Novel resilient solar photovoltaic power extraction strategy for rural AC micro grids with enhanced incremental conductance based MPPT – Nature

Report on a Novel Solar Power Extraction Strategy for Rural Electrification in Alignment with Sustainable Development Goals

Abstract: Advancing SDG 7 through Enhanced Photovoltaic Efficiency

This report details the conceptualization, evaluation, and implementation of an interconnected Alternating Current (AC) grid architecture powered by solar photovoltaic (PV) energy, designed to advance rural electrification in developing nations. Central to this initiative is the promotion of Sustainable Development Goal 7 (SDG 7: Affordable and Clean Energy). A novel Maximum Power Point Tracking (MPPT) technique, the Enhanced Incremental Conductance Algorithm (EICA), is presented to maximize PV system efficiency under diverse environmental conditions. The EICA adjusts the duty cycle of a DC-DC Boost converter to prevent power divergences common in conventional methods, especially under rapidly changing irradiance. Simulation and hardware results confirm the EIC method’s superior performance. Key outcomes contributing to sustainability targets include a 22% faster convergence rate and a 15% increase in overall PV system efficiency, alongside significantly lower Total Harmonic Distortion (THD). These improvements demonstrate a viable technological pathway to providing reliable, sustainable, and modern energy for all.

1.0 Introduction: Addressing the Rural Energy Deficit through SDG 7

The global effort to achieve Sustainable Development Goal 7 (SDG 7), which advocates for “affordable, reliable, sustainable, and modern energy for all,” necessitates a focused approach on rural communities. Despite progress, a significant energy access gap persists, with 84% of the world’s unelectrified population residing in rural areas. Off-grid and micro-grid solutions are critical to bridging this divide. In India, for instance, approximately 31 million rural homes remain without electricity, characterized by several developmental challenges:

1. Extremely low household counts and population density.
2. Limited communication and transportation infrastructure.
3. Low income levels and affordability constraints.
4. Low technical proficiency and literacy rates.

Harnessing renewable energy, particularly solar PV systems, presents a powerful solution. Solar energy is a clean, limitless, and modular resource, directly supporting SDG 13 (Climate Action) by reducing carbon emissions. However, the efficiency of PV systems is a major challenge, as power output varies with temperature and irradiance. To ensure the reliability and affordability mandated by SDG 7, it is crucial to operate these systems at their maximum power point (MPP). This report introduces an Enhanced Incremental Conductance (EIC) based MPPT algorithm designed to optimize energy harvesting, making solar power a more robust and effective tool for sustainable rural development.

2.0 Technical Background and Literature Review

2.1 Limitations of Conventional MPPT Methods

Traditional MPPT methods, such as Perturb and Observe (P&O) and Incremental Conductance (INC), are simple but suffer from significant drawbacks, including slow tracking speed and large steady-state oscillations. Under the dynamic weather conditions typical of rural environments, these methods often fail to track the MPP accurately, reducing the overall energy yield and undermining the reliability required to meet SDG 7 targets. While advanced soft computing techniques offer higher accuracy, their complexity and cost make them unsuitable for low-cost rural deployments.

2.2 The Case for an Enhanced Incremental Conductance (EIC) Approach

Recent studies have revisited Incremental Conductance-based MPPT for its balance of simplicity and effectiveness. However, conventional INC algorithms struggle to differentiate between power fluctuations caused by voltage disturbances and those from sudden changes in solar radiation, leading to tracking errors. This report identifies a critical need for an adaptive algorithm that is both robust and cost-effective. The proposed EIC method addresses these gaps by integrating additional control logic to distinguish between environmental changes and system disturbances. Key observations from the literature highlight the advantages of this approach:

• Combines the simplicity of traditional INC with adaptive intelligence, making it suitable for rural applications.
• Improves tracking accuracy under dynamic irradiance without requiring extra hardware like temperature sensors, aligning with the affordability goal of SDG 7.
• Reduces oscillations and prevents tracking direction loss, enhancing system stability and reliability.
• Offers a superior balance of performance and implementation complexity for grid-tied rural PV systems.

