Economic assessment of voltage and reactive power control provision by wind farms

Sáiz-Marín, Elena; Lobato, E.; Egido, Ignacio; Rouco, L.

doi:10.1002/we.1734

Cited by 7 publications

(8 citation statements)

References 14 publications

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“…Operating time is the time that turbines spend effectively operating for energy production, usually measured in hours per year. This time defines the amount of time the turbine will be running producing energy, and this number of hours is considered to calculate the total capacity of energy generated over a period of time 9,49,125 …”

Section: Resultsmentioning

confidence: 99%

Identification and analysis of impact factors on the economic feasibility of wind energy investments

et al. 2020

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Summary The growing energy demand in the world and the concern for environmentally damaging energy sources have led to an increased interest in seeking alternative renewable energy sources, such as wind energy. Furthermore, choosing effective locations for wind power plants has become a key issue in project planning. However, prior to implementation, such projects should be confirmed as economically viable. This article is a systematic review of the literature carried out with the aim to identify the main factors that impact the economic feasibility of wind energy investments. The search was performed in the ISI Web of Science (WoS) electronic database, from which 120 papers were extracted after a selection process, and were analyzed individually. As a result of the review analysis, 23 factors that have an impact on feasibility analysis were identified and organized in five categories: location (surface roughness, turbine location), economic (investment costs, operation and maintenance costs, avoided energy cost, depreciation, land rent), political (interest rates and taxes, energy sales price, inflation, financing conditions), climatic (wind speed, air density, temperature, air pressure), and technical (turbine height, installed wind power, lifetime, efficiency, rotor diameter, operation time, number of turbine blades, construction time). These factors can directly impact the cost of capital and/or energy production, affecting the economic viability of wind farms. In the last decade, there has been an exponential growth in publications about economic feasibility of wind investments. The wind investments growth has been accompanied by financial studies about this subject. This study provides insights on the main variables used in wind energy feasibility studies. The results may assist researchers and investors to identify the key parameters that are being examined in the literature, and to evaluate which ones should be considered in their study to ensure a sustainable development of power generation through the wind source.

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Section: Resultsmentioning

confidence: 99%

Identification and analysis of impact factors on the economic feasibility of wind energy investments

et al. 2020

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“…This condition was checked by using a factor called wind power. Wind power is actually a metric showing how much wind energy of an area can be converted into electricity (Arslan, 2010;Sáiz-Marín et al, 2014). Wind power of a given area can be calculated using its long-term meteorological data and some statistical analysis.…”

Section: Effective Criteriamentioning

confidence: 99%

Sensitivity analysis of criteria to optimize wind farm localizing: A case study

et al. 2019

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The objective of this study was to perform a sensitivity analysis on the factors affecting wind site localization. A case study is selected based on 13 cities in the province of Fars in Iran which is equally applicable in any other wind sites. Then, the cities are ranked using the dual form of the data envelopment analysis model. Next, six criteria are adopted including wind conditions, population, Available Land condition, distance to distribution networks, rate of natural disasters, and the cost of land. In the sensitivity analysis of each criterion, first, the criterion under analysis is omitted from the model, and then the dual model is applied again to obtain a new ranking. Evaluating the results of the ranking for 13 studied cities indicate that the city of Shiraz is just sensitive to the population criterion and fell 11 places in the ranking by omitting this criterion. But the city is insensitive to any other criteria.

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“…The probability of a particular reactive power setpoint will usually be site‐specific and depend on the SO reactive power management philosophy, an evaluation for one site may be found e.g. in Sáiz‐Marín et al …”

Section: Characterizing Wind Park Losses For Overall System Studiesmentioning

confidence: 99%

“…The probability of a particular reactive power setpoint will usually be site-specific and depend on the SO reactive power management philosophy, an evaluation for one site may be found e.g. in Sáiz-Marín et al 14 As next step, probability of active power operating points is evaluated: An exemplary analysis of the impact of wind speed frequency distribution on the resulting distribution of the annual average of CQ-related losses is carried out. To transform the simulated loss map into a representation in which all points have equal probability, the following steps are taken: Each of the shaft powers simulated with increments of P D 5%P n is regarded as a shaft power interval stretching from p i to p i C p. For each interval i, the corresponding wind speed interval is assessed using the exemplary power curve of Figure A2.…”

Section: Reactive Power-related Losses In the Pq-planementioning

confidence: 99%

“…Annualized assessments of cost to maintain a certain voltage profile at PCC, as carried out in Sáiz‐Marín et al ., are necessarily network dependent: Voltage varies substantially throughout the day and possibly also seasonally: The related cost will be different from WP to WP and from PCC to PCC. An annualized assessment of maximum overexcited reactive power provision as found in Zhou et al .…”

Section: Introductionmentioning

confidence: 99%

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Models of reactive power‐related wind park losses for application in power system load flow studies

Kaempf

Braun

2017

Wind Energy

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In power system load flow studies, it is common to ignore wind park (WP) losses completely, since WPs are obliged to provide reactive power as a free-of-charge ancillary service. Strongly simplified WP loss estimations are also widespread. Prevailing loss modelling approaches may result in substantial and so far usually ignored reactive power allocation inefficiencies. The innovation of this paper lies in demonstrating this and in presenting an alternative modelling approach that combines speed, ease-of-use and accuracy. Calculations are based on a generic WP connected to 110 kV. It is simulated once using gearless permanent magnet synchronous generators and once using doubly fed induction generators. In this way, for the first time, the consequences of neglecting differences between wind generator types when calculating reactive power-related losses are systematically quantified. Loss-minimal dispatch is assessed using heuristic optimal power flow. Relevance of findings is demonstrated for the application of reducing system losses based on reactive power control of WPs in closed-loop optimal power flow schemes. It is shown that non-consideration of WP losses may lead to dispatch decisions where the increase in WP losses outweighs the achieved loss reduction in the 110 kV system by 400%. The study facilitates comparing reactive power ancillary services from WPs to that of other technologies from an economic perspective. It concludes by a benchmarking overview of pros and cons of modelling alternatives

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Economic assessment of voltage and reactive power control provision by wind farms

Cited by 7 publications

References 14 publications

Identification and analysis of impact factors on the economic feasibility of wind energy investments

Identification and analysis of impact factors on the economic feasibility of wind energy investments

Sensitivity analysis of criteria to optimize wind farm localizing: A case study

Models of reactive power‐related wind park losses for application in power system load flow studies

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