This study evaluates a disturbance-informed, planning-level workflow for assessing steady-state feeder performance and post-disturbance frequency security in renewable-rich distribution networks. The workflow links feeder operation in DIgSILENT PowerFactory to reduced-order frequency-security screening in OpenModelica and PSAT, with Pandapower used as an independent steady-state cross-check. The IEEE 33-bus feeder includes distributed photovoltaic units, DFIG-based wind generation, and a grid-forming battery energy storage system (BESS). Hourly feeder time-series results are used to identify renewable-output deficits, and each deficit is converted from MW to the common 10 MVA dynamic-system base before being applied as a conservative step disturbance. The steady-state validation gives a maximum voltage mismatch of 0.0155 pu, within the adopted 2% screening limit. The cross-tool frequency benchmark shows close agreement for nadir and settling time, while RoCoF is interpreted conservatively because of its sensitivity to numerical differentiation and event implementation. As renewable penetration increases from 0% to 100%, the minimum bus voltage remains close to 1.0 pu (0.9999–0.9991 pu), the maximum bus voltage rises from 1.0295 pu to 1.0826 pu, and feeder losses increase from 0.0246 MW to 0.1531 MW. The 24 h assessment gives a maximum daily voltage of 1.0755 pu at 100% penetration, while loading remains below thermal limits. For the corrected 75% severe event (0.3048 MW; −0.0305 pu on the 10 MVA base), the 2 MW droop-plus-FFR case improves the nadir from 49.9695 Hz without support to 49.9924 Hz. Voltage therefore becomes the earliest binding screening constraint from 50% penetration onward, whereas thermal loading and supported frequency nadir remain non-binding under the studied conditions.

Harmonic components are present in power systems due to the nonlinear characteristics of the circuit elements used in power electronics-based products and their rapid implementation. Power systems rely on essential parameters such as sinusoidally varying voltage and current, oscillating at a frequency of 50 Hz. The established limits of IEEE-519-1992 served as a reference point in this analysis. To achieve optimal performance, it is crucial to keep the total harmonic distortion (THD) below the specified threshold, even at specific harmonic frequencies, while also considering the power factor. By analyzing the simulation results and forecasts for each mitigation approach, it is possible to reduce THDI below the IEEE-519 standard while gaining financial and electrical benefits. The analysis and modeling focused on the photovoltaic system, which includes solar panels, a DC-DC converter, a DC-AC inverter, and a nonlinear load. The evaluation of the results from the designed systems was conducted according to the IEEE standard and SANS 10142 Standard to ensure the safety of connected equipment in the off-grid network. The results pertain to a standalone single-phase photovoltaic system and the single-phase Z-Source inverter. The Z-Source inverter features two unique PWM control methods: the constant boost control and the simple boost control. Each of the three designs incorporates a combination of passive filters: the LC filter, LCL filter, and LLCL filter. The outcomes are based on three different configurations of the network. LLCL demonstrates exceptional performance as a passive filter, confirming its position as the best option. The optimal performance of a single-phase off-grid photovoltaic system is achieved by using LC, LCL, and LLCL filters, with respective performance percentages of 2.99%, 2.45%, and 1.71%. The unfiltered rate was 89.05%, indicating a concerning situation for the devices connected to the network.

The global transition to renewable energy sources (RESs) has accelerated the search for novel solutions for efficient energy generation, storage, and consumption. This paper details the design, simulation, and performance assessment of a 55 kW standalone photovoltaic (PV) system for rural areas, focusing on voltage quality improvement by LCL filtering and the prospective incorporation of a proton exchange membrane fuel cell (PEMFC). The unrefined inverter output of the PV system demonstrated considerable harmonic distortion, with Total Harmonic Distortion of Voltage (THDV) over 55% during early switching transients and sustaining elevated levels beyond IEEE 519 standards under steady-state settings. The blue phase regularly had the largest THDV, indicating anomalies in inverter switching or load imbalance. The integration of an LCL filter into the inverter output stage markedly enhanced power quality, lowering THDV to under 1% across all phases and attaining a harmonic attenuation of almost 98%. Although the PEMFC was inactive throughout the LCL-filtered testing, its function in stabilizing DC-link voltage and providing load support under dynamic situations is essential for the durability of hybrid systems. The findings validate that the suggested LCL-filtered PV system complies with international power quality requirements, providing a feasible alternative for clean and dependable independent energy generation.

