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Over the last decade, multilevel inverter (MLI) has gained a global research paradigm in power electronics. The high-power application of multilevel inverters necessitates the safe and reliable operation of the inverter. Fault diagnosis of MLI is inevitable to enhance the reliability of the inverter. The real-time applications monitor the intricate switching process of the MLI using data from sensors like voltage, current, and temperature. Obtaining complementary fault features through conventional methods is difficult due to operating complexity and limited switch-fault samples. These methods heavily depend on prior knowledge. To deal with this problem, this paper proposes a new multiscale kernel convolution neural network (MKCNN) for fast fault diagnosis of cascaded MLI. Firstly, the proposed method necessitates using frequency domain samples instead of raw signals, which can leverage the power of a convolution neural network (CNN) to obtain hierarchical features from the images through a short-time Fourier transform (STFT). Secondly, the multiscale kernel convolution network model is constructed to capture and analyze low- to high-level fault features. This method improves the traditional CNN by extracting discriminative fault information through multiple convolution kernels of different scales with varying resolutions obtaining high diagnosis accuracy under single and multiple open circuit and short circuit faults. Finally, the softmax layer generates the output of the fault diagnosis results. Simulation results validate the effectiveness of the proposed model, demonstrating a high diagnosis accuracy rate of 98.3%. The model exhibits robustness in diagnosing single and multiple switch faults across different fault cases of an MLI. Comparison with other intelligent models further emphasizes the superiority of the proposed method.

In industries, the demand for multi-phase Multi-Level Inverters (MLIs) increases as they have reduced switching loss, Common Mode Voltage (CMV) and voltage stress across switches. The Multi-Carrier PWM (MCPWM) and Space Vector Modulation (SVM) techniques are predominantly used for controlling the inverter. This paper discusses various PWM techniques like PD, POD, APOD, IC, PSC, VFC PWM and SVM (OFV and SVM with Zero CMV) for 5-phase NPC 3L Inverter. Each PWM techniques gives better results in voltage THD/ dc-link balancing/ CMV. The SVM is significant for obtaining better performances in all these aspects. The Optimized Five Vector (OFV) which has 113 vectors is preferred than normal SVM as it has inequality relationship between 5-phase voltages. Though, OFV gives better results in terms of higher output voltage and lower NPF, the CMV is not eliminated. To eliminate CMV, 51 vectors that generates Zero CMV is selected to drive the inverter where output voltage and NPF is also improved. However, due to the presence of x-y components the distortion is present. The vectors are further reduced to 31 where the x-y components are neglected to reduce the distortion is proposed in this paper. The performance of the inverter drive is enhanced by applying proposed SVM with 31 vectors. The NPF, CMV and losses are calculated for all PWM techniques, also the THD performances of an inverter is found for various techniques. The simulation is carried out for all PWM techniques and the results are verified by experimental results.

The inverter drives for controlling multiple loads will provide several advantages like lower power electronic components, costs, space, etc. In this paper, a new Three-Level (3L) Neutral Point Clamped (NPC) inverter topology for controlling the two independent Five-Phase Load (FPL) is proposed which is named as Twenty Five Switch Inverter (TFSI) topology. This TFSI topology has five switches and two diodes in each leg. The number of switches in the conventional two load inverter is 30 switches which is reduced to 25 switches in the proposed topology. The Space Vector Modulation (SVM) for the proposed TFSI topology has 1024 vectors which is the addition of two individual Five-Phase Three-Level (FPTL) SVM. The performance of two loads for the proposed topology is examined at different conditions like changing the fundamental frequency (fo), switching frequency (fsw) and modulation indices. The simulation is carried out with MATLAB/Simulink and the results are validated with hardware implementation.

The increasing number of electrical components and sensors in modern vehicles makes network design more challenging. The development of automotive electronics through multiple communication protocols brings out the importance of a hybrid network that is both optimal and fault-tolerant. In order for a vehicle to communicate with electronic components like engine management systems, stability control units, braking systems, and door functions, a CAN (controller area network) is developed. In order to create a hierarchical vehicle network gateway for quality fortification and cost reduction of vehicles, the CAN and LIN (local interconnect network) are considered. This standardisation will reduce the variety of low-end multiplex solutions currently available for automotive electronics’ development costs, production rates, service fees, and logistics costs. The implementation of a gateway in these electronic devices is made possible with the proposed hybrid architecture. This system effectively shows the high-speed and low-speed applications relevant to crucial ECUs in the network by using two distinct CAN and LIN gateways to send sensor data between the ECUs (electronic control units).

The Neutral Point Clamped (NPC) Multi-Level Inverters (MLI) have been ruling the power electronics industries for the past two decades. The Multi-Carrier Pulse Width Modulation (MCPWM) is common PWM techniques which are widely used in NPC-MLI applications. However, MCPWM is not having a good impact on the balancing of DC-link voltages, Common Mode Voltage (CMV) and limiting the Total Harmonics Distortion (THD). The Selective Harmonic Elimination (SHE) technique is introduced for reducing the THD, however all the switching angles should be maintained less than $\pi $ /2 to keep the eliminated harmonics at constant level which narrows down the modulation index range. Hence, in recent days Space Vector Modulation (SVM) technique is widely used in NPC-MLI, which gives better DC-link voltage balancing, self-neutral point balancing, near-zero CMV reduction, better-quality harmonics profile and switching loss minimization. Hence, it is a preferred solution for the majority of electrical conversion applications such as electric traction, high power industrial drives, renewable power generation, and grid-connected inverters, etc. The paper gives a comprehensive review of the SVM for NPC-MLI. First, this paper deliberates the state of art for two-level SVM and extends it to three-level (3L) SVM. Also compares the 3L SVM performance with other MCPWM techniques. Followed by the various modified MLI SVM techniques in terms of their implementations, DC-link capacitor balancing, and reduction of CMV. Further, the review of MLI SVM is widened to open-end winding Inverters and multiphase MLIs. The final part of this paper discussed the future trends and research directions on MLI SVM techniques and its applications.

