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With the increasing permeability of photovoltaic (PV) power production, the uncertainties and randomness of PV power have played a critical role in the operation and dispatch of the power grid and amplified the abandon rate of PV power. Consequently, the accuracy of PV power forecast urgently needs to be improved. Based on the amplitude and fluctuation characteristics of the PV power forecast error, a short-term PV output forecast method that considers the error calibration is proposed. Firstly, typical climate categories are defined to classify the historical PV power data. On the one hand, due to the non-negligible diversity of error amplitudes in different categories, the probability density distributions of relative error (RE) are generated for each category. Distribution fitting is performed to simulate probability density function (PDF) curves, and the RE samples are drawn from the fitted curves to obtain the sampling values of the RE. On the other hand, based on the fluctuation characteristic of RE, the recent RE data are utilized to analyze the error fluctuation conditions of the forecast points so as to obtain the compensation values of the RE. The compensation values are adopted to sequence the sampling values by choosing the sampling values closest to the compensation ones to be the fitted values of the RE. On this basis, the fitted values of the RE are employed to correct the forecast values of PV power and improve the forecast accuracy. [ABSTRACT FROM AUTHOR]

This paper presents a techno-economic assessment of the wind power potential for eight locations distributed over the Northern part of Cyprus. The wind speed data were collected from the meteorological department located in Lefkoşa, Northern Cyprus.Ten distribution models were used to analyze the wind speed characteristics and wind energy potential at the selected locations. The maximum-likelihood method was used for calculating the parameters of the distribution functions.The power law model is utilized to determine the mean wind speed at various heights. In addition, the wind power density for each location was estimated. Furthermore, the performances of different small-scale vertical axis 3–10 kW wind turbines were evaluated to find those that were suitable and efficient for power generation in the studied locations.The results showed that the annual mean wind speed in the regions is greater than 2 m/s at a height of 10 m. Moreover, it is indicated that Generalized Extreme Value distribution provided the best fit to the actual data for the regions of Lefkoşa, Ercan, Girne, Güzelyurt, and Dipkarpaz. However, the Log-Logistic, Weibull, and Gamma distributions gave a better fit to the actual data of Gazimağusa, YeniBoğaziçi, and Salamis, respectively. The Rayleigh distribution does not fit the actual data from all regions. Furthermore, the values of wind power densityat the areas studied ranged from 38.76 W/m2 to 134.29 W/m2 at a height of 50 m, which indicated that wind energy sources in these selected locations are classified as poor. Meanwhile, based on the wind analysis, small-scale wind turbine use can be suitable for generating electricity in the studied locations. Consequently, an Aeolos-V2 with a rating of 5 kW was found to be capable of producing the annual energy needs of an average household in Northern Cyprus. [ABSTRACT FROM AUTHOR]