http://hdl.handle.net/10174/917 2026-04-03T19:09:21Z 2026-04-03T19:09:21Z Mesbahi, Oumaima Kandoussi, Khalid El otmani, Rabie Hajjaji, Abdeloawahed Janeiro, Fernando M. Tlemçani, Mouhaydine http://hdl.handle.net/10174/30664 2026-02-20T12:25:36Z 2020-11-01T00:00:00Z

Title: Global MPP Tracking for Photovoltaic Panel under Shading Conditions using Robust Numerical Algorithm Authors: Mesbahi, Oumaima; Kandoussi, Khalid; El otmani, Rabie; Hajjaji, Abdeloawahed; Janeiro, Fernando M.; Tlemçani, Mouhaydine Abstract: This paper presents a new numerical approach for the modelling of the PV panels under partial shading conditions. It also solves the major drawback of the PV systems, which is the tracking of maximum power point under partial shading conditions where the P-V characteristic has a more complex structure with many local maximums on the graph. This paper aims to resolve this phenomenon using Newton method in order to find the global maximum power point.

2020-11-01T00:00:00Z Mesbahi, Oumaima Kandoussi, Khalid El otmani, Rabie Hajjaji, Abdeloawahed Janeiro, Fernando M. Tlemçani, Mouhaydine http://hdl.handle.net/10174/30664 2026-02-20T12:25:36Z 2020-11-01T00:00:00Z

Title: Global MPP Tracking for Photovoltaic Panel under Shading Conditions using Robust Numerical Algorithm Authors: Mesbahi, Oumaima; Kandoussi, Khalid; El otmani, Rabie; Hajjaji, Abdeloawahed; Janeiro, Fernando M.; Tlemçani, Mouhaydine Abstract: This paper presents a new numerical approach for the modelling of the PV panels under partial shading conditions. It also solves the major drawback of the PV systems, which is the tracking of maximum power point under partial shading conditions where the P-V characteristic has a more complex structure with many local maximums on the graph. This paper aims to resolve this phenomenon using Newton method in order to find the global maximum power point.

2020-11-01T00:00:00Z Rodrigues, Nuno M. Carvalho, João P. Janeiro, Fernando M. Ramos, Pedro M. http://hdl.handle.net/10174/30663 2022-01-07T22:18:55Z 2020-05-31T23:00:00Z

Title: Electrical Power Grid Frequency Estimation with Fuzzy Boolean Nets Authors: Rodrigues, Nuno M.; Carvalho, João P.; Janeiro, Fernando M.; Ramos, Pedro M. Abstract: Power quality analysis involves the measurement of quantities that characterize a power supply waveform such as its frequency. The measurement of those quantities are regulated by internationally accepted standards from IEEE or IEC. Monitoring the delivered power quality is even more important due to recent advances in power electronics and also due to the increasing penetration of renewable energies in the electrical power grid. The primary suggested method by IEC to measure the power grid frequency is to count the number of zero crossings in the voltage waveform that occur during 0.2 s. The standard zero crossing method is usually applied to a filtered signal that has a non deterministic and frequency dependent delay. For monitoring the power grid a range between 42.5 and 57.5 Hz should be considered which means that the filter must be designed in order to attenuate the delay compensation error. Fuzzy Boolean Nets can be considered a neural fuzzy model where the fuzziness is an inherent emerging property that can ignore some outliers acting as a filter. This property can be useful to apply zero crossing without false crossing detection and estimate the real timestamp without the non deterministic delay concern. This paper presents a comparison between the standard frequency estimation, a Goertzel interpolation method, and the standard method applied after a FBN network instead of a filtered signal.

2020-05-31T23:00:00Z Rodrigues, Nuno M. Carvalho, João P. Janeiro, Fernando M. Ramos, Pedro M. http://hdl.handle.net/10174/30663 2022-01-07T22:18:55Z 2020-05-31T23:00:00Z

Title: Electrical Power Grid Frequency Estimation with Fuzzy Boolean Nets Authors: Rodrigues, Nuno M.; Carvalho, João P.; Janeiro, Fernando M.; Ramos, Pedro M. Abstract: Power quality analysis involves the measurement of quantities that characterize a power supply waveform such as its frequency. The measurement of those quantities are regulated by internationally accepted standards from IEEE or IEC. Monitoring the delivered power quality is even more important due to recent advances in power electronics and also due to the increasing penetration of renewable energies in the electrical power grid. The primary suggested method by IEC to measure the power grid frequency is to count the number of zero crossings in the voltage waveform that occur during 0.2 s. The standard zero crossing method is usually applied to a filtered signal that has a non deterministic and frequency dependent delay. For monitoring the power grid a range between 42.5 and 57.5 Hz should be considered which means that the filter must be designed in order to attenuate the delay compensation error. Fuzzy Boolean Nets can be considered a neural fuzzy model where the fuzziness is an inherent emerging property that can ignore some outliers acting as a filter. This property can be useful to apply zero crossing without false crossing detection and estimate the real timestamp without the non deterministic delay concern. This paper presents a comparison between the standard frequency estimation, a Goertzel interpolation method, and the standard method applied after a FBN network instead of a filtered signal.

2020-05-31T23:00:00Z