Published October 2015 | Version v1
Journal article

A new method to adequate assessment of wind farms' power output

Description

Highlights: • A probabilistic method is presented to model wind farm's power output. • This method uses real data involving wind speed and wind turbine's power output. • Power probability distribution functions are used to model wind turbine's power. • Statistical spatial distribution of wind speed over wind farm is considered. - Abstract: This paper presents a novel probabilistic technique so as to estimate the power output of wind farms (WFs). At first, the power output of each wind turbine (WT) is calculated using power probability distribution functions (PPDFs). These PPDFs are acquired from the actual data of an installed WT measured in a particular time horizon, which involves WT's wind speed and its corresponding power output. In the next step, using the calculated PPDFs and assigning Poisson distribution as statistical spatial distribution for wind speed over the WF, the power output of WF is computed in a probabilistic manner. It has been demonstrated that the probability distribution function (PDF) of a WF's power output as well as its capacity factor (CF) can be calculated accurately utilizing the proposed approach. The outcome could have a substantial effect on conducting several power system studies such as reliability evaluation, power system expansion planning and so on. To verify the outperformance of the proposed method, the actual measured data of Manjil WF in Iran has been used as a real case study. The obtained results confirm the accuracy of the proposed method as a more precise approach compared to the conventional ones

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enconman.2015.07.001

Additional details

Identifiers

DOI
10.1016/j.enconman.2015.07.001;
PII
S0196-8904(15)00652-4;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
103
Journal Page Range
p. 585-604
ISSN
0196-8904
CODEN
ECMADL

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
47019065
Subject category
S29: ENERGY PLANNING, POLICY AND ECONOMY;
Descriptors DEI
DISTRIBUTION FUNCTIONS; PLANNING; POWER SYSTEMS; PROBABILISTIC ESTIMATION; PROBABILITY; RELIABILITY; SPATIAL DISTRIBUTION; WIND TURBINE ARRAYS; WIND TURBINES
Descriptors DEC
CALCULATION METHODS; DISTRIBUTION; ENERGY SYSTEMS; EQUIPMENT; FUNCTIONS; MACHINERY; TURBINES; TURBOMACHINERY

Optional Information

Copyright
Copyright (c) 2015 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.