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-This paper proposes probabilistic reliability evaluation model of power system considering Wind Turbine Generator(WTG) integrated with Energy Storage System(ESS). Monte carlo sample state duration simulation method is used for the evaluation. Because the power output from WTG units usually fluctuates randomly, the power cannot be counted on to continuously satisfy the system load. Although the power output at any time is not controllable, the power output can be utilized by ESS. The ESS may make to smooth the fluctuation of the WTG power output. The detail process of power system reliability evaluation considering ESS cooperated WTG is presented using case study of Jeju island power system in the paper.

A Ti-Ni alloy compositionally graded along the thickness direction in order to obtain a shape change over a wide temperature range, which is beneficial to the actuator for precise position control, was prepared by spark plasma sintering (SPS) after stacking Ti-Ni alloy ribbons in the sequence of Ti-51Ni, Ti-50Ni, Ti-49Ni and Ti-48Ni (at%) followed by annealing. Then, the microstructure and martensitic transformation behavior were investigated by using FE-SEM, DSC and thermal cycling tests under a constant load. The inter-ribbon defects observed after SPS due to insufficient diffusional bonding between the ribbons were eliminated by post-SPS annealing at 1023 K for 36 ks. The compositionally graded sample showed compositional variation of 1.5 at% Ti along the thickness direction (- 120 μm) and a martensitic transformation temperature window as large as 91 K on cooling and 79 K on heating. A recoverable elongation of 0.9% was obtained under a stress of 80 MPa and the deformation rate, which is defined as the ratio of the recoverable elongation to the temperature range where the elongation occurred was 0.015%/K in the compositionally graded sample.

This paper proposes a probabilistic generation assessment model of renewable energy generators(REGs) considering uncertainty of resources, mainly focused on Wind Turbine Generator(WTG) and Solar Cell Generator(SCG) which are dispersed widely in South Korea The proposed numerical analysis method assesses the one day-ahead generation by combining equivalent generation characteristics function and probabilistic distribution function of wind speed(WS) and solar radiation(SR) resources. The equivalent generation functions(EGFs) of the wind and solar farms are established by grouping a lot of the farms appropriately centered on Weather Measurement Station(WMS). First, the EGFs are assessed by using regression analysis method based on typical least square method from the recorded actual generation data and historical resources(WS and SR). Second, the generation of the REGs is assessed by adding the one day-ahead resources forecast, announced by WMS, to the EGFs which are formulated as third order degree polynomials using the regression analysis. Third, a Renewable Energy Generation Assessment System(REGAS) including D/B of recorded actual generation data and historical resources is developed using the model and algorithm predicting one day-ahead power output of renewable energy generators.