Z-source inverters (ZSIs) have lately replaced conventional voltage source inverters (VSIs). The Z-source inverter, developed by Prof. F. Z. Peng in 2002, outperformed both current-source and voltage-source inverters, showcasing a more advanced configuration for direct current (DC) to alternating current (AC) conversion [1]–[3].Obtain gain-factors within the ZSI circuit to ensure that filters and power quality demonstrate the same percentage of enhancement as the boost factors observed in SBC, CBC, and MBC approaches. Gain factors demonstrate a linear relationship with a boost factor, where the modulation index acts as the constant of proportionality. The potential stress ratio within the switching elements of a ZSI is, on average, increased by 1.7% for MBC PWM control and decreased by over 40% for the MBC technique. On average, the total harmonic distortion for the Z-source inverter is reduced by more than 112% using the series boost converter technique, increased by over 16.8% with the current boost converter technique, and decreased by more than 24% when applying the modified boost converter technique.

There is a need to design a system to ensure that parties involved in crop production, distribution and consumption have a transparent supply chain management system that guarantees the products' openness, neutrality, reliability and, thus, security. This paper presents a system developed to decentralize agricultural supply-chain management by allowing supply-chain stakeholders to validate supply-chain events and carry out guaranteed payments using blockchain technology in agricultural supplychain management, from farm to table. Blockchain introduces digital trust into the system as important information is recorded in a public space, immutable, transparent, time-stamped and decentralized. This eliminates the need for third parties to be involved. The developed system enhances food safety and integrity through higher traceability and forces dishonest business entities out of business, thereby making the market safe. A peer-to-peer Agricultural crop products supply chain data structure was designed, and a front-end interface for users to sign up to using a crypto wallet was set up, providing a marketplace where farmers receive just compensation for their crops, thereby minimizing the risk of exploitation by dishonest intermediaries. The consumers also benefit as they will not pay inflated prices for their goods through the curbing of artificial inflation of prices by intermediaries.

Detecting and locating faults within electrical grids presents substantial challenges in power systems engineering, leading to energy loss, reduced revenue, and equipment damage. This paper provides a comprehensive review of the integration and utilization of machine learning algorithms to enhance fault identification processes. Acknowledging the constraints of traditional methods, the paper delves into the historical evolution of fault detection in power systems. By highlighting the significance of machine learning, this review underscores its pivotal role in fault prevention, energy conservation, and bolstering the resilience of power infrastructures.

Marine renewable energy extraction continues to be a prominent area of interest worldwide. The exploration of this particular type of energy has yet to be carried out in South Africa, which is unique in being the only country in the world that is bordered by both the Indian and Atlantic oceans. The aforementioned factor motivated a research investigation into the optimal type of turbine that could efficiently harness tidal energy. The present investigation focuses on the empirical examination of the operational efficiency of the triple helix turbine. The parameters of the model are presented, followed by a comprehensive account of the fabrication procedures utilized in the construction of the turbine. The experimental environment is described in precision, followed by an extensive account of each conducted experiment. This study presents a comparative analysis between experimental results and simulation results. It constitutes a concise overview of the findings and subsequently formulates deductions.

An increase in the weather events can result in an increase in the frequency of grid faults, thereby leading to a decrease in electricity supply reliability. To develop a better performance model for outage forecasting, it is essential to consider various types of events for different complex weather conditions and constraints. A conventional event-driven forecasting algorithm is only appropriate for a single type of event scenario and unable to adapt effectively to multiple types of event scenarios concurrently. A multiple-constraints event-driven outage model that depends on a maximum entropy function, which transforms a complex event-driven outage problem into two continuous differential single-objective subproblems using the collaborative neural network (CONN) algorithm is proposed in this article. The CONN event-driven forecasting algorithm, validated by many experiments, successfully resolves the problem of the difficulty in obtaining very large complex weather events and outages data.

Electrification has become the most useful tool to improve the standard of living in rural and remote areas. The usage of fossil-fueled power stations for electrification has had harmful effects on the environment, thus, requiring alternative energy sources. The usage of existing renewable energy sources such as solar and wind energy, as well as the use of microgrids, is gaining popularity as a strategy to attain full electrification for rural areas, due to its benefits of being environmentally-safe and having sustainable performance. In this paper, the simulations of power flow and DC fault analysis were performed for a PV/Wind hybrid DC microgrid in the MATLAB /SIMULINK. The main aims was to understand the influence of DC microgid and study the steadiness of the hybrid system under different DC faults conditions. The faults analysed are DC line to line and DC line to ground. The results revealed a good load distribution for a hybrid DC microgrid, not much influenced by faults. The expected maximum voltages of 666.6 V from Vdc was not met during fault condition, maximum power point tracker/1 plays an important part boosting the performance of the system under the hybrid of wind and PV generations.

