Two-Layer Collaborative Optimization Configuration Method for CCHP System with Wind-Solar-Storage

doi:10.12204/j.issn.1000-7229.2021.08.009

Abstract

Abstract:

The efficient and economical operation of combined cooling, heat and power (CCHP) system depends on the overall optimization of the system’s equipment capacity and operating strategy. In order to improve the practicality of the CCHP, a two-layer collaborative optimization configuration method for the CCHP system considering wind power, solar power and energy storage is proposed. The optimized configuration of the outer layer aims at the best economic net present value and the lowest pollutant emissions as the objective function, and the NSGAⅡ algorithm is used to obtain the capacity configuration of the devices. The dual theory is used in the inner optimization configuration to build a robust model, and the optimal annual operating cost considering pollutant emissions and energy purchase costs is the objective function to obtain the optimal scheduling of each device. Finally, taking the CCHP system of a certain park as the research object, the double-layer collaborative optimization configuration method proposed in this paper is used to optimize the configuration of the system. The simulation results verify the effectiveness of the proposed method, which can effectively realize the collaborative optimization of the system with both economy and environmental protection.

Key words: combined cooling, heating and power (CCHP) system, two-layer optimization configuration, NSGAⅡ algorithm, duality theory, robust model

CLC Number:

TM732

JIANG Zhuohan, LIU Zhigang, XU Jiazhu, WU Min, XIE Xintao, HOU Yiling. Two-Layer Collaborative Optimization Configuration Method for CCHP System with Wind-Solar-Storage[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(8): 71-80.

Figures/Tables 12

Fig.1 Structure of a CCHP system with wind power, solar power and energy storage

Fig.2 Flowchart of two-layer optimization solution

Fig.3 Typical daily load

Fig.4 Daily output curve of wind and solar power

Table 1 Economic and technical parameters of the devices

Table 2 Time-of-use price

Fig.5 Pareto frontier solution for outer multi-objective optimization

Table 3 Device configuration plan

Fig.6 CCHP operation output with different seasons

Fig.7 SOC of the battery in different seasons

Table 4 Operating costs in different scenarios

Table 5 Operating costs under different robust parameters

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