AHREPS - Alternating Hybrid Renewable Energy Power System for Load Prioritization: A Case Study of Otokwu-Mmaku Community, Awgu, Enugu State, Nigeria
Anikpo Chukwuka Ekene,
Ogbonna Bartholomew Odinaka
Issue:
Volume 12, Issue 2, March 2023
Pages:
24-31
Received:
13 March 2023
Accepted:
21 April 2023
Published:
10 May 2023
Abstract: This paper presents the results of a research study using a novel Binary Data Driven Programming (BDDP) solution coined AHREPS (Alternating Hybrid Renewable Energy Power Systems) to alternate between a Solar Photovoltaic (Solar PV) Renewable Energy (RE) system and a Wind Turbine (WT) Renewable Energy system to provide continuous power supply in a rural-to-suburban household at Otokwu Mmaku Community, Awgu, Enugu State, Nigeria. The computational model for the Otokwu-Mmaku Solar PV (OMPV) and Otokwu-Mmaku Wind Turbine (OMWT) hybrid renewable energy (RE) systems are data-driven by a synthesis of data from simple function-fitted models to a generalized polynomial of order-1 for a 4-year duration (2018 to 2021). The results considering an average baseline load of 0.9kWh/day showed that using a 3-parallel connected 200W Solar PV modules and 5kW Wind turbine modules; the AHREPS employed the OMPV RE system for the months of January through June and the months of September through December all through the 4-year duration (2018-2021) but in the months of July (2021) and August (2020), the AHREPS employed the OMWT RE system in providing continuous power supply for the estimated load. This clearly shows that considering the model selection and alternating effects of the hybrid RE systems, the proposed AHREPS model can effectively meet the expected load demand of the aforementioned location.
Abstract: This paper presents the results of a research study using a novel Binary Data Driven Programming (BDDP) solution coined AHREPS (Alternating Hybrid Renewable Energy Power Systems) to alternate between a Solar Photovoltaic (Solar PV) Renewable Energy (RE) system and a Wind Turbine (WT) Renewable Energy system to provide continuous power supply in a r...
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Adaptive LMS MPPT Controller and Adaptive Inverter Control Law to Control the Solar Photovoltaic System
Nalini Karchi,
Deepak Kulkarni
Issue:
Volume 12, Issue 2, March 2023
Pages:
32-39
Received:
17 August 2022
Accepted:
16 September 2022
Published:
5 June 2023
Abstract: The objective of the proposed work is to develop the maximum power point tracking controller and inverter controller by applying the adaptive Least mean square algorithm to control the total harmonics distortion of a solar photovoltaic system. The advantage of the adaptive LMS algorithm is simple and required less computational time. The adaptive LMS algorithm is applied to modify the perturbation and observation, maximum power point tracking controller. In this controller, the adaptive LMS algorithm is used to predict solar photovoltaic power. The development of the inverter control law is done using the d-q frame theory. This helps to reduce the number of equations to build a control law. The load current, grid current and grid voltage are sensed and transformed into d and q components. This adaptive LMS control law is used to extract the reference grid currents and later compared them to the actual grid currents. The comparison result is used to generate the switching gate pulses for inverter switches. The proposed controllers are developed and implemented with a solar PV system in MATLAB Simulink. The total harmonics distortion in current and voltage is investigated under linear and non-linear load conditions with changes in solar irradiations. The analysis is done by selecting step incremental values and sampling time.
Abstract: The objective of the proposed work is to develop the maximum power point tracking controller and inverter controller by applying the adaptive Least mean square algorithm to control the total harmonics distortion of a solar photovoltaic system. The advantage of the adaptive LMS algorithm is simple and required less computational time. The adaptive L...
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