This review paper is a foundational resource for power distribution and management decisions, thoroughly examining short-term load forecasting (STLF) models within power systems. The study categorizes these models into three groups: statistical approaches, intelligent-computing-based methods, and hybrid models. Performance indicators are compared, revealing the superiority of heuristic search and population-based optimization learning algorithms integrated with artificial neural networks (ANNs) for STLF. However, challenges persist in ANN models, particularly in weight initialization and susceptibility to local minima. The investigation underscores the necessity for sophisticated predictive models to enhance forecasting accuracy, advocating for the efficacy of hybrid models incorporating multiple predictive approaches. Acknowledging the changing landscape, the focus shifts to STLF in smart grids, exploring the transformative potential of advanced power networks. Smart measurement devices and storage systems are pivotal in boosting STLF accuracy, enabling more efficient energy management and resource allocation in evolving smart grid technologies. In summary, this review provides a comprehensive analysis of contemporary predictive models and suggests that ANNs and hybrid models could be the most suitable methods to attain reliable and accurate STLF. However, further research is required, including considerations of network complexity, improved training techniques, convergence rates, and highly correlated inputs to enhance STLF model performance in modern power systems.

Battery energy storage systems and multilevel converters are the most essential constituents of modern medium voltage networks. In this regard, the modular multilevel converter offers numerous advantages over other multilevel converters. The key feature of modular multilevel converter is its capability to integrate small battery packs in a split manner, given the opportunity to submodules to operate at considerably low voltages. In this paper, we focus on study of potential SMs for modular multilevel converter based battery energy storage system while, keeping in view the inconsistency of secondary batteries. Although, selecting a submodule for modular multilevel converter based battery energy storage system, the state of charge control complexity is a key concern, which increases as the voltage levels increase. This study suggests that the half-bridge, clamped single, and full-bridge submodules are the most suitable submodules for modular multilevel converter based battery energy storage system since, they provide simplest state of charge control due to integration of one battery pack along with other advantages among all 24 submodule topologies. Depending on submodules analysis, the modular multilevel converter based battery energy storage system based on half-bridge submodules is investigated by splitting it into AC and DC equivalent circuits to acquire the AC and DC side power controls along with an state of charge control. Subsequently, to validate different control modes, a downscaled laboratory prototype has been developed.

Renewable energy sources such as photovoltaic and wind turbine power generators may make the power grid unstable because of their output fluctuations. Battery energy storage systems (BESSs) are being considered as a countermeasure for this issue. Cascaded H-bridge (CHB) is expected as a promising topology for large capacity BESSs because the state of charge (SOC) of battery clusters can be controlled independently by H-bridge power units, and the harmonic current of the system is low enough to remove the ac filter. This paper describes the development of the Y-connection CHB-BESS and a power control strategy for the BESS. A real-scale 2MW/10kV CHB-BESS was constructed in Shenzhen, China and its successful operation verify the effectiveness of the proposed control method. Based on the system, the power control strategy was verified by three parts of the experiment, which are decoupling power control test, emergency shutdown test and step response test. The results indicate that the system can realize decoupling control of active and reactive power effectively, achieve step response at the millisecond level and make full-load shutdown in an emergency state at the microsecond level.

The modern utility grid is transitioning from a centralized to a distributed structure, facilitated by integrating distributed generation sources (DGs) and loads. Microgrids (MGs) have emerged as a key solution, with different topologies such as parallel AC microgrids, series-cascaded AC microgrids (SC-ACMGs), and series-parallel ACMGs, each offering distinct advantages for specific applications. Parallel ACMGs provide fault tolerance and well-established protection schemes, making them widely adopted in industrial and urban power grids. Meanwhile, SC-ACMGs offer modular scalability and efficient voltage stacking, making them suitable for renewable energy sources (RESs) integration, battery energy storage, off-grid electrification, and electric vehicle charging infrastructure. Series-parallel ACMGs combine features of both but introduce additional control complexity. With increasing interest in SC-ACMGs for applications requiring direct voltage stacking and reduced power conversion stages, this paper provides an inclusive review of SC-ACMG architectures and their control methodologies. While SC-ACMGs enable cost-effective and flexible control, they face challenges such as power sharing, frequency synchronization, and voltage regulation, particularly with higher penetration of RESs. This paper explores different SC-SCMG configurations, technical challenges, and control methodologies, providing a comparative analysis of existing methodologies. Furthermore, it identifies research gaps, future trends, and technical barriers to large-scale deployment while suggesting potential solutions. Finally, it discusses emerging technologies to enhance SC-ACMG integration with smart grid features, serving as a valuable resource and roadmap for researchers working on next-generation power systems.

Series-cascaded microgrids (SCMGs) indeed provide control flexibility and high-voltage synthesis capabilities. However, the power distribution in SCMGs based on distributed generation (DG) sources stays understudied. This paper proposes an SCMG topology using non-dispatchable DG sources and battery energy storage, with an integrated power-routing control. The objective is to address power distribution limitations and stabilize SCMG output voltages under varying conditions. A case study validates the control methodology, considering zero irradiation levels for photovoltaic (PV) and maximum power sharing. The battery modules play a crucial role by providing power, voltage support, and maintaining capacitor voltage at a reference value of a PV-integrated module. This is achieved through a third harmonic current injection in the fundamental frequency current, coupled with proportional power distribution using a third harmonic power signal. The effectiveness of the proposed SCMG topology and control is demonstrated through MATLAB/Simulink and hardware-in-loop analyses (Typhoon HIL). The results present an extended power distribution between series-cascaded DG sources-based units while ensuring stable SCMG output voltages, even in adverse conditions like PV module intermittency. Future work aims to extend the proposed topology to a ring/delta-connection SCMG, where third harmonic current aids power distribution among SCMG legs and between series-cascaded DG sources-based units.