin integrated with electric chiller (EC) system, ground source heat pump (GSHP) system, water thermal energy storage (WTES) system and combined cooling, heating and power (CCHP) system under background of actual cooling load demand. Considering both nonlinear input-output characteristics and discrete working ranges of energy equipments, the mixed-integer nonlinear programming model is used to solve this problem. Results illustrate that the proposed optimal scheduling strategy can achieve zero waste of cooling energy and the cost saving ratio can reach to 24.3%, 34.2%, 47.3% and 63.9% under the load ratio of 75%, 60%, 45% and 30% respectively, compared with the existing scheduling strategy, which shows the cost saving effect is significant especially for the new-built energy station during the initial operation stage. Highlights: Optimal scheduling strategy based on the actual operation was developed. Mixed-integer nonlinear programming approach was used for the optimal scheduling. Cooling output and operation cost characteristics of each subsystem was investigated. Operation cost of the proposed strategy was compared with that of the current one.