3.0 Proposed Methodology for Sustainable Power Generation

The proposed system consists of a PV array, a boost converter managed by an EIC-based MPPT controller, and a three-phase Voltage Source Inverter (VSI) for grid integration. This architecture is designed to deliver stable and high-quality power, a cornerstone for achieving sustainable infrastructure as outlined in SDG 9 (Industry, Innovation, and Infrastructure) and SDG 11 (Sustainable Cities and Communities).

3.1 PV Module and Boost Converter Design

The system utilizes a standard single-diode PV model. The boost converter steps up the PV output voltage to the level required for grid integration. Its primary function is to execute the commands from the MPPT controller by adjusting its duty cycle, thereby ensuring the PV array operates at its maximum power point regardless of environmental fluctuations.

3.2 Enhanced Incremental Conductance (EIC) MPPT Controller

The core innovation is the EIC algorithm. Unlike the traditional INC method, which can lose track of the MPP during rapid changes in solar radiation, the EIC algorithm incorporates additional checks. It analyzes changes in both current and voltage to differentiate between a power fluctuation caused by a voltage perturbation and one resulting from a change in solar radiation. This allows the algorithm to prevent divergence from the MPP and maintain optimal power extraction, thereby maximizing the clean energy generated and contributing directly to SDG 7 and SDG 13.

4.0 Simulation Results and Discussion

The proposed methodology was validated using MATLAB/Simulink for a 100 W solar PV system under varying temperature and irradiance profiles. The simulation confirmed the EIC algorithm’s ability to effectively track the MPP and ensure stable grid integration.

4.1 Performance Under Dynamic Conditions

The results demonstrate that the EIC controller successfully adjusts the duty cycle to maintain the PV system at its MPP. The boost converter’s output voltage consistently matched the reference voltage, indicating superior control and stability. The system achieved seamless integration with the utility grid, delivering a stable power output. This level of reliability is essential for supporting rural economies and improving quality of life, aligning with the broader aims of the Sustainable Development Goals.

4.2 Comparative Analysis

A comparative analysis showed that the proposed EIC method provides significant advantages over traditional approaches:

• Faster Convergence: The EIC algorithm demonstrated a 22% faster convergence to the MPP.
• Increased Efficiency: The system achieved a 15% increase in overall energy conversion efficiency due to reduced oscillations and more accurate tracking.
• Improved Power Quality: The intelligent controller produced a stable modulation index, leading to better voltage regulation and lower harmonic distortion.

5.0 Hardware Implementation and Validation

A real-time hardware prototype was developed to validate the simulation findings. The experimental setup confirmed the superior performance of the EIC-based MPPT controller in a practical application, reinforcing its potential for widespread deployment in rural micro-grids.

5.1 Total Harmonic Distortion (THD) Analysis

The hardware results demonstrated a significant improvement in power quality. Compared to traditional methods, the EIC controller achieved substantially lower THD values:

• Simulation THD: Voltage THD of 13.15% and Current THD of 12.31%.
• Hardware THD: Voltage THD of 14.52% and Current THD of 13.55%.

These results are well below those of conventional converters and indicate a marked improvement in power quality. By minimizing harmonic distortions, the system ensures the delivery of clean and stable electricity, which is critical for powering sensitive electronic devices and fostering local economic activities in rural areas.

6.0 Conclusion and Future Outlook

This report has successfully demonstrated a novel power extraction strategy for rural AC micro-grids that directly supports the achievement of the Sustainable Development Goals, particularly SDG 7. The Enhanced Incremental Conductance (EIC) based MPPT algorithm provides a robust, efficient, and cost-effective solution for maximizing power from solar PV systems under real-world conditions. The verified improvements in convergence speed, efficiency, and power quality establish this technology as a critical enabler for building resilient and sustainable energy infrastructure in developing regions.

Future work will focus on further refining the algorithm to handle partial shading conditions, a common challenge in distributed PV systems. By continuing to enhance the performance and affordability of such technologies, we can accelerate the global transition to clean energy and ensure that no community is left behind.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

The article primarily addresses issues related to the following Sustainable Development Goals (SDGs):

• SDG 7: Affordable and Clean Energy

  This is the most explicitly mentioned and central SDG in the article. The introduction directly states that the work is motivated by the need to accomplish “Sustainable Development Goal (SDG) 7, which calls for ‘affordable, reliable, sustainable, and modern energy for all'”. The entire paper focuses on developing a solar photovoltaic (PV) energy system specifically to “promote rural electrification in developing countries,” which is a core objective of SDG 7.

