Intelligent Multi-Pollutant Emission Control via Global Optimization
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Solution Overview
Problem
Existing ultra-low emission systems face challenges such as mutual independence of pollutant control facilities, significant operating fluctuations, and high costs for pollutant removal, making it difficult to achieve optimal control of multiple pollutants simultaneously.
Innovation Solution
An intelligent multi-pollutant ultra-low emission system with a four-layer structure, comprising a device layer, a sensing layer, a control layer, and an optimization layer, which uses advanced modeling, optimization, and control methods to overcome the complexities of multi-condition, multi-pollutant systems and achieve efficient simultaneous pollutant removal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pollutant control facilities operate separately in a pyramid manner, then each facility can be controlled independently, but the system cannot achieve multi-pollutant simultaneous removal and optimal control
Solution Approach 1:
The patent merges multiple independently controlled pollutant removal facilities into an integrated control system. The control method coordinates desulfurization, denitration, and precipitation facilities to operate simultaneously and cooperatively, achieving multi-pollutant removal while maintaining the operational independence of each facility through centralized coordination.
Solution Approach 2:
The control system is designed with universal functionality to handle multiple pollutant types (SO2, NOx, PM) simultaneously. The system can adaptively adjust control parameters for different facilities based on real-time pollutant concentrations, enabling a single control framework to manage diverse removal processes efficiently.
2Device complexity
If manual control in a pyramid manner is used, then the system structure is simple, but the system cannot adapt to dynamic operating conditions and frequent load variations
Solution Approach 1:
The control system transitions from static manual control to dynamic automated control that continuously adapts to changing operating conditions. The system real-time adjusts control parameters based on fluctuating load conditions, coal quality variations, and pollutant concentrations, enabling flexible response to dynamic demands while maintaining a relatively simple overall structure.
Solution Approach 2:
The patent implements feedback control mechanisms that monitor pollutant concentrations and system performance in real-time. Based on this feedback, the control system automatically adjusts operational parameters to maintain optimal performance under varying conditions, significantly improving adaptability without requiring complex manual intervention.
3Reliability
If environmentally-friendly facilities consume more materials and energy to improve pollutant emission reduction efficiency, then emission standards are met, but the operating cost increases
Solution Approach 1:
The control system optimizes operational parameters (such as injection rates, temperatures, and flow rates) to achieve the highest possible emission reduction efficiency with minimal material and energy consumption. By continuously adjusting parameters based on real-time conditions, the system maintains reliable pollutant removal while minimizing resource usage.
Solution Approach 2:
The system applies partial action principles by adjusting the intensity of pollutant removal based on actual needs. Rather than consistently operating at maximum capacity, the system uses just enough energy and materials to meet emission standards, avoiding excessive consumption while maintaining reliable performance.
4Ease of operation
If existing operating manners based on workers' experience are used, then the system is easy to operate, but accurate regulation and optimal control cannot be achieved when operating conditions change
Solution Approach 1:
The patent replaces manual operational experience with an automated control system that uses sensors, controllers, and computational algorithms. This substitution maintains ease of operation through automated decision-making while significantly improving measurement precision and accurate regulation through real-time data processing and adaptive control algorithms.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system improves the controllability and adjustability of ultra-low emission systems, reduces operating costs, and enhances the stability and reliability of pollutant emission control, enabling efficient, reliable, and economical operation.
Implementation Method 1
desulfurization device
Implementation Method 2
realizes efficient removal of pollutants through a series of physical and chemical reactions
Implementation Method 3
denitration device
Implementation Method 4
precipitators
Data Source
AI summary
The invention relates to an intelligent multi-pollutant ultra-low emission system and a global optimization method thereof. The intelligent multi-pollutant ultra-low emission system comprises a device layer, a sensing layer, a control layer and an optimization layer from bottom to top. The global optimization method comprises: obtaining an accurate description multiple pollutants in the generation, migration, transformation and removal process in multiple devices by means of accurate modeling of a multi-device multi-pollutant simultaneous removal process of the ultra-low emission system; accurately evaluating multi-pollutant emission reduction costs under different loads, coal qualities, pollutant concentrations and operating parameters through a global operating cost evaluation method of the ultra-low emission system; realizing minute-level planning and optimization of emission reductions of a global pollutant emission reduction device under different emission targets through a multi-pollutant, multi-target and multi-condition global operating optimization method; and guaranteeing reliable emission reduction and margin control of the pollutants through an advanced control method for reliable up-to-standard ultra-low emission of the pollutants.