The introduction of variable speed drives (VSD's) has become very popular in industrial operations, as it allows for smoother and more efficient operations of different processes. The installation of a VSD in an electrical system reduces the operational costs and if well implemented, it prolongs the life span of electrical equipment in the power system. Although the use of VSD's offers these benefits, the main disadvantage is that its operations produce harmonics. Harmonic filters can be used to act as a low impedance path at the harmonic frequency, which enables the filter to shunt most of these harmonics at their frequencies [1]. This paper presents an investigation of the harmonic distortion caused by the operation of variable speed drives in a soap manufacturing industry with the main aim to determine the best harmonic filter to mitigate these harmonics. For this reason, the use of single tuned, double-tuned, C-type, and high pass filters are considered to determine which filter would best mitigate the harmonic distortion.

Tidal power is a form of renewable energy from the ocean that can be exploited for electrical power generation. Several countries have implemented the techniques of harnessing tidal power through tidal barrages and tidal streams. A substantial amount of the electricity consumed in South Africa is generated from the combustion of fossil fuel, which is known to have huge consequences on the environment. Hence, the establishment of a tidal power plant would reduce greenhouse gasses and also minimize the huge reliance on fossil fuels. This paper presents the concepts of the design elements for a tidal plant that employs helical turbines. A case study of Esikhawini is presented which is the optimum site that was selected for the establishment of the tidal plant proposed in this study. The significance of this study mainly focused on the design considerations of the helical turbine. The tidal velocity at Esikhawini was modelled the results show an average velocity of 1.5 m/s. The tidal velocity was used as an input into the analytical model of the turbine which implements the blade element momentum theory (BEMT). The power generated from a single tidal turbine unit was 23.75 kW, and the overall power generated from the proposed tidal plant was 1.4 MW.

With the growing penetration level of renewable energy (RE) systems, the overall inertia of the power system is expected to reduce to values that expose the system to inadvertent frequency eventuality that can threaten the stability, security, and resilience of the system. To tackle this issue, this paper proposes an advanced virtual inertia control strategy in an interconnected power system which considers high renewable energy penetration and power system deregulation. The virtual inertia control is capable of providing dynamic inertia support by adjusting the active power reference of the power electronic converter of an energy storage system (ESS). This improves the response and stability of the system during frequency events. The proposed virtual inertia control strategy is based on the type-II fuzzy logic control scheme. To improve the accuracy and performance of the proposed controller, the artificial bee colony algorithm is used for optimal tuning of the input and output weights of the type-II fuzzy-based virtual inertia control. The proposed control strategy is designed to competently perform during load variation, RE fluctuations, and other power system dynamic disturbances. The simulation results show its robustness in minimizing the frequency deviation and maintaining system frequency within specified operating limits.

The safe operation, control, and stability of standalone microgrids (MGs) are highly dependent on their coordination with the MG control center (MGCC). Due to the open communication channel between the MG and the MGCC, the measurement signals are vulnerable to cyber attacks that can compromise the stability of the system. In this article, a false data injection (FDI) attack on the frequency measurement of a standalone MG is considered to disrupt the stable operation of the MG. Therefore, an attack detection and identification method are proposed to protect the MG against the impacts of this attack. The proposed method is based on a dynamic state estimation technique that uses an unknown input observer (UIO) to estimate the MG states and generate a residual function that detects the presence of an FDI attack and triggers a detection alarm for attack isolation and mitigation. The robustness and practicability of the proposed method are demonstrated with real-time simulation results of a real-world MG system.

The frequency stability of stand-alone microgrids (MGs) is highly vulnerable due to the high penetration of fluctuating renewable energy and continuous demand variations that are unknown to the MG in real-time. Therefore, to maintain the frequency of a stand-alone MG within safe operational limits, there should be efficient frequency regulation to correct power imbalances caused by renewable energy systems and demand variations. This paper proposes the application of the unknown input observer (UIO) for dynamic disturbance estimation of unknown inputs in a stand-alone microgrid (MG). The proposed UIO scheme is capable of estimating the internal states of the MG and accurately estimate the disturbances or unknown inputs that affect the steady-state operation of the MG. The robustness of the proposed UIO model is verified for real-time applications using the Speedgoat real-time simulator.

