Electricity, Volume 5, Issue 3 (September 2024) – 12 articles

Modern power systems are growing in complexity due to the installation of large generators, long transmission lines, the addition of inertialess renewable energy resources (RESs) with zero inertia, etc., which can all severely degrade the system frequency stability. This can lead to under-/over-frequency load shedding, damage to turbine blades, and affect frequency-sensitive loads. In this study, we propose a methodology to improve the two critical frequency stability indices, i.e., the frequency nadir and the rate of change of frequency (RoCoF), by formulating an optimization problem. The size and placement location of battery energy storage systems (BESSs) are considered to be the constraints for the proposed optimization problem. Thereafter, the optimization problem is solved using the three metaheuristic optimization algorithms: the particle swarm optimization, firefly, and bat algorithm. The best performing algorithm is then selected to find the optimal sizing and placement location of the BESSs. The analyses are all performed on the IEEE 9-bus and IEEE 39-bus test systems. Several scenarios which consider multiple generator outages, increased/decreased loading conditions, and the addition of RESs are also considered for both test systems in this study. The obtained results show that under all scenarios, the proposed method can enhance system frequency compared to the existing method and without BESSs. The proposed method can be easily upscaled for a larger electrical network for obtaining the optimized BESS size and location for the improvement of the system frequency stability. Full article

This paper compares concentrated and distributed reactive power compensation to improve the power factor at the point of common connection (PCC) of an industrial electrical system (IES) with harmonics. The electrical system under study has a low power factor, voltage variation, and harmonics caused by motors operating at low loads and powered by variable-speed drives. The designed compensation system mitigates harmonics and reduces electrical losses with the shortest payback period. Four solutions were compared, considering concentrated and distributed compensation with capacitor banks and harmonic filters. Although the cost of investment in concentrated compensation is lower than that of distributed compensation, a higher reduction in electrical losses and a lower payback period are obtained with distributed compensation. Although the lowest payback period was obtained with distributed compensation with capacitor banks (0.4 years), it is not recommended in the presence of harmonics because the effects of current harmonics significantly reduce the useful life of these elements. For this reason, distributed compensation with harmonic filters obtained a payback period of 0.6 years, and it was proposed as the best solution. These results should be considered in projects aimed at power factor compensation in IESs with harmonics. The concentrated compensation of the capacitor bank at the PCC is proposed because of the lower investment cost and ease of installation. However, the advantages of distributed compensation with harmonic filters have not been evaluated. An energy efficiency approach is used to analyze the impact of the location methods of the power factor compensation equipment on the electrical losses of the IES. Full article

This paper presents the design of a predictive controller for a boost converter and validation through real-time simulation. First, the boost converter was mathematically modeled, and then the electronic components were designed to meet the operation requirements. Subsequently, a model-based predictive controller (MBPC) and a digital PI (Proportional–Integral) controller were designed, and their performance was compared using MATLAB/SIMULINK^®. The controls were further verified by implementing test benches based on an FPGA (Field-Programmable Gate Array) with an OPAL-RT real-time simulator, which included the RT-LAB and RT-eFPGAsim simulation packages. These tests were successfully carried out, and the methodology used for this design was validated. The results showed a better response obtained with MBPC, both in terms of stabilization time and lower overvoltage. Full article

This article examines the impact of meteorological conditions represented by ambient temperature, ambient humidity, wind speed, and daily precipitation sum on the reliability of low-voltage cable lines. Cable line reliability is crucial to the stability and safety of power systems. Failure of cable lines can lead to power outages. This can cause serious economic and social consequences, as well as threaten human safety, especially in the public sector and critical infrastructure. In addition, any interruption of cable lines generates costs related to repairs, operational losses, and possible contractual penalties. This is why it is so important to investigate the causes of power equipment failures. Many power system failures are caused by weather factors. The main purpose of this article is to quantify the actual impact of weather conditions on the performance and reliability of power equipment in distribution networks. Reliability indicators (failure rate, failure duration, restoration rate, and failure coefficient) for low-voltage cable lines were calculated as a function of weather conditions. Empirical values of the indicators were determined based on many years of observations of power lines operating in the Polish power system. An analysis of the conformity of their empirical distribution with the assumed theoretical model was also conducted. By quantifying the impact of specific weather factors on the operation of power equipment, it becomes possible to identify the ranges in which failures are most likely. Full article

