• Energy Research

Power tapping from HVDC transmission corridor to serve rural areas has been the focus of many researchers and network planners. The tapping stations are to be of small power ratings so that it will not interfere with the main control and stability of the HVDC network. Several research works have assumed tap-off of different percentages of the main HVDC terminal rating without justification. This paper therefore proposes a simple analytical technique used to determine power tapping limit on DC-link of a VSC HVDC network. Effect of power tapping below and above the analytical tap limit is illustrated by results from simulation carried out in Matlab/Simulink, hence validating the proposed technique.

This paper solves the allocation planning problem of integrating large scale renewable energy hybrid distributed generations and capacitor banks into the distribution systems. Extraordinarily, the integration of renewable energy hybrid distributed generations such as solar photovoltaic, wind, and biomass takes into consideration the impact assessment of variable generations from PV and wind on the distribution networks’ long term dynamic voltage and small-signal stabilities. Unlike other renewable distributed generations, the variability of power from solar PV and wind generations causes small-signal instabilities if they are sub-optimally allocated in the distribution network. Hence, the variables related to small-signal stability are included and constrained in the model, unlike what is obtainable in the current works on the planning of optimal allocation of renewable distributed generations. Thus, the model is motivated to maximize the penetration of renewable powers by minimizing the net present value of total cost, which includes investment, maintenance, energy, and emission costs. Consequently, the optimization problem is formulated as a stochastic mixed integer linear program, which ensures limited convergence to optimality. Numerical results of the proposed model demonstrate a significant reduction in electricity and emission costs, enhancement of system dynamic voltage and small-signal stabilities, as well as improvement in welfare costs and environmental goodness.

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.

The use of a single criterion in the selection of the most suitable hybrid renewable energy system (HRES) has been reported to be inadequate in terms of sustainability. In order to fill this gap, this study presents a multi-criteria approach for the selection of HRES for a typical low-income household. The analysis is based on two energy demand scenarios viz: consumer demand based on energy efficient equipment (EET) and consumer energy demand without energy efficiency. The optimization of the HRES is performed using hybrid optimization of multiple energy renewables (HOMER) while the multi-criteria analysis is carried out using Criteria Importance Through Intercriteria Correlation (CRITIC) and the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS). Results show that the optimal HRES alternative returned based on both energy demand scenarios is a PV/GEN/BAT system. The analysis further shows that a reduction of 44.6% in energy demand through EET leads to: 51.38% decrease in total net present cost, 11.90% decrease in cost of energy, 96.61% decrease in CO 2 emission and 193.94% increase in renewable fraction. Furthermore, the use of multi-criteria approach for HRES selection has an influence in the selection and ranking of the most suitable HRES alternatives. Overall, the application of EETs is environmentally and economically beneficial while the application of MCDM can help decision makers make a comprehensively informed decision on the selection of the most suitable HRES.

Traditional centralized energy grids struggle to meet urban areas’ increasingly complex energy demands, necessitating the development of more sustainable and resilient energy solutions. Smart microgrids offer a decentralized approach that enhances energy efficiency, facilitates the integration of renewable energy sources, and improves urban resilience. This study follows a systematic review approach, analyzing the literature published in peer-reviewed journals, conference proceedings, and industry reports between 2011 and 2025. The research draws from academic publications of energy institutions alongside regulatory reports, examining actual smart microgrid deployments in San Diego, Barcelona, and Seoul. Additionally, this article provides real-world case studies from New York and London, showcasing successful and unsuccessful smart microgrid deployments. The Brooklyn Microgrid in New York demonstrates peer-to-peer energy trading, while London faces regulations and funding challenges in its decentralized energy systems. The paper also explores economic and policy frameworks such as public–private partnerships (PPPs), localized energy markets, and standardized regulatory models to enable microgrid adoption at scale. While PPPs provide financial and infrastructural support for microgrid deployment, they also introduce stakeholder alignment and regulatory compliance complexities. Countries like Germany and India have successfully used PPPs for smart microgrid development, leveraging low-interest loans, government incentives, and regulatory mechanisms to encourage innovation and adoption of smart microgrid technologies. In addition, the review examines new trends like the utilization of AI and quantum computing to optimize energy, peer-to-peer energy trading, and climate resilient design before outlining a future research agenda focused on cybersecurity, decarbonization, and the inclusion of new technology. Contributions include the development of a modular and scalable microgrid framework, innovative hybrid storage systems, and a performance-based policy model suited to the urban environment. These contributions help to fill the gap between what is possible today and what is needed for future sustainable urban energy systems and create the foundation for resilient cities of the next century.

