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Optimal development of location and technology independent machine learning photovoltaic performance predictive models
(2019)
Photovoltaic (PV) power prediction is important for monitoring the performance of PV plants. The scope of this work is to develop a methodology for deriving an optimized location and technology independent machine learning ...
Intra-day Solar Irradiance Forecasting Based on Artificial Neural Networks
(2019)
Accurate solar irradiance forecasting is important for improving forecasting precision of photovoltaic (PV) power. In this study, an intra-day (i.e. 1 to 6 hours ahead) machine learning model based on an artificial neural ...
Enhanced Frequency Response of Inverter Dominated Low Inertia Power Systems
(2019)
This paper addresses the problem of frequency stability of power systems highly penetrated by distributed energy resources interfaced through power electronics inverters. The integration of asynchronously connected generation ...
Analysis of ‘Increase Self-Consumption’ Battery Energy Storage System Use - A Residential Case Study in Cyprus
(2019)
This paper presents the case of the first grid-connected Battery Energy Storage System (BESS) in Cyprus, integrated with a residential rooftop photovoltaic (PV) system. The BESS assists in increasing the household's ...
Architectural Design of Decentralized Demand Response with Integrated Peer-to-Peer Technology
(2019)
Increasing development of the electrical smart grid technology offers exceptional opportunities for more complex electrical supply and demand interactions in a relationship that has been historically unilateral. The smart ...
Shunt Resistance Relation to Power Loss due to Potential Induced Degradation in Crystalline Photovoltaic Cells
(2019)
Potential Induced Degradation (PID) is expected to become more frequent with the increased system voltage of photovoltaic (PV) systems. Thus, a PID detection method is required to detect PID at an early stage in order to ...