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%