https://orcid.org/0000-0002-2813-6976
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ABSTRACT
This manuscript deals with the energy storage technology with renewable energy design can directly reduce the overall constraint of electrical micro grid in upcoming power grids. The original energy monitoring arrangement can lower the typical price of micro grids and increase the utilization of renewable assets by targeting the entire site for essential energy storage systems to predefined functions. The limited progress of solar PV and wind turbines with nickel-cadmium battery storage integrates with the sum of increasing renewable systems, for this concept the hybrid integrated micro grids can be fundamentally modeled and calculated. The proposed hybrid micro grid system gives a photovoltaic output power of 37 kW, the developed output voltage is 80 V and the power of the wind module is 900 watts, the output power of the PV panel is 420 watts. The developed output voltage is 80 V. The convex coding system is used for schema planning and optimization route. The nominal time-optimal controller and receiver locations are simply well known by this planned convex programming method. An optimization algorithm was functional to define the optimal sizing of the PV/wind/battery hybrid system for power continuity in rural areas for continuity of electricity consumption.
Highlights
The proposed hybrid micro grid system gives a photovoltaic output power of 37 kW.
The output power of the wind module is 900 watts.
An optimization algorithm was functional to define the optimal sizing of the PV/wind/battery hybrid system.
The renewable resources for the applications of power continuity in rural areas for more than 10 h of electricity generation.
List of abbreviations including units and nomenclature
| PV | = | Photovoltaic |
| WT | = | Wind Turbine |
| AC | = | Alternating Current |
| DC | = | Direct Current |
| PWM | = | Pulse Width Modulation |
| PMSG | = | Permanent Magnet Synchronous Generator |
| PAR | = | Peak to Average Ratio |
| ECS | = | Energy Controlling Strategy |
| ESS | = | Energy Storage System |
| MPPT | = | Maximum Power Point Tracking |
| BES | = | Battery Energy Storage |
| MOSFET | = | Metal Oxide Field Effect Transistor |
| λPV | = | Capital cost of the photovoltaic |
| APV | = | Area of the Photovoltaic |
| Cpv,Wt | = | Capital cost of Photovoltaic and Windturbine |
| V | = | Voltage |
| A,b | = | Convex Variables |
| SOC | = | State of Charge |
| HHO | = | Harris Hawks Optimizer |
| AEFA | = | Artificial electric field |
| GWA | = | grey wolf optimizer |
| PEM | = | Point Estimate Method |
| DG | = | Distributed Generators |
| POCF | = | probabilistic-optimal control flow problem |
| PLL | = | Phase locked loop |
| ia,ib,ic | = | The inverter output currents from three phases |
| d-q | = | Reference frame Voltages and Currents |
| EPV | = | Energy From the photovoltaic |
| Ah | = | Ampere hours |
| ANFIS | = | Adaptive Neuro Fuzzy Interface System |
| VIF | = | Variance Inflation Factor |
| NGC | = | Net Generation Cost |
| NE | = | Net Emission |
| Cp | = | Correlation Matrix |
Acknowledgments
The authors would like to acknowledge Mr. Ian Thomas for kindly making the manuscript more readable.
Disclosure statement
This manuscript has not been submitted to, nor is under review at, another journal or other publishing venue.