Hybrid Renewable Energy Generation Through Incremental Conductance Mppt

The relevance of electricity generation from renewable energy sources is growing every day in the current global energy environment. The scarcity of fossil fuels and the environmental risks connected with traditional power producing methods are the main reasons behind this. The major sources of non-conventional energy are wind and solar which can be harnessed easily. A new system design for hybrid photovoltaic and wind-power generation is introduced within this study. A Modified M.P.P.T. has been proposed to strengthen productivity of this system. The proposed approach employs the Incremental Conductance (IC) MPPT technique. Under varied climatic conditions (Solar irradiance & Temperature), IC is utilized to determine the optimum voltage output of a photo voltaic generator (P.V.G.) within the photo voltaic system (P.V.) structure. The Incremental Conductance is utilized to manage the converter’s technology having boosting function. The P.M.S.G. is used to determine the maximum voltage output for varied wind flow rates in wind turbine system. Simulations are conducted in Matlab2019b to test efficacy of the proposed MPPT. The proposed scheme’s effectiveness can be supported with simulation results.

Hybrid Renewable Energy Generation Through Incremental Conductance Mppt

The relevance of electricity generation from renewable energy sources is growing every day in the current global energy environment. The scarcity of fossil fuels and the environmental risks connected with traditional power producing methods are the main reasons behind this. The major sources of non-conventional energy are wind and solar which can be harnessed easily. A new system design for hybrid photovoltaic and wind-power generation is introduced within this study. A Modified M.P.P.T. has been proposed to strengthen productivity of this system. The proposed approach employs the Incremental Conductance (IC) MPPT technique. Under varied climatic conditions (Solar irradiance & Temperature), IC is utilized to determine the optimum voltage output of a photo voltaic generator (P.V.G.) within the photo voltaic system (P.V.) structure. The Incremental Conductance is utilized to manage the converter’s technology having boosting function. The P.M.S.G. is used to determine the maximum voltage output for varied wind flow rates in wind turbine system. Simulations are conducted in Matlab2019b to test efficacy of the proposed MPPT. The proposed scheme's effectiveness can be supported with simulation results.

Artificial Neural Network Assisted Variable Step Size Incremental Conductance MPPT Method with Adaptive Scaling Factor

In conventional adaptive variable step size (VSS) maximum power point tracking (MPPT) algorithms, a scaling factor is utilized to determine the required perturbation step. However, the performance of the adaptive VSS MPPT algorithm is essentially decided by the choice of scaling factor. In this paper, a neural network assisted variable step size (VSS) incremental conductance (IncCond) MPPT method is proposed. The proposed method utilizes a neural network to obtain an optimal scaling factor that should be used in current irradiance level for the VSS IncCond MPPT method. Only two operating points on the characteristic curve are needed to acquire the optimal scaling factor. Hence, expensive irradiance and temperature sensors are not required. By adopting a proper scaling factor, the performance of the conventional VSS IncCond method can be improved, especially under rapid varying irradiance conditions. To validate the studied algorithm, a 400 W prototyping circuit is built and experiments are carried out accordingly. Comparing with perturb and observe (P&O), α-P&O, golden section and conventional VSS IncCond MPPT methods, the proposed method can improve the tracking loss by 95.58%, 42.51%, 93.66%, and 66.14% under EN50530 testing condition, respectively.

Energy Management of a Renewable Hybrid Isolated DC Microgrid

Hybrid microgrid is the key solution to energize remote rural areas. The microgrid system incorporates more than one Distributed Renewable Energy (DRE) source to complement one another. This paper proposes a hybrid DC microgrid system to be operated in isolated mode. The proposed microgrid consists of a PMSG based Wind Turbine, PV array, and Lead-acid battery as an energy storage device. The Wind Turbine generator is connected to the DC bus through a Three-phase Diode Bridge Rectifier. The PV array is tied to the DC bus by a Boost converter and incremental conductance algorithm is used to extract the maximum power from the PV array. The battery uses a bidirectional converter for charging and discharging. A simple PI-based closed-loop control system is incorporated for proper energy management. The bus voltage is maintained either by the boost converter or the bidirectional converter depending upon the operating condition. The proposed microgrid system is modeled in MATLAB/SIMULINK software. Simulation of this model is done for varying irradiance, temperature, wind condition, and different load condition. The simulation results show that the system is stable under various load and supply conditions. Keywords: Hybrid microgrid, Distributed Renewable Energy (DRE), PMSG, PV array, DC bus, Boost converter, incremental conductance, bidirectional converter