Conventional power systems have been heavily dependent on fossil fuel to meet the increasing energy demand due to exponential population growth and diverse technological advancements. This paper presents an optimal energy model and power management of an off-grid distributed energy system (DES) capable of providing sustainable and economic power supply to electrical loads. The paper models and co-optimizes multi-energy generations as a central objective for reliable and economic power supply to electrical loads while simultaneously satisfying a set of system and operational parameters. In addition, mixed integer nonlinear programing (MINLP) optimization technique is exploited to maximize power system generation between interconnected energy sources and dynamic electrical load with highest reliability and minimum operational and emission costs. Due to frequent battery cycling operation in the DES, rainflow algorithm is applied to the optimization result to estimate the depth of discharge (DOD) and subsequently count the number of cycles. The validity and performance of the power management strategy is evaluated with an aggregate load demand scenario of sixty households as a benchmark in a MATLAB program. The simulation results indicate the capability and effectiveness of optimal DES model through an enhanced MINLP optimization program in terms of significant operational costs and emission reduction of the diesel generator (DG). Specifically, the deployment of DES minimizes the daily operational cost by 71.53%. The results further indicate a drastic reduction in CO2 emissions, with 22.76% reduction for the residential community load scenario in contrast to the exclusive DG system. This study provides a framework on the economic feasibility and effective planning of green energy systems (GESs) with efficient optimization techniques with capability for further development.

The use of hybrid renewable energy systems among household consumers in sub-Sahara Africa (SSA) is increasingly gaining attention. This is due to low electrification rates in many of the countries in SSA. A hybrid energy system for power generation combines various energy systems, either renewable or a combination of renewable and fossil-powered sources for optimal power extraction and operation. In the era of decarbonization of the electricity grid through the use of renewable energy, hybridization of sources is an essential condition for the production of electricity. Based on current quest for renewable energy (RE) expansion in the global energy mix, optimum conditions for the production and adoption of hybrid renewable energy systems (HRES) at micro-levels are indispensable and must be advocated for. This can be justified based on the perpetually rising cost of energy for socio-economic development. This paper presents a survey of major issues regarding the motivations and specific benefits behind the adoption of HRES. Also presented, is a discussion on different renewable energy sources that can be adopted for HRES application for both grid and off-grid consumers. Furthermore, a discussion on the important issues as it pertains to the design and implementation of HRES is also presented. Finally, a policy discussion on the affordability of HRES in a low-income household is presented.

The increased adoption of intermittent renewable sources in the energy sector has also increased the use of battery storage systems. However, the negative impact which the improper disposal of batteries has on the environment has stirred debates on its sustainability. To ensure the proper disposal of battery waste, there is a need to identify and rank the most preferred battery ‘end-of-life’ handling alternatives. This paper focuses on identifying the most preferred ‘end-of-life’ handling alternatives for batteries using a modified triangular intuitionistic fuzzy aggregating and ranking function (TIFARF) model. To test the proposed modified TIFARF model, opinions from experts in the Nigerian renewable energy sector were collected, and the results show that the most preferred alternative is incineration, with a closeness coefficient of 0.130, while the least preferred alternative is recycling, whose closeness coefficient is 0.112. The results are an indication of a lack of facilities needed for the proper recycling of battery remains after their lifetime; if adequate facilities are available, the opinion of experts may be biased towards other alternatives. Future studies should focus on more battery ‘end-of-life’ handling alternatives and on countries with adequate facilities that can be used to manage batteries at the end of their lifespan.

This paper proposes a digital model predictive controller (DMPC) for a multi-input multi-output (MIMO) DC-DC converter interfaced with renewable energy resources in a hybrid system. Such MIMO systems generally suffer from cross-regulation, which seriously impacts the stability and speed of response of the system. To solve the contemporary issues in a MIMO system, a controller is required to attenuate the cross-regulation. Therefore, this paper proposes a controller, which increases speed of response and maintains stable output by regulating the load voltage independently. The inductor current and the capacitor voltage of the proposed converter are considered as the controlling parameters. With the aid of Forward Euler’s procedure, the future values are computed for the instantaneous values of controlling parameters. Cost function defines the control action by the predicted values that describe the system performance and establish optimal condition at which the output of the system is required. This allows proper switching of the system, thereby helping to regulate the output voltages. Thus, for any variation in load, the DMPC ensures steady switching operation and minimization of cross-regulation. To prove the efficacy of proposed DMPC controller, simulations followed by the experimental results are executed on a hybrid system consisting of dual-input dual-output (DIDO) positive Super-Lift Luo converter (PSLLC) interfaced with photovoltaic renewable energy resource. The results thus obtained are compared with the conventional PID (proportional integrative derivative) controller for validation and prove that the DMPC controller is able to control the cross-regulation effectively.