Abstract
Around the world, countries are integrating photovoltaic generating systems to the grid to support climate change initiatives. However, solar power generation is highly uncertain due to variations in solar irradiance level during different hours of the day. Inaccurate modelling of this variability can lead to non-optimal dispatch of system resources. Therefore, accurate characterization of solar irradiance patterns is essential for effective management of renewable energy resources in an electrical power grid. In this paper, the Weibull distribution based probabilistic model is presented for characterization of solar irradiance patterns. Firstly, Weibull distribution is utilized to model inter-temporal variations associated with reference solar irradiance data through moving window averaging technique, and then the proposed model is used for irradiance pattern generation. To achieve continuity of discrete Weibull distribution parameters calculated at different steps of moving window, Generalized Regression Neural Network (GRNN) is employed. Goodness of Fit (GOF) techniques are used to calculate the error between mean and standard deviation of generated and reference patterns. The comparison of GOF results with the literature shows that the proposed model has improved performance. The presented model can be used for power system planning studies where the uncertainty of different resources such as generation, load, network, etc., needs to be considered for their better management.
Highlights
Environmental and cost concerns associated with fossil fuels have tracked the attention of relevant stakeholders on green energy resources to achieve sustainable and green policy objectives
Solar energy is a promising Renewable Energy Resource (RER) and an economical alternative to fossil fuels that can play a critical role in achieving green policy objectives and resolving energy crisis issues [1]
Further expansion is possible if governments and policy makers announce more incentives on the purchase of solar panels [5] and related auxiliaries such as power electronic converters and energy storages, etc., for their effective utilization [6]
Summary
Energy has become part and parcel of our daily life and the dream of a sustainable society is unrealizable without sustainable energy solutions. Higher Education Institutes (HEIs) can play a significant role in this regard by motivating large segments of society towards decarbonization objectives [7] Another strategy to engage consumers in green energy programs is to declare a penalty cost for CO2 emissions and a continuous increment in its value with the passage of time to achieve goals targeted in various environmental protocols signed by the international stakeholders [8]. Probabilistic modelling and characterization of solar irradiance can help to manage many challenges associated with the uncertain varying nature of grid connected PV systems It extracts useful information from the irradiance data and can be used as a supporting tool in the decision making process [17]
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