曝光臺 注意防騙 網曝天貓店富美金盛家居專營店坑蒙拐騙欺詐消費者

On-line Optimization .rocess
Figure 19-8 shows how on-line systems are configured. The system gathers data in real time. The data is gathered from either the D-CS system or from the control system. Data for startups and transients are needed from the control system since the data from the D-CS is usually updated every threeto four seconds， while the control system can have very rapidloops， which are updated as often as 40 times per second. To ensure that performancedata is taken at a steady state condition， since most models of the plant aresteadystate， the system must observe some key parameters and ensure thatthey are not varying. In turbines parameters， such as turbine wheelspace， temperatures should be observed to be constant. This data is then checked for accuracy and errors removed. This involves simple checks against instru-ment operationalranges， and system operation parameter ranges. The data is then fully analyzed and various performance data checks are made. .ew operational and performance maps are then plotted and the system then can optimize itself against an operational model. The operational goalis to maximize the efficiency of the plant at allloads， thus the new perform-ancemaps， which show degradation of the plant are then used in the plant model to ensure that the control is at the right setting for the operation of the plant at any given time. Many maintenance practices are also based on the rate of economic return these operational maintenance practices such as an off-line compressor wash would contribute to the operations of the plant.
Many plants use off-line optimization. .ff-line optimization is an openloop control system. Instead of the closed loop system， which controls theplant settings， data is provided to the operator so that he can make the decisions based on the findings of the operational data. .ff-line systems are also used by engineers to design plants and by maintenance personnel to plan plant maintenance. Comparisons of the on-line systems to off-line systems can be seen in Table 19-1.
Performance evaluation is also important initially in determining that aplant meets its guarantee pointsand， subsequently， to ensure it continues to be operated at or near its design operating condition. Maintenance practices are being combined ever more closely with operational practices to ensure
Optimization Module

Process
Control

Condition Monitoring Data Evaluation System
Performance Vibration and Corrosion Analysis Control Systems of Individual Turbines

 

that plants have the highest reliability with maximum efficiency. When a newplant is built， its cost amounts to only about 7-10% of the life cycle cost. Maintenance costs represent approximately 15-20% overall.However，operating costs， which in the case of a power plant for example， consistessentially of energy costs， make up theremainder， and amount to between 70-80% of the life cycle costs of the facility. This brings performance monitoring to the forefront as an essential tool in any type of plant condition monitoring system. .perating a plant as close as possible to its design conditions will guarantee that its operating costs will be reduced. As an
Table 19-1 Comparisons of On-line and Off-line .lant Optimization System Use
On-line Systems Off-line Systems
.bjectivesMaximize economicbenefit， operate the plant at its maximum efficiency at all operation points
Target Existing operating plant
Prime use Process and maintenance operations
Users .peration and maintenance engineers
Maximize economicbenefit， operate the plant at its maximum efficiency at all operation points
.ptimize overall facilities design
and investment Existing operating plant
.ew facilities Facility expansion Process and maintenance operations Design modifications
.peration and maintenance engineers Project and design engineers
illustration of the opportunity cost this represents， large fossil power plants currently being commissioned range from 600-2800 MW. The fuel costs for these plants will amount to between US$72 million and US$168 million perannum. Therefore， savings of 1-3% of these costs can amount to an overall cost reduction of upward of US$1 million per annum.
　
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