Recent advancements in residential solar electricity have revolutionized sustainable development. This paper introduces a methodology leveraging machine learning to forecast solar panels’ power output based on weather and air pollution parameters, along with an automated model for fault detection. Innovations in high-efficiency solar panels and advanced energy storage systems ensure reliable electricity supply. Smart inverters and grid-tied systems enhance energy management. Government incentives and decreasing installation costs have increased solar power accessibility. The proposed methodology, utilizing machine learning techniques, achieved an R-squared value of 0.95 and a Mean Squared Error of 0.02 in forecasting solar panel power output, demonstrating high accuracy in predicting energy production under varying environmental conditions. By improving operational efficiency and anticipating power output, this approach not only reduces carbon footprints but also promotes energy independence, contributing to the global transition towards sustainability. Full article

Today, many factors, especially the increasing world population and developing technology, increase the energy needs of people and societies day by day. The fact that fossil resources are both in danger of depletion and have negative environmental impacts has directed countries to new resources. The study focuses on the effective use of renewable energy sources (RES) and the evaluation of waste to meet the electricity and heat energy needs of Yiğit Harman Village, located in the Solhan district of Bingöl Province. For this purpose, a renewable-energy-based combined heat and power system (CHP) was designed using HOMER Pro software (version 3.14.2, Homer Energy LLC, Boulder, CO, USA). Solar, wind, biomass, and hydrogen energy sources were used, considering the resources of the region. Using the designed model, the entire electricity energy requirement and half of the heat energy were completely met by the region’s available RESs. In addition to the technical analysis, economic and environmental analyses were also conducted, and LCOE, NPC, and CO₂ emission values were obtained as 0.271 USD/kWh, USD 739,772, and 37,958 kg/yr, respectively. These results indicate that with an investment of approximately USD 7000 per household, the electrical and thermal energy needs for 25 years can be met. Full article

Ghana, being blessed with abundant solar resources, has strategically invested in solar photovoltaic (PV) technologies to diversify its energy mix and reduce the environmental impacts of traditional energy technologies. The 50 MW solar PV installation by the Bui Power Authority (BPA) exemplifies the nation’s dedication to utilizing clean energy for sustainable growth. This study seeks to close the knowledge gap by providing a detailed analysis of the system’s performance under different weather conditions, particularly on days with abundant sunshine and those with cloudy skies. The research consists of one year’s worth of monitoring data for the climatic conditions at the facility and AC energy output fed into the grid. These data were used to analyze PV performance on each month’s sunniest and cloudiest days. The goal is to aid in predicting the system’s output over the next 365 days based on the system design and weather forecast and identify opportunities for system optimization to improve grid dependability. The results show that the total amount of AC energy output fed into the grid each month on the sunniest day varies between 229.3 MWh in December and 278.0 MWh in November, while the total amount of AC energy output fed into the grid each month on the cloudiest day varies between 16.1 MWh in August and 192.8 MWh in February. Also, the percentage variation in energy produced between the sunniest and cloudiest days within a month ranges from 16.9% (December) to 94.1% (August). The reference and system yield analyses showed that the PV plant has a high conversion efficiency of 91.3%; however, only the sunniest and overcast days had an efficiency of 38% and 92%, respectively. The BPA plant’s performance can be enhanced by using this analysis to identify erratic power generation on sunny days and schedule timely maintenance to keep the plant’s performance from deteriorating. Optimizing a solar PV system’s design, installation, and operation can significantly improve its AC energy output, performance ratio, and capacity factor on sunny and cloudy days. The study reveals the necessity of hydropower backup during cloudy days, enabling BPA to calculate the required hydropower for a consistent grid supply. Being able to predict the daily output of the system allows BPA to optimize dispatch strategies and determine the most efficient mix of solar and hydropower. It also assists BPA in identifying areas of the solar facility that require optimization to improve grid reliability. Full article

