Measured and forecasted weather and power dataset for management of an island and grid-connected microgrid

Silva, Danilo P. e; Salles, José Leandro Félix; Fardin, Jussara Farias; Pereira, Maxsuel M. Rocha; Ottz, Vinícius C.; Silva, Flavio Barcelos Braz Da; Pignaton, Eduardo Godoy

doi:10.1016/j.dib.2021.107513

Cited by 8 publications

(4 citation statements)

References 9 publications

(24 reference statements)

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“…The Human Development Index-Longevity (HDI-L) is 0.773, one of the highest in the metropolitan region [ 17 ]. The average temperature of the region is 26.58 °C, with fluctuations through the year [ 18 ]. In Natal, the humid coastal tropical climate is predominant, with an average rainfall of 1200 mm/year, and vegetation coverage of 18.01 % [ 16 ].…”

Section: Methodsmentioning

confidence: 99%

Epidemiological study in Brazil: Scorpion sting cases in Natal, Rio Grande do Norte

Araújo,

Torres-Rêgo,

Gurgel-Medeiros

et al. 2024

Heliyon

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Section: Methodsmentioning

confidence: 99%

Epidemiological study in Brazil: Scorpion sting cases in Natal, Rio Grande do Norte

Araújo,

Torres-Rêgo,

Gurgel-Medeiros

et al. 2024

Heliyon

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“…The two most imprecise parameters are renewable energy resources [23,34] and load demand. Long-term weather forecast can help optimize the microgrid design while short-term forecast can help better manage the available energy [35,36]. The accuracy of the load profile immensely influences optimization results [33,37].…”

Section: Overall Approach and Main Parametersmentioning

confidence: 99%

Flexible Demand for Optimzed Microgrid Design and Cost

Robert¹

2023

Renewable Energy - Recent Advances

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Although access to energy has been a major enabler for the development of our civilization, more than a billion people remain without access to electricity. Recent improvements in solar technology offer a unique opportunity to achieve global electrification. However, field studies have reported number of project failures. This chapter is dedicated to project developers, engineers, academicians and policymakers, who wish to contribute to rural development. In the first part, it recalls some important features of a well-thought rural electrification project, while proposing to involve students to liaise with local population. In a second part, it presents an original approach for achieving lowest cost solar microgrid design considering the random nature of solar energy and the users’ willingness to be flexible in their consumption. The inconvenience (loss of utility) for users has been modeled and the results suggest that rural users are likely to adapt their consumption to the availability of solar energy to reduce their electricity bill. Such a conclusion is likely to apply to interconnected power grid as renewable energy becomes more and more prominent in the energy mix and energy storage remains a costly challenge.

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“…Wind sensor ▪ Measurement of wind speed and direction to predict the potential wind power in a plant [279] Power meter ▪ Measuring real power and calculation of the estimated wind power [280] Weather sensor ▪ Measuring temperature and pressure to enhance prediction model [281] Turbine sensor ▪ To acknowledge blade pitch angle and turbulence intensity in a wind turbine [282] Anemometer ▪ A measurement instrument to gather wind information [283] Software and control Input data evaluation ▪ Classification of data obtained from measurement sensors [133] Weather prediction algorithm ▪ To predict current and future weather conditions (i.e., wind speed, temperature, pressure, air density, etc.) [134] Output power estimation ▪ To calculate the possible power generation amount of the wind turbine [135] Communication protocols TCP/IP ▪ To transfer the measured and calculated data through internet [140] WAP ▪ Performing wireless communication to provide achievement to the data from a personal computer [141] SMTP ▪ Enabling the transfer of the measured data via an electronic mail [142] HTTP ▪ An application layer in TCP/IP protocol for the data transfer [143] standards.…”

Section: Measurementmentioning

confidence: 99%

A Review on Wind Power Forecasting Regarding Impacts on the System Operation, Technical Challenges, and Applications

et al. 2022

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Wind energy generation is a fast developing efficient renewable source widely used for modern power generation. [1] Countries and energy companies have increased their interest in electricity generation from wind energy in the last decades, thanks to its natural, cost-free, and environmentally friendly features. [2] Wind power plants can generate electrical energy at any time of the day and are distributed energy sources for systems that need permanent energy. [3] Nonetheless, due to the disordered nature of the earth's atmosphere, there is a major uncertainty in the electrical power produced by the wind, which causes complexities in the utilization and management of wind energy sources. [4] The changes in weather conditions depending on time and location also create uncertainty in managing the supply-demand balance controlled by the grid operators. [5] In cases where the electrical energy produced by wind power plants is insufficient, auxiliary energy sources provide operational support to the electric grid. [6] Ensuring the supply-demand balance in the electricity grid is also an important condition for the electrical power quality and energy supply in the transmission system, and wind power plant operators care about the follow-up of wind power in terms of economy, operation, and planning. [7] For this, the presence of wind power forecasting (WPF) is an essential factor in the optimization of wind power plants. [8] For consumers to use electrical energy uninterruptedly, efficiently, and economically, wind power plant operators need to estimate the generated electrical energy smoothly. [9] The smooth estimation of electrical power generated by wind turbines increases the operational efficiency for system maintenance, planning, investment, and energy traders. [10,11] It is a precious procedure for electrical grids to provide a respectable commercial yield on the electrical energy market. [12] The capability of advanced WPF provides the contributions like balancing the power system and mitigation of penalties, scheduling the maintenance of wind power plants, investment regarding site location, and technoeconomic and socioeconomic benefits. [13,14] In this way, it is possible to reduce the energy cost and obtain high revenue in the energy market as a result of the contributions obtained for wind power generation systems. [15]

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Measured and forecasted weather and power dataset for management of an island and grid-connected microgrid

Cited by 8 publications

References 9 publications

Epidemiological study in Brazil: Scorpion sting cases in Natal, Rio Grande do Norte

Epidemiological study in Brazil: Scorpion sting cases in Natal, Rio Grande do Norte

Flexible Demand for Optimzed Microgrid Design and Cost

A Review on Wind Power Forecasting Regarding Impacts on the System Operation, Technical Challenges, and Applications

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