The installation of 3 × 50 MW (150 MW DC) large utility scale solar power plant is ground based using ventilated polycrystalline module technology with fixed tilt angle of 28°in a 750-acre land, and the site is located about 115 km northeast of Karachi, Pakistan, near the town of ThanoBula Khan, Nooriabad, Sindh. This plant will be connected to the utility distribution system through a national grid of 220 kV outgoing double-loop transmission line. The 3 × 50 MW solar PV will be one of the largest tied grid-connected power projects as the site is receiving a rich average solar radiation of 158.7 kW/h/m 2 /month and an annual average temperature of about of 27°C. The analysis highlights the preliminary design of the case project such as feasibility study and PV solar design aspects and is based on a simulation study of energy yield assessment which has all been illustrated. The annual energy production and energy yield assessment values of the plant are computed using the PVSYST software. The assumptions and results of energy losses, annual performance ratio (PR) 74.73%, annual capacity factor 17.7%, and annual energy production of the plant at 232,518 MWh/year are recorded accordingly. Bear in mind that reference recorded data indicates a good agreement over the performance of the proposed PV power plant.
Access to solar energy is a prerequisite to remedy CO2 and improve the standard of human living. Green solar energy is only an immediate solution to add its zero emission profile and provide carbon footprint reduction benefits. This energy does not emit greenhouse gases which means it is a renewable free source of energy when producing electricity. The purpose of this paper is to investigate the accurate annul energy production data reducing uncertainty in solar energy estimates. This work investigated the solar energy assessment taking into account a detailed solar resource and energy production assessment for a 3 × 50 MW PV project with uncertainty analysis. The authors defined a total uncertainty of energy production which is estimated at 9.5% for one year and 8.9% for ten years as well as future variability of 3.4% for one year and 1.1% for ten years. The annual power degradation and expected energy production over the plant lifespan at dissimilar 99%, 90%, 75%, 60%, 50%, and 25% probability of surplus are also observed in this paper.
The accuracy of energy management system for renewable microgrid, either grid-connected or isolated, is heavily dependent on the forecasting precision such as wind, solar, and load. In this paper, an improved fuzzy prediction horizon forecasting method is developed to address the issue of intermittence and uncertainty problem related to renewable generation and load forecast. In the first phase, a Takagi-Sugeno type fuzzy system is trained with many evolutionary optimization algorithms and established coverage grade indicator to check the accuracy of interval forecast. Secondly, a wind, solar, and load forecaster is developed for renewable microgrid test bed which is located in Beijing, China. One day and one step ahead results for the proposed forecaster are expressed with lowest RMSE and training time. In order to check the efficiency of the proposed method, a comparison is carried out with the existing models. The fuzzy interval-based model for the microgrid test bed will help to formulate the energy management problem with more accuracy and robustness.
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