• SDG 9: Industry, Innovation, and Infrastructure

  The article’s focus on creating a “novel Maximum power point tracking (MPPT) technique” and an “interconnected Alternating Current (AC) grid architecture” directly relates to SDG 9. It contributes to building resilient infrastructure (9.1), promoting clean and environmentally sound technologies (9.4), and enhancing scientific research and technological capabilities (9.5) to make energy systems more efficient and sustainable.

• SDG 13: Climate Action

  Although not mentioned by number, the article’s context aligns with SDG 13. It highlights the need to “develop carbon-free power grids, reduce global warming, and run out of fossil fuels” as key drivers for the integration of solar energy. By proposing a more efficient solar power system, the research contributes to climate change mitigation efforts by making renewable energy a more viable alternative to fossil fuels.

2. What specific targets under those SDGs can be identified based on the article’s content?

Based on the article’s content, the following specific SDG targets can be identified:

1. Targets under SDG 7 (Affordable and Clean Energy)

   • Target 7.1: By 2030, ensure universal access to affordable, reliable and modern energy services. The article directly addresses this by focusing on “rural electrification” and citing statistics like “84% of the world’s population lacks access to electricity and lives in rural areas” and “Approximately 31 million rural dwellings in India have yet to be electrified.”
   • Target 7.2: By 2030, increase substantially the share of renewable energy in the global energy mix. The paper’s entire premise is to improve the efficiency and viability of solar PV systems, a key renewable energy source, thereby facilitating its wider adoption.
   • Target 7.a: By 2030, enhance international cooperation to facilitate access to clean energy research and technology… and promote investment in energy infrastructure and clean energy technology. This research paper itself is a contribution to clean energy technology, presenting a “novel Maximum power point tracking (MPPT) technique” to improve solar energy systems.

2. Targets under SDG 9 (Industry, Innovation, and Infrastructure)

   • Target 9.1: Develop quality, reliable, sustainable and resilient infrastructure… with a focus on affordable and equitable access for all. The conceptualization of an “interconnected Alternating Current (AC) grid architecture powered by solar photovoltaic energy” for rural areas is a direct attempt to develop such infrastructure.
   • Target 9.4: By 2030, upgrade infrastructure… with increased resource-use efficiency and greater adoption of clean and environmentally sound technologies. The proposed Enhanced Incremental Conductance (EIC) method, which increases PV system efficiency by 15%, is a clean technology designed to improve resource-use efficiency.
   • Target 9.5: Enhance scientific research, upgrade the technological capabilities of industrial sectors in all countries, in particular developing countries… The paper is a clear example of scientific research aimed at creating an advanced technological solution (“Enhanced Incremental Conductance algorithm”) for the energy sector in developing nations.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

Yes, the article mentions and implies several quantitative and qualitative indicators that can measure progress:

• Indicators for Access to Energy (Target 7.1)

  The article provides baseline statistics that serve as indicators of the current challenge, such as the “770 million [people] in 2019” lacking electricity and the disparity between urban (97%) and rural (82%) electricity availability. The successful deployment of the proposed system would contribute positively to Indicator 7.1.1: Proportion of population with access to electricity.

• Indicators for Technological Efficiency and Performance (Targets 7.2, 9.4, 9.5)

  The article provides specific, measurable performance metrics for its proposed technology, which act as direct indicators of its contribution to efficiency and innovation. These include:

  • Increase in PV System Efficiency: The article states that the new method results in “15% increasing the efficiency of the photovoltaic system.” This is a direct measure of improved performance for a renewable energy source.
  • Convergence Speed: The EIC-based MPPT achieves “22% fast convergence,” indicating a more responsive and efficient system under changing conditions.
  • Power Quality (Total Harmonic Distortion – THD): The article provides precise measurements for power quality. For the EIC controller, it reports “VTHD of 13.15% and ITHD of 12.31%” in simulation and “VTHD of 14.52% and ITHD of 13.55%” in hardware implementation. Lower THD values indicate a cleaner, more reliable power output, contributing to the quality of the energy infrastructure.

4. Table of SDGs, Targets, and Indicators

Source: nature.com