This study presents analyses of the results of selected experimental power quality (PQ) data obtained on a grid-tied photovoltaic (PV) system composed of different PV modules technologies and four PV inverters integrating the grid at the point of common coupling. A PQ analyzer is utilized to collect the data from the 110 kW PV system for two weeks. The measured PQ data was obtained by following South Africa and international power quality measurement standards. The data measured were RMS voltage, RMS current, voltage unbalance, frequency, voltage total harmonic distortion (THDV), current total harmonic distortion (THDI), active and reactive power. Voltage unbalance, frequency, voltage total harmonic distortion (THDV), current total harmonic distortion (THDI) have been appraised and juxtaposed with the requirements of the South Africa Renewable Energy Grid Code. These parameters were all found within the regulated limits, except for the current total harmonic distortion (THDI) that exceeded the grid code limit due to sudden voltage variations. This occurrence is observed primarily at dawn and dusk when the PV inverter output active power is at the lowest level. This study's performance analysis contributes to evaluating large-scale PV systems inverters’ behaviour and their impact on the distribution grid power quality at different power generation levels.

Inertia emulation has been considered as a promising solution to improve the frequency stability of stand-alone microgrids (MGs) with high penetration of renewable energy sources (RESs). To effectively emulate system inertia using power electronic converters, it is necessary to accurately estimate the actual system frequency. The phase-locked loop (PLL) has been widely used in frequency estimation; however, it is associated with measurement delays that may compromise the stability of a M G if the disturbance is severe. This paper proposes a frequency-locked loop (FLL)-based inertia emulation strategy in a stand-alone MG to improve the frequency response of the system. The performance of the proposed strategy is compared to a conventional PLL-based inertia strategy under varying M G operating scenarios. The results show that the FLL-based inertia emulation strategy has a fast transient response, damps oscillation, and reduces frequency deviation. The frequency stability and resilience of the M G are shown to be preserved.

The access to electricity is one of the major problems faced by rural areas and isolated regions. Over the years, the fossil-fueled power stations used to generate electricity had a detrimental effects and it has necessitated the need for alternative energy sources such as solar, wind, biomass and other renewable energy sources. Hybrid energy system (HES) based on distributed energy resources (DERs) integration into the DC microgrid is considered as the viable means to carry out the electrification of rural as well as isolated area. However, DC microgrids are limited by the occurrence of faults and this affect their performance. This paper presents the modelling and simulation of power flow and the fault analysis in a hybrid DC microgrid. This hybrid DC microgrid is powered by PV and wind energy system, the formulation, modeling and simulations was implemented in the MATLAB/SIMULINK. The faults analyzed in the system are the DC line-to-ground faults and DC line-to-line faults. Results for a hybrid DC microgrid revealed that high quality of power is experienced in load distribution. Also based on the results, when DC faults occurs there is disturbance to output.

It is well known that a vast amount of energy is stored in the ocean. Tidal energy is a form of ocean energy which is yet to be exploited in South Africa and it can be considered as an alternative energy resource or renewable energy sources. The implementation of tidal technology can address the electricity crisis in the country and also minimizes the huge reliance on coal for power generation. The study covers the tidal phenomenon, the concept of tidal energy, energy conversion process and electrical energy generation. An overview of the two dominant tidal energy conversion systems; tidal barrage and tidal stream was done. The aim of this paper is to carry out a resource assessment, identify optimum characteristics for establishing a tidal plant and proposed the energy conversion system that is suitable for South Africa. Thus, based on the tidal resource available in the country, a suitable site is identified. The tidal resource, extractable power and the impact of the turbine configuration are evaluated using MATLAB.

In smart grid technology, modern communication infrastructure is utilized for the exchange of data between various elements of the microgrid (MG) system and the MG control center (MGCC). However, the integrity of the data may be compromised through cyber-attack activities leading to disruption in the stability and safe operation of the MG system. This paper investigates the vulnerability of frequency measurements to false data injection (FDI) attacks in an isolated MG system. The impact of two kinds of FDI attack on the frequency stability of the MG system is analyzed. The results show that FDI attacks can stealthily destabilize the stability of the MG with an exogenous FDI attack and more damage can be done with an endogenous FDI attack of negative magnitude. The analysis is done using the MATLAB/Simulink software.