Purpose The application of hybrid renewable energy system (HRES) can mitigate inadequate access to clean, stable and sustainable energy among households in sub-Saharan Africa (SSA). Available studies on HRES seem to concentrate only on its techno-economic and environmental viability. In so doing, these studies do not seem to underline the likely challenges that follow the acquisition of HRES by especially low-income households. The ensuing reality is, of course, a limitation in the use of HRES in homes with low incomes. It is therefore imperative to analyze how a household with low income can afford this kind of energy system. The purpose of this study, therefore, lies in presenting a techno-economic, environmental and affordability analysis of how HRES is acquired. Design/methodology/approach To arrive at a grounded analysis, a typical household in SSA is used as an example. The analysis focused on the pattern of energy use, and this is obtained by visiting an active site to evaluate the comprehensive load profile. In the course of analysis, an optimal techno-economic design and sizing of a hybrid PV, wind and battery were undertaken. Additionally, an acquisition analysis was done based on loan amortization. Findings The interesting result is that a combination of the photovoltaic-gasoline-battery system is the most cost-effective energy system with a net present cost of $2,682. The system combination can lead to an emission reduction of approximately 98.3 per cent, compared to the use of gasoline generating sets, common mostly in SSA. If an amortized loan is used to purchase the energy system, and the payment plan is varied such that the frequency of payments is made quarterly, annually, semi-annually, bi-monthly, semi-monthly and bi-weekly, it will be observed that low-income household can conveniently acquire a HRES. Originality/value The result presented a framework by which a low-income household can purchase and install HRES. To facilitate this, it is recommended that low-income households should be given interest-friendly loans, so as to enhance the acquisition of HRES.

Vast peak demand management approaches are being implemented in the residential space, and some of them involve automated switching control strategies. Controlled switching of appliances during peak periods minimizes demand and energy consumption, however this may constrict the consumer's flexibility to utilize desired appliances to fulfil their needs. This article presents the experimental implementation of an end-use appliance control simulation study, for performance evaluation of a control technique. The system prototype was built based on an end-use appliance, switching control technique embedded with an event detector algorithm. The performance of the switching control device was evaluated in a lab-home-representative environment. Factors surrounding occupant's energy consumption behavior and issues on frequent switching of appliances are discussed. Validation of device performance was done through experimental tests and results obtained revealed that the control system is feasible as it contributed towards peak demand and energy consumption reduction. Results also show the effectiveness of the system in increasing user's preferred appliance (UPA) usage flexibility margin.

Abstract This paper presents a constant voltage operation of a Six-Phase Self-Excited Induction Generator (SPSEIG) driven by a fixed speed wind turbine using an Ant colony optimisation (ACO) technique to predict the behaviour of a the machine. In this paper, an attempt has been made to estimate the excitation capacitance requirements of a SPSEIG for maintaining rated terminal voltage and frequency. The range of capacitance variation required for maintaining constant terminal voltage while supplying a load of variable magnitude is evaluated. Analytical approaches, suitable for all the configurations of shunt capacitances such as variable excitation capacitance connected across (i) single three-phase winding set only and (ii) both the three-phase winding sets of an SPSEIG for operation as a simple shunt on no load and pure resistive load, are presented. The mathematical model developed is based on loop impedance method using graph theory. It is shown that the proposed technique is very effective and useful for making the SPSEIG feasible for remote areas with wind potential. The proposed approach is tested and compared with Genetic Algorithm (GA) and Fmincon technique.

The demand for renewable energy-based Electric Vehicle (EV) charging infrastructure is increasing in recent years. Solar PV based EV charging method is preferred as it has simple energy harvesting technique. The PV system is an uncertain power source, where the power generation is varied with respect to the availability of sunlight. So, that the charging station requires a backup power supply for the uninterrupted charging. For the integrated power sources, the charging station requires a simple and efficient conversion unit for the DC/AC/DC conversion. In this work, a modified Z-source inverter (MZSI) is developed for the multiport EV charger using PV and grid. The proposed MZSI is connected between the input and output sides to boost the voltage as per the demand at the battery side. In order to connect many battery units with the charger, the capacitors used in the MZSI are split as per the required number of charging ports. This developed converter topology operates the systems in four different modes like PV-Grid, PV-battery, grid-battery, and battery-grid. The performance of this proposed work has been validated in MATLAB/Simulink® and in the experimental setup. The experimental setup has been developed with two charging ports for obtaining 250W at each charger end which cumulatively produces 500W output across both chargers with an efficiency of 90.18%.