Multi-Criteria Optimization of Pulverized Fuel Coal-Fired Power Generation System Load Dispatching

2003 ◽  
Author(s):  
Hongtao Li ◽  
Meinrad Burer ◽  
Franc¸ois Marechal ◽  
Daniel Favrat ◽  
Guolian Hou ◽  
...  
Keyword(s):  
Power Generation ◽  
Co2 Emissions ◽  
Total Power ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Start Up ◽  
Partial Load ◽  
Pulverized Fuel ◽  
Power Dispatching ◽  
Daily Total

With a given power demand pattern supplied by a set of pulverized fuel coal-fired (PC) power generation units at various locations, different power dispatching solutions will result in different fuel consumptions, CO2 emissions, and power generation costs. This is due to the performance differences of their shut-down and start-up processes as well as those under the operational conditions, and to fuel prices differences between different power stations. In this paper, a methodology characterized with a multi-objective optimization approach based on a fast evolutionary algorithm is employed to optimize the daily total power generation operating cost and the daily total CO2 emissions. The shut down and start-up processes are divided into 7 sub-operations: load-decreasing, shutdown, boiler ignition preparation, ignition-warming up, connecting to grid, load-increasing and stabilization process, according to their characteristics in order to calculate the fuel consumptions, the CO2 emissions and the cost. Available data have been used to derive the models that characterize the emission and cost performances of typical PC units as well as their rating and partial load performances [1]. From the results of the multi-objective optimization, the so called Pareto Optimal Frontiers (POFs) are used to evaluate the effect of CO2 tax on the optimal power dispatching solutions. The influence of SO2 tax on the CO2 abatement marginal cost is also analyzed.

scholarly journals Power Loss Calculation in 11-Level Cascaded H-Bridge Inverter using Harmony Search Optimized Switching Scheme

2019 ◽  
Vol 8 (6) ◽  
pp. 5200-5205
Keyword(s):  
Optimization Algorithm ◽  
Power Loss ◽  
System Analysis ◽  
Search Algorithm ◽  
Optimization Technique ◽  
Harmony Search ◽  
Multilevel Inverter ◽  
Total Power ◽  
Multi Objective Optimization ◽  
Multi Objective

Power loss is the most significant parameter in power system analysis and its adequate calculation directly effects the economic and technical evaluation. This paper aims to propose a multi-objective optimization algorithm which optimizes dc source magnitudes and switching angles to yield minimum THD in cascaded multilevel inverters. The optimization algorithm uses metaheuristic approach, namely Harmony Search algorithm. The effectiveness of the multi-objective algorithm has been tested with 11-level Cascaded H-Bridge Inverter with optimized DC voltage sources using MATLAB/Simulink. As the main objective of this research paper is to analyze total power loss, calculations of power loss are simplified using approximation of curves from datasheet values and experimental measurements. The simulation results, obtained using multi-objective optimization method, have been compared with basic SPWM, optimal minimization of THD, and it is confirmed that the multilevel inverter fired using multi- objective optimization technique has reduced power loss and minimum THD for a wide operating range of multilevel inverter.

scholarly journals Multi-objective optimization of solar thermal photovoltaic hybrid power generation system based on NSGA-II algorithm

2021 ◽  
Vol 336 ◽  
pp. 02022
Author(s):  
Liang Meng ◽  
Wen Zhou ◽  
Yang Li ◽  
Zhibin Liu ◽  
Yajing Liu
Keyword(s):  
Power Generation ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Solar Thermal ◽  
Multi Objective Optimization ◽  
Generation System ◽  
Nsga Ii ◽  
Multi Objective ◽  
Hybrid Power ◽  
Power Generation System

In this paper, NSGA-Ⅱ is used to realize the dual-objective optimization and three-objective optimization of the solar-thermal photovoltaic hybrid power generation system; Compared with the optimal solution set of three-objective optimization, optimization based on technical and economic evaluation indicators belongs to the category of multi-objective optimization. It can be considered that NSGA-Ⅱ is very suitable for multi-objective optimization of solar-thermal photovoltaic hybrid power generation system and other similar multi-objective optimization problems.