This paper explores how investments in research and development (R&D) and government policies impact the growth of renewable energy in Brazil, Chile, and Colombia up to 2040. The study presents four scenarios to understand how different levels of R&D investment and the presence or absence of supportive policies affect the spread of renewable technologies such as solar and wind energy. The scenarios range from an optimistic one with high R&D funding and strong policy support to a worst-case scenario with low R&D efforts and weak policies. The findings emphasize the importance of solid government backing and strategic R&D investments in promoting renewable energy and increasing the number of green patents. On the other hand, scenarios with limited policy support and R&D funding show much slower growth, highlighting the challenges posed by economic constraints and tough market conditions. The study shows that strong renewable energy policies could boost renewable energy adoption by 100% to 200%. Overall, this research adds to the discussion on sustainable energy policies and provides useful insights for policymakers and stakeholders to develop strategies that maximize the potential of renewable energy in the region. Full article

The application of fractional calculus to obtain dynamic models for supercapacitors represents an alternative approach to obtaining simpler and more accurate models. This paper presents a model for the supercapacitor in the time domain, based on the use of the fractional or non-integer order integral. This fractional model is compared with the conventional simple model, which is typically used in industrial applications. This fractional integral-based model provides satisfactory fits in relation to the number of parameters used in the model. Furthermore, an interpretation of the effect of the application of fractional integration is presented for constant current charging and discharging processes at constant current, using the Riemann–Liouville definition for the non-integer order integral. Supercapacitors are devices that exhibit non-linear behavior, with a distinct charging and discharging operation. There are several methods of dynamic analysis for the characterization of supercapacitors. The information extracted from these methods is essential for understanding the behavior of supercapacitors and, thus, ensuring that processes involving supercapacitors are as efficient as possible. This paper presents a dynamic analysis based on charge and discharge operations with constant currents. The conclusion is that the fractional model provides fairly accurate fits. Full article

This paper investigates hydrogen’s potential to accelerate the energy transition in hard-to-abate sectors, such as steel, petrochemicals, glass, cement, and paper. The goal is to assess how hydrogen, produced from renewable sources, can foster both industrial decarbonization and the expansion of renewable energy installations, especially solar and wind. Hydrogen’s dual role as a fuel and a chemical agent for process innovation is explored, with a focus on its ability to enhance energy efficiency and reduce CO₂ emissions. Integrating hydrogen with continuous industrial processes minimizes the need for energy storage, making it a more efficient solution. Advances in electrolysis, achieving efficiencies up to 60%, and storage methods, consuming about 10% of stored energy for compression, are discussed. Specifically, in the steel sector, hydrogen can replace carbon as a reductant in the direct reduced iron (DRI) process, which accounts for around 7% of global steel production. A next-generation DRI plant producing one million tons of steel annually would require approximately 3200 MW of photovoltaic capacity to integrate hydrogen effectively. This study also discusses hydrogen’s role as a co-fuel in steel furnaces. Quantitative analyses show that to support typical industrial plants, hydrogen facilities of several hundred to a few thousand MW are necessary. “Virtual” power plants integrating with both the electrical grid and energy-intensive systems are proposed highlighting hydrogen’s critical role in industrial decarbonization and renewable energy growth. Full article

This paper introduces a dynamic consensus-based economic dispatch (ED) algorithm utilizing the Alternating Direction Method of Multipliers (ADMM) to optimize real-time pricing and generation/demand decisions within a decentralized energy management framework. The increasing complexity of modern energy markets, driