Enhanced Harmonics Reactive Power Control Strategy Based on Multilevel Inverter Using ML-FFNN for Dynamic Power Load Management in Microgrid.

The shift of the world in the past two decades towards renewable energy (RES), due to the continuously decreasing fossil fuel reserves and their bad impact on the environment, has attracted researchers all around the world to improve the efficiency of RES and eliminate problems that arise at the point of common coupling (PCC). Harmonics and un-balance in 3-phase voltages because of dynamic and nonlinear loads cause a lagging power factor due to inductive load, active power losses, and instability at the point of common coupling. This also happens due to a lack of system inertia in micro-grids. Passive filters are used to eliminate harmonics at both the electrical converter's input and output sides and improve the system's power factor. A Synchronous Reference Frame (SRF) control method is used to overcome the problem related to grid synchronization. The sine pulse width modulation (SPWM) technique provides gating signals to the switches of the multilevel inverter. A multi-layer feed forward neural network (ML-FFNN) is employed at the output of a system to minimize mean square error (MSE) by removing the errors between target voltages and reference voltages produced at the output of a trained model. Simulations were performed using MATLAB Simulink to highlight the significance of the proposed research study. The simulation results show that our proposed intelligent control scheme used for the suppression of harmonics compensated for reactive power more effectively than the SRF-based control methods. The simulation-based results confirm that the proposed ML-FFNN-based harmonic and reactive power control technique performs 0.752 better in terms of MAE, 0.52 for the case of MSE, and 0.222 when evaluating based on the RMSE.

Assessing the role of sustainable strategies in alleviating energy poverty: an environmental sustainability paradigm.

The rapid urbanization and industrialization of India have caused a demand-supply gap in the electrical sector, leading to higher electric bills. Lower-income households face the worst energy poverty in the country. Sustainable strategies like corporate social responsibility are the most effective way to combat the energy crisis. This study aims to assess the contribution of corporate social responsibility (CSR) to energy poverty alleviation (EPA) by developing the role of mediating variables such as assessment of renewable energy resource (RER), feasibility of sustainable energy supply (SES), and sustainable energy development (SED). We used hybrid research methodology such as partial least squares structural equation modeling (PLS-SEM) to analyze the collected data from professionals, economic experts, and directors in the country in 2022. The study proved that CSR directly affects energy poverty alleviation. Besides, the findings suggest RER, SES, and SED significantly lead the energy poverty alleviation. The findings of this study will divert the attention of policymakers, stakeholders, and economists toward the corporate social responsibility to mitigate the energy crisis in Indian context. A mediating role of a renewable energy resource (RER) as a value-added contribution to this study can be strengthened more in future research. Based on the results, the study illustrates that CSR acts as a catalyst to alleviate energy poverty.

An evaluation of influencing factors and public attitudes for the adoption of biogas system in rural communities to overcome energy crisis: A case study of Pakistan.

Energy is the backbone of a country's economy and development. The potential contribution of renewable energy technology to energy stability, climate change mitigation and economic growth is immense. Biogas, is a renewable energy resource and enriched with methane, produced through the breakdown of organic matters (anaerobically). The large quantity of livestock has significant contributions in Pakistan's economy, and also having a high potential for production of biogas. Therefore, this study was conducted in 6 southern districts of Khyber Pakhtunkhwa province of Pakistan, to identify the expected willingness of households for adopting any biogas system. A sum of 360 households (livestock-farmers) was selected for data collection by the procedure of equal allocation. The identification of the influencing factors on the household's willingness to adopt any biogas system was determined through probit analysis. It has been validated from the research outcomes of probit analysis that the selected household's qualification, electricity shortfall on daily basis and its impact on children's education and female work, awareness of the selected household's about the biogas utilization and its benefits as well as the availability of space have demonstrated their significance and relationship with the household's willingness to adopt biogas system. The overall model is statistically significant at 1% significance level and confirmed the impact of socioeconomic features as the prominent factors for the household's decision to adopt a biogas system. This study suggests the public awareness, which has more significant impact on identifying the household's adoption behavior. Similarly, adequate investments both at the private and public level, should be encouraged for promoting biogas technology. At the same time, the government's fiscal policy should be subsidized which will encourage the lower-income populations' participation in adopting and installing biogas plants.