scholarly journals Multi-Objective Joint Optimal Operation of Reservoir System and Analysis of Objectives Competition Mechanism: A Case Study in the Upper Reach of the Yangtze River

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2542 ◽  
Author(s):  
Mufeng Chen ◽  
Zengchuan Dong ◽  
Wenhao Jia ◽  
Xiaokuan Ni ◽  
Hongyi Yao
Keyword(s):  
Power Generation ◽  
Water Supply ◽  
Yangtze River ◽  
Water Resource Management ◽  
Flood Control ◽  
Optimal Operation ◽  
Total Power ◽  
The Yangtze River ◽  
Multi Objective ◽  
Reservoir System

The multi-objective optimal operation and the joint scheduling of giant-scale reservoir systems are of great significance for water resource management; the interactions and mechanisms between the objectives are the key points. Taking the reservoir system composed of 30 reservoirs in the upper reaches of the Yangtze River as the research object, this paper constructs a multi-objective optimal operation model integrating four objectives of power generation, ecology, water supply, and shipping under the constraints of flood control to analyze the inside interaction mechanisms among the objectives. The results are as follows. (1) Compared with single power generation optimization, multi-objective optimization improves the benefits of the system. The total power generation is reduced by only 4.09% at most, but the water supply, ecology, and shipping targets are increased by 98.52%, 35.09%, and 100% at most under different inflow conditions, respectively. (2) The competition between power generation and the other targets is the most obvious; the relationship between water supply and ecology depends on the magnitude of flow required by the control section for both targets, and the restriction effect of the shipping target is limited. (3) Joint operation has greatly increased the overall benefits. Compared with the separate operation of each basin, the benefits of power generation, water supply, ecology, and shipping increased by 5.50%, 45.99%, 98.49%, and 100.00% respectively in the equilibrium scheme. This study provides a widely used method to analyze the multi-objective relationship mechanism, and can be used to guide the actual scheduling rules.

scholarly journals Multi-Objective Optimal Operations Based on Improved NSGA-II for Hanjiang to Wei River Water Diversion Project, China

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1159 ◽  
Author(s):  
Lianzhou Wu ◽  
Tao Bai ◽  
Qiang Huang ◽  
Jian Wei ◽  
Xia Liu
Keyword(s):  
Power Generation ◽  
Search Space ◽  
Water Transfer ◽  
Water Diversion ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Water Diversion Project ◽  
Basin Water ◽  
Wei River

It is important to investigate the laws of reservoir multi-objective optimization operations, because it can obtain the best benefits from inter-basin water transfer projects to mitigate water shortage in intake areas. Given the multifaceted demands of the Hanjiang to Wei River Water Diversion Project, China (referred hereafter as “the Project”), an easy-to-operate multi-objective optimal model based on simulation is built and applied to search the multi-objective optimization operation rules between power generation and energy consumption. The Project includes two reservoirs connected by a water transfer tunnel. One is Huangjinxia, located in the mainstream of Hanjiang with abundant inflow but no regulation ability, and the other is Sanhekou, located in the tributary of Hanjiang with multi-year regulation ability but less water. The layout of the Project increases the difficulty of reservoir joint optimization operations. Therefore, an improved Non-dominated Sorting Genetic Algorithm-II (I-NSGA-II) with a feasible search space is proposed to solve the model based on long-term series data. The results show that: (1) The validated simulation model is helpful to obtain Pareto front curves to reveal the rules between power generation and energy consumption. (2) Choosing a reasonable search step size to build a feasible search space based on simulation results for the I-NSGA-II can help find more optimized solutions. Considering the influence of the initial populations of the algorithm and limited computing ability of computers, the qualified rate of Pareto points solved by I-NSGA-II are superior to NSGA-II. (3) According to the characteristics of the Project, water transfer ratio threshold value of two reservoirs are quantified for maximize economic benefits. Moreover, the flood season is a critical operation period for the Project, in which both reservoirs should supply more water to intake areas to ensure the energy balanced of the entire system. The findings provide an easy-to-operate multi-objective operation model with the I-NSGA-II that can easily be applied in optimal management of inter-basin water transfer projects by relevant authorities.

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