Abstract
With diminishing fossil fuel resources and increasing environmental concerns, large-scale deployment of Renewable Energy Sources (RES) has accelerated the transition towards clean energy systems, leading to significant RES generation share in power systems worldwide. Among different RES, solar PV is receiving major focus as it is most abundant in nature compared to others, complimented by falling prices of PV technology. However, variable, intermittent and non-synchronous nature of PV power generation technology introduces several technical challenges, ranging from short-term issues, such as low inertia, frequency stability, voltage stability and small signal stability, to long-term issues, such as unit commitment and scheduling issues. Therefore, such technical issues often limit the amount of non-synchronous instantaneous power that can be securely accommodated by a grid. In this backdrop, this research work proposes a tool to estimate maximum PV penetration level that a given power system can securely accommodate for a given unit commitment interval. The proposed tool will consider voltage and frequency while estimating maximum PV power penetration of a system. The tool will be useful to a system operator in assessing grid stability and security under a given generation mix, network topology and PV penetration level. Besides estimating maximum PV penetration, the proposed tool provides useful inputs to the system operator which will allow the operator to take necessary actions to handle high PV penetration in a secure and stable manner.
Highlights
The requirement of an environmentally friendly and sustainable energy generation to meet the ever-growing global energy needs has directed focus on renewable energy sources (RES), solar PV and wind which are commercially well established and are proven technologies for clean power generation
The proposed tool is applied to IEEE 39 bus test system constructed considering detailed dynamic models of all components in DIgSILENT PowerFactory simulation platform
Extensive number of dynamic simulations are performed under various case studies and python scripts are used to automate the simulation processes
Summary
The requirement of an environmentally friendly and sustainable energy generation to meet the ever-growing global energy needs has directed focus on renewable energy sources (RES), solar PV and wind which are commercially well established and are proven technologies for clean power generation. The operation of power system worldwide is moving closer ever to their security level, primarily due to RES-driven displacement of conventional power plants. Several techniques such as maximum power point tracking algorithms, advanced tracking techniques using artificial neural networks, controllers based on adaptive neuro fuzzy interface systems, etc., have been developed for increasing power generation from solar PV power plants [4]. Higher PV penetration levels in distribution networks directly affect equipment like load tap changers, line voltage regulators and voltage controlled capacitor banks as they operate to maintain system voltages within the limits [7]
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