conventional capacity may increase in order to maintain system reliability [5]。 Note that the deterministic approach is favored in calculating the operating limit and transmission capability, which are needed as input to probabilistic reliability assessments。

A new approach to reliability cost assessment is presented in this paper, which is an extension of the model developed  in [5]。 The impacts of wind resource on system reliability can be quantified by the cost of additional conventional capacity。 Several reliability modeling issues, which may affect the accuracy of probabilistic reliability assessment for wind resource integration, are investigated in this。 As an extension of [10], the impact of wind turbine  outage  on system reliability is analyzed first。 Then the correlation between the wind capacity factor and the outage rate of wind turbine is discussed。 Another modeling issue is related to the capacity of transmission system。 It is assumed that the transmission capacity has been obtained in deterministic study。 An equivalent probabilistic reliability model is developed to represent the composite system of transmission and wind generator。 Using the developed model, the impact of transmission upgrade on system reliability can be assessed when different target capacity of transmission upgrade is adopted。 The outages of transmission line and other facilities can also be incorporated into the developed model。 Based on the proposed models and methods, a framework of identifying appropriate target capacity of transmission upgrades and additional generation capacities can be developed。 The IEEE- RTS system is used to illustrate the developed probabilistic models。

II。 Modeling Wind Resources in Generation System Adequacy Evaluation

A。Reliability index, expected energy not supplied (EENS)

Different reliability indices can be used to quantify the system

where n is the number of system capacity states;

Pk   is the probability of a capacity state;

Ek  is the energy curtailed when the capacity is at state k。

EENS has energy unit, such as MWh or GWh。

B。Capacity states of a wind farm

Assuming there is no energy storage facility associated with the wind energy conversion system, the wind generation can be modeled as a conventional generation with multiple capacity states with corresponding probability reflecting the energy availability at various levels。 [7]。 The capacity states of wind generation can be sampled from historical profiles of wind generation。 The philosophy of using the historical profiles of wind generation is that both wind energy availability and wind turbine availability have been  reflected in the historical profiles。 In the absence of live data, the wind generation output is normally calculated based on the wind speed of the location where the wind turbine is installed and the wind turbine technology [8, 10 and 11]。

In a wind farm that has many wind turbines, the availability of inpidual wind turbines is another factor that may affect the output of the wind farm。 A joint capacity state method  has been developed in [8 and 9] to calculate the capacity states of wind farm considering the availability of both  wind energy and wind turbine。 This model is further employed in generation system reliability assessment for wind generation integration in [10]。 The same idea is extended in this paper to investigate the correlation of the wind turbine outage and the wind farm capacity factor。

The capacity factor of a wind farm is the ratio between the average capacity and the maximum capacity in the study period, which normally is a calendar year。 A large wind capacity factor implies that the probabilities of high wind conditions are large。 Capacity factor can be calculated as

reliability。 LOLE (Loss of Load Expectation), LOLP (Loss of Load Probability) and EENS (Expected Energy Not Supplied) have  been  widely  used  in probabilistic reliability assessment