Fig。 3。 EENS increases as wind penetration and peak load increase
Addition of conventional capacity
Addition of wind capacity
2300 2400 2500 2600 2700 2800 2900 3000 3100 3200 3300
Peak load (MW)
to meet the 6% RPS target。 The method presented in this sub- section a simple and easy to use practical model that can be utilized in large system assessments。
Fig。 4。 Addition of new conventional capacity to improve system reliability
Fig。 5。 Wind penetration change along with peak load increases
Similar studies have been performed using different wind capacity factors。 The same conclusions can be made, although the results are not shown here because of space limitation。 Note that the size and FOR of the additional thermal units that are used in the earlier assessments will affect the total capacity need of additional thermal units, but the conclusion will still be valid。 In order to meet the RPS goal and to maintain the system reliability, close coordination between the developments of wind resource and conventional capacity is always needed in wind resource integration。
The additional conventional capacity causes reliability capacity cost of wind resource integration, which can only be adequately determined using the the probabilistic reliability models。 The reliability capacity cost can be obtained given the cost of additional thermal units。 This cost needs to be added with other cost in the economic assessment for wind integration。 Assuming the cost of thermal unit in this example is $0。3 million/MW, the reliability capacity cost of wind integration is shown in Fig。 6。 It can be seen that the reliability capacity cost increases quickly as peak load increases, in order
Fig。 6。 Cost of capacity addition of wind integration
F。Effect of wind capacity factor
In this sub-section, the test system is modified such that the peak load is 2850 MW。 A 570 MW wind farm is added into the system to replace 570 MW of existing generation that has higher FOR。 EENS for scenarios with different wind capacity factors are computed, as well as the need of additional conventional capacity。 The results are shown in Fig。 7, where the EENS is illustrated by wide columns and the need for additional conventional capacity is illustrated by narrow columns。 As expected, the wind farms with low capacity factor have less contribution to the system reliability than the wind farms with high capacity factor。 This is reflected in Fig。
7 that the EENS decreases when wind capacity factor increases。 It is also seen that more additional conventional capacity is needed for the wind farms with low capacity factor than the wind farms with high capacity factor。
G。Impacts of wind turbine availability
A large wind farm normally includes many energy collection facilities, e。g。 hundreds of the wind turbines in a wind farm。 This sub-section will discuss the impact of wind turbine availability on the system reliability。 The correlation of the wind turbine availability and the wind capacity factor will be analyzed。
The same modified test system as considered in sub-section
III。B is used。 Two wind turbine outage rates, 4% and 20%, are compared。 The changes of EENS that are resulted from the increase of wind turbine outage rate are shown in Fig。 8。
0% 10% 20% 30% 概率风能模型的发电系统可靠性英文文献和中文翻译(6):http://www.youerw.com/fanyi/lunwen_99770.html