AI transformation of renewable energy (Current and Future)
Artificial Intelligence (AI) plays an important role in modern industries worldwide. It transforms how we approach problem-solving and emulates human intelligence and problem-solving capabilities through machines enabling these machines to learn and improve their performance.
As the renewable energy sector grapples with challenges like unpredictable weather, high storage costs, and inefficiencies in power management, AI in renewable energy optimization is driving a green energy transition by maximizing efficiency, ensuring reliability, and paving the way for sustainable energy with AI.
AI has become essential and integrated with most daily activities, from the smallest to the self-driving car. It is also extended beyond limits and shared in energy transformation, health care, and automation and control systems.
The renewable energy sector addresses climate change and substituting traditional fossil fuels with renewable sources such as solar and wind energy. Integrating AI helps power generation, power distribution, and Energy storage systems (ESS).
AI is also used in energy management systems that control the operation of power generation systems in renewable hybrid power systems such as wind/solar systems. It enhances the system’s operation in bad weather conditions to ensure maximum efficiency.
In this article, we will discuss the current situation of renewable energy and the role that AI plays in maximizing the benefits of that sector. We will also discuss how renewable energy with AI will lead the world to a greener future.
Many challenges force renewable energy to slow down its growth. These challenges include the excessive initial cost when compared with the harnessed energy because of the physical nature of the renewable sources causing the payback time of the projects.
Renewable sources depend on natural parameters like solar and wind. So, the generated power needs to be stored and restored during the absence of these sources. That requires special and large-scale storage systems like batteries which need more cost. Adding to that, some other challenges should be addressed and considered such as shortage of knowledge, awareness, and policies.
In summary, AI plays a crucial role in renewable energy's current and future transformation. It addresses the challenges such as climate change, sustainability, and operation costs. It helps in equipment predictive maintenance, weather, and energy forecasting, and the management of hybrid power systems.
In the future, the role of AI will be maximized by utilizing advanced energy storage solutions and developing self-operation power plants. Besides renewable energy optimization, AI will share environmental awareness to ensure green energy transition.
The integration between renewable energy and AI will enable societies to adopt the technologies for a carbon-neutral future and put a road map for a global transition to a clean and sustainable energy economy.
What is the current situation of renewable energy?
Recently, as per the International Renewable Energy Agency (IRENA) report, renewable energy has encountered a significant increase in renewable energy capacity and production. The capacity increased from 1698295 (MW) in 2014 to 3864522 (MW) in 2023 globally and the production increased from 5304340 (GWH) in 2014 to 8439671 (GWH) in 2022.Many challenges force renewable energy to slow down its growth. These challenges include the excessive initial cost when compared with the harnessed energy because of the physical nature of the renewable sources causing the payback time of the projects.
Renewable sources depend on natural parameters like solar and wind. So, the generated power needs to be stored and restored during the absence of these sources. That requires special and large-scale storage systems like batteries which need more cost. Adding to that, some other challenges should be addressed and considered such as shortage of knowledge, awareness, and policies.
How is AI transforming renewable energy?
AI supports the transition of green energy, renewable energy transformation, and energy sustainability by involving AI in machines' predictive maintenance plans, energy forecasting, energy storage management, and enhancing energy management systems to improve the efficiency of renewable energy applications.1- Predictive maintenance.
AI detects the error of the machine before it happens based on the database of the machines’ conditioning monitor systems and the equipment reports. It also submits the performance and KPI of the renewable supported systems.
2- Energy forecasting.
Weather is the main factor that affects renewable energy. So, the AI’s reports for weather conditions and future forecasting predict the expected generated power from renewable energy. And prepare plans for full production time throughout the year.
3- Energy management systems.
AI optimizes the operation of renewable energy's multi systems such as hybrid power systems to enhance bad weather conditions or during the absence of these sources. It ensures the sustainability of the power generation problems by utilizing these sources.
Solar power systems, batteries, and Hydrogen fuel cells generate the electrical power needed. AI manages battery charging using surplus power from solar systems and hydrogen fuel cells, storing energy for nighttime when solar power is unavailable.
The supercapacitor's fast response efficiently manages rapid load changes. The overhaul system component and the use of AI ensure the benefits of optimum, low-cost, and efficient system operation as one of the successful hybrid renewable energy systems.
In 2021, I published a research paper about a hybrid renewable power system. The article's title is “Enhancing the operation of fuel cell-photovoltaic-battery-supercapacitor renewable system through a hybrid energy management strategy”. It details the system's operation, simulating its advantages using MATLAB.
Example of a successful hybrid renewable power system
An example of energy management is enhancing the operation of solar PV solar power and Hydrogen fuel cells as a power generation system, battery as a primary energy storage element, and supercapacitor as a second energy storage system.Solar power systems, batteries, and Hydrogen fuel cells generate the electrical power needed. AI manages battery charging using surplus power from solar systems and hydrogen fuel cells, storing energy for nighttime when solar power is unavailable.
The supercapacitor's fast response efficiently manages rapid load changes. The overhaul system component and the use of AI ensure the benefits of optimum, low-cost, and efficient system operation as one of the successful hybrid renewable energy systems.
In 2021, I published a research paper about a hybrid renewable power system. The article's title is “Enhancing the operation of fuel cell-photovoltaic-battery-supercapacitor renewable system through a hybrid energy management strategy”. It details the system's operation, simulating its advantages using MATLAB.
 |
| hybrid-power-system-diagram |
What is the future role of AI in renewable energy?
The future of renewable energy with AI is fabulously promising in dealing with the most renewable challenges (climate change and renewable energy sustainability. AI can share and transform the renewable energy strategy into 3 main cores:1- Power generation from renewable energy sources.
- AI will support weather forecasting and its integration into hybrid power systems especially solar panels and wind turbines to avoid weather challenges. It will transform the micro-grid and peer-to-peer projects to attract more people to off-grid power generation and selling.
- AI will maximize power generation by applying modern technologies to equipment fabrication. AI will increase equipment's overhaul efficiency, predict machine errors, and fix problems.
2- Sustainability of the power generated.
- AI will support renewable energy by using updated technical algorithms to enhance the storage systems and store power as much as possible with a reasonable energy capacity. it will also utilize the energy management system to control and sustain the power generation elements.
- AI will take responsibility for renewable energy power plants by applying self-operation using AI to minimize human actions and all the changes will be done automatically according to the weather and network’s actual condition.
3- Environment social impacts
AI will integrate more renewable energy with society and social activity to increase the knowledge and information about renewable energy and reduce greenhouse gases to ensure clean and green plants with minimal value of carbon emissions.In summary, AI plays a crucial role in renewable energy's current and future transformation. It addresses the challenges such as climate change, sustainability, and operation costs. It helps in equipment predictive maintenance, weather, and energy forecasting, and the management of hybrid power systems.
In the future, the role of AI will be maximized by utilizing advanced energy storage solutions and developing self-operation power plants. Besides renewable energy optimization, AI will share environmental awareness to ensure green energy transition.
The integration between renewable energy and AI will enable societies to adopt the technologies for a carbon-neutral future and put a road map for a global transition to a clean and sustainable energy economy.
No comments:
Post a Comment