Operation Cost Optimization on an Ultralow Emission System Based on Improved Collaborative Optimization

Song Zheng,Kafei Tang,Xiaoqing Zheng,Shuai Chen

doi:10.1109/access.2020.2974938

Song Zheng, Kafei Tang + Show 2 more

Open Access

https://doi.org/10.1109/access.2020.2974938

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Journal: IEEE Access	Publication Date: Jan 1, 2020
Citations: 16	License type: CC BY 4.0

Affiliation: Hangzhou Dianzi University

Abstract

Due to the lack of an effective overall coordinated treatment method, it is difficult to achieve low cost and efficient removal of pollutants from coal-fired flue gas. This paper establishes a collaborative optimization model for ultralow emission systems, including a system level model of operation cost and three discipline level models for denitration, desulfurization, and dust removal. An improved collaborative optimization method with a dynamic penalty function is proposed to optimize an ultralow emission system. Simulation results show that the improved method achieves better global optimization and effectively reduces the operation cost of the system under ultralow emission constraints.

Highlights

Due to the continuous enhancement of environmental protection requirements, ultralow emission systems for coal-fired power plants (ULE system) are constantly being updated and improved
The results show that the operation cost of condition 3 with low load and high pollutant concentration is the highest, at 0.028383 yuan/kWh
The second strategy considers the collaborative removal among devices and uses centralized decision, which is solved by particle swarm optimization (PSO)

Summary

INTRODUCTION

Due to the continuous enhancement of environmental protection requirements, ultralow emission systems for coal-fired power plants (ULE system) are constantly being updated and improved. Kroo et al proposed a new approach, collaborative optimization (CO), which is considered a kind of advanced decentralized solving strategy. This approach decomposes the problem into two levels of optimized structure, and it has high degree of autonomy and good adaptability, suitable for optimization problems of multimodel complex systems such as reducers. An improved collaborative optimization method based on a dynamic penalty function is proposed in this paper.

OPERATION COST MODEL FOR COLLABORATIVE REMOVAL IN A ULE SYSTEM

OPERATION COST MODEL FOR DESULFURIZATION

OPERATION COST MODEL FOR DEDUSTING

CASE STUDIES

Findings

CONCLUSION