Backward neural network (BNN) based multilevel control for enhancing the quality of an islanded RES DC microgrid under variable communication network.

Microgrids (MGs) and energy communities have been widely implemented, leading to the participation of multiple stakeholders in distribution networks. Insufficient information infrastructure, particularly in rural distribution networks, is leading to a growing number of operational blind areas in distribution networks. An optimization challenge is addressed in multi-feeder microgrid systems to handle load sharing and voltage management by implementing a backward neural network (BNN) as a robust control approach. The control technique consists of a neural network that optimizes the control strategy to calculate the operating directions for each distributed generating point. Neural networks improve control during communication connectivity issues to ensure the computation of operational directions. Traditional control of DC microgrids is susceptible to communication link delays. The proposed BNN technique can be expanded to encompass the entire multi-feeder network for precise load distribution and voltage management. The BNN results are achieved through mathematical analysis of different load conditions and uncertain line characteristics in a radial network of a multi-feeder microgrid, demonstrating the effectiveness of the proposed approach. The proposed BNN technique is more effective than conventional control in accurately distributing the load and regulating the feeder voltage, especially during communication failure.

A comprehensive review of wind power integration and energy storage technologies for modern grid frequency regulation.

Integrating wind power with energy storage technologies is crucial for frequency regulation in modern power systems, ensuring the reliable and cost-effective operation of power systems while promoting the widespread adoption of renewable energy sources. Power systems are changing rapidly, with increased renewable energy integration and evolving system architectures. These transformations bring forth challenges like low inertia and unpredictable behavior of generation and load components. As a result, frequency regulation (FR) becomes increasingly important to ensure grid stability. Energy Storage Systems (ESS) with their adaptable capabilities offer valuable solutions to enhance the adaptability and controllability of power systems, especially within wind farms. This research provides an updated analysis of critical frequency stability challenges, examines state-of-the-art control techniques, and investigates the barriers that hinder wind power integration. Moreover, it introduces emerging ESS technologies and explores their potential applications in supporting wind power integration. Furthermore, this paper offers suggestions and future research directions for scientists exploring the utilization of storage technologies in frequency regulation within power systems characterized by significant penetration of wind power.

Application of 0-1 test for chaos on forward converter to study the nonlinear dynamics.

DC-DC converters has significant role in the applied power electronic systems, distributed power systems, computers, home appliances and communication equipment. A converter must remain within the specified range of operation. The main goal of this paper is to discuss the nonlinear behavior of forward converter and highlighted the application of the 0-1 test by applying it on the forward converter. As forward converter may contains electronic components, which cause instability in the system. So, it is necessary to understand its behavior when specifications of components are changed. To study chaotic behavior, 0-1 test will be applied on the forward converter, which is a novel technique outperform in unearthing the subtle chaotic behavior in deterministic dynamical systems. The forward converter goes from period-1, period-2, period-4 and finally become chaotic when the load resistance is varied. This variation in the behavior of the forward converter are analysis through 0-1 test for chaos. Moreover, time series plot, phase portrait and Bifurcation diagram for forward converter is also drawn for the validation of results obtained from 0-1 test. Test algorithm is applied via MATLAB and simulation of forward converter via MultiSim by varying its load resistance.

A Critical Analysis of the Impact of Pandemic on China's Electricity Usage Patterns and the Global Development of Renewable Energy.

The COVID-19 pandemic has impacted economic activity in numerous sectors due to multiple forms of disruption, including border closures, a stay-at-home policy, and social isolation; the electricity consumption trends in this region will undoubtedly improve. This article examines the impact of COVID-19 on electricity generation and consumption in China during the first two quarters (Q1-Q2) of 2020 and 2021. Furthermore, several governments' perspectives on COVID-19's implications for renewable energy development, notably offshore wind power and solar photovoltaics (PV), were examined. Results of this article show that COVID-19 impacts the power industry. According to the analysis, during the first two quarters of 2020, the amount of electricity generated and consumed by China decreased by 1.4 and 1.3 percent, respectively, the capacity of the power plants increased by 5.3 GW and coal consumption dropped by 3.6 g/kWh. Investments in the power generation sector increased by 51.5 billion yuan and investment in the power grid grew by 0.7 billion. Additionally, new generation capacity decreased by 378 GW during the first two quarters of 2020. During the first two quarters of 2021, electricity consumption and production grew by 13.7 and 16.2 percent, respectively. Power plants' capacity increased by 9.5 GW, while coal consumption for power supply fell by 0.8 g/kWh. The investment in power generation projects increased by 8.9 billion, while investment in power grid projects increased by 4.7 billion. Compared to last year's same period, 14.92 GW of new capacity was installed. Due to lockdown measures, such as studying at home or working at home, domestic power use in the first two quarters of 2020-2021 increased by 6.6 and 4.5 percent, respectively. To minimize COVID-19's impact on renewable energy development and assist in building offshore wind power plants, economic and financial measures have been put in place to reduce the epidemic's effect on solar PV systems.

Sustainable Solutions for Advanced Energy Management System of Campus Microgrids: Model Opportunities and Future Challenges.

Distributed generation connected with AC, DC, or hybrid loads and energy storage systems is known as a microgrid. Campus microgrids are an important load type. A university campus microgrids, usually, contains distributed generation resources, energy storage, and electric vehicles. The main aim of the microgrid is to provide sustainable, economical energy, and a reliable system. The advanced energy management system (AEMS) provides a smooth energy flow to the microgrid. Over the last few years, many studies were carried out to review various aspects such as energy sustainability, demand response strategies, control systems, energy management systems with different types of optimization techniques that are used to optimize the microgrid system. In this paper, a comprehensive review of the energy management system of campus microgrids is presented. In this survey, the existing literature review of different objective functions, renewable energy resources and solution tools are also reviewed. Furthermore, the research directions and related issues to be considered in future microgrid scheduling studies are also presented.