DC microgrids look attractive in distribution systems due to their high reliability, high efficiency, and easy integration with renewable energy sources. The key objectives of the DC microgrid include proportional load sharing and precise voltage regulation. Droop controllers are based on decentralized control architectures which are not effective in achieving these objectives simultaneously due to the voltage error and load power variation. A centralized controller can achieve these objectives using a high speed communication link. However, it loses reliability due to the single point failure. Additionally, these controllers are realized through proportional integral (PI) controllers which cannot ensure load sharing and stability in all operating conditions. To address limitations, a distributed architecture using sliding mode (SM) controller utilizing low bandwidth communication is proposed for DC microgrids in this paper. The main advantages are high reliability, load power sharing, and precise voltage regulation. Further, the SM controller shows high robustness, fast dynamic response, and good stability for large load variations. To analyze the stability and dynamic performance, a system model is developed and its transversality, reachability, and equivalent control conditions are verified. Furthermore, the dynamic behavior of the modeled system is investigated for underdamped and critically damped responses. Detailed simulations are carried out to show the effectiveness of the proposed controller.

Recently, different metaheuristic techniques, their variants, and hybrid forms have been extensively used to solve economic load dispatch (ELD) problems with and without valve point loading (VPL) effects. Due to the randomization involved in these metaheuristic techniques, one has to perform extensive runs for each experiment to get an optimal solution. The process may sometimes become laborious and time-consuming to converge to an optimal solution. On the other hand, advanced calculus-based techniques, being deterministic, perform iteration systematically and come up with the same solution on each run of the experiment. Since ELD problems are constrained optimization problems, we are proposing the constrained (deterministic) optimization algorithm for their solutions. Various 13-unit, 38-unit, and 40-unit thermal test systems are considered. Valve point loading (VPL) effects are also considered in some cases. Computer-based numerical results depict that the constrained optimization algorithm shows evidence of being almost as competitive in a total fuel cost as the metaheuristic optimization techniques, especially for the less-constrained ELD problems but with far reduced computation time. This finding validates the application of the constrained optimization technique to solve the economic dispatch problem.

In a standalone DC microgrid, sources are interconnected in a parallel configuration. When sources of different power ratings are parallel connected, there arises a major issue of circulating currents which disturb current sharing by sources as per their capacity. Consequently, the voltage regulation becomes poorer. Additionally, connecting line resistances also play their part to contribute to abnormal current sharing. Droop controllers are normally preferred for the mitigation of circulating currents among parallel-connected sources. However, droop controllers cannot eliminate circulating currents for different rating sources. Hence, current sharing and voltage regulation cannot be ensured simultaneously. To address the issues, a distributed architecture-based Sliding Mode Control (SMC) technique is proposed in this paper. An analysis of the circulating currents for a two-source system is presented. Simulation results are presented to show the effectiveness and fail-safe operation of the proposed technique in a steady-state condition.

DC microgrids are gaining popularity due to their lack of reactive power compensation, frequency synchronization, and skin effect problems. However, DC microgrids are not exempted from stability issues. The stability of DC microgrids based on decentralized architecture is presented in this paper. Centralized architecture can degrade system performance and reliability due to the failure of a single central controller. Droop with proportional integral (PI) controller based on decentralized architecture is being used for DC microgrid stability. However, droop control requires a tradeoff between voltage regulation and droop gain. Further, global stability through PI controller cannot be verified and controller parameters cannot be optimized with different operating conditions. To address limitations, an equivalent sliding mode (SM) controller is proposed for a DC microgrid system in this paper. Detailed simulations are carried out, and results are presented, which show the effectiveness of an equivalent SM controller.

Load-sharing and voltage regulation are key challenges in low voltage dc microgrid systems. Droop-based decentralized control methods are used to control dc grids which cannot achieve these challenges simultaneously due to unequal voltages and load power variations. Centralized control schemes can achieve these challenges using high bandwidth communication. However, the failure of a single central controller can degrade performance and reliability. In addition, cascaded proportional-integral (PI) type controllers are used to control the voltage and current loop of each power electronic converter. These controllers suffer stability and show slower dynamic responses. Furthermore, control parameters cannot be optimized for different operating conditions. To address these challenges, a distributive control method using an equivalent sliding mode (SM) controller utilizing low bandwidth communication is proposed in this paper. The distributive method improves reliability and achieves load sharing and voltage regulation simultaneously. Furthermore, in SM, both voltage and current loop operate in the parallel configuration which improves the dynamic response and shows stability in all operating conditions. To analyze, a system model is developed, and existence and stability conditions are verified. Detailed simulations are carried out to show the steady-state and transient performance. The presented results show the effectiveness of the proposed scheme.

Recent years have witnessed the rapid proliferation of Industry 4.0 technologies in smart grids, leading to a revolution in energy generation and management, which provides improved operational efficiency and intelligent automation for smart grids. Nevertheless, this highly integrated infrastructure, while making energy more secure and reliable, simultaneously creates greater vulnerability to sophisticated cyber threats such as Distributed Denial of Service (DDoS) attacks, data manipulation and unauthorized access. The task of addressing these challenges requires innovative approaches that maintain the resilience as well as security of critical energy infrastructures. A novel Blockchain-Enhanced Cybersecurity Framework (BCF) specific to Industry 4.0-enabled smart grid systems is presented in this paper. The proposed framework integrates advanced security protocols with real-time threat detection capabilities through the decentralized, transparent and tamper-resistant nature of blockchain technology. Authentication, data validation and secure communication are accomplished through smart contracts to automate it, eliminating human intervention and single points of failures. The framework is able to allow for high transaction volumes, typical of modern smart grid networks, whilst maintaining integrity via a hybrid consensus mechanism that ensures scalability. In addition, the framework is further augmented with a Machine Learning-Based Intrusion Detection System (ML-IDS) to detect and mitigate cyber-attacks in real time. The proposed system achieves excellent performance in identifying malicious activities with high accuracy, precision and recall on the UNSW-NB15 dataset. Analysis with traditional methods indicates that the Blockchain Enhanced Cybersecurity Framework significantly lowers false positive rates and increases detection reliability. The framework is justified in terms of its strength to secure the systems in Industry 4.0-enabled smart grids against emerging cyber threats through extensive simulations and case studies. The value of this work is that it shows that blockchain and machine learning can be used to improve cybersecurity in renewable energy systems, and concrete insights and recommendations on implementing secure and cost-effective systems of energy infrastructure are provided. The proposed framework creates an enabling environment on which the creation of resilient and future-ready smart grids to facilitate the global goal of sustainable and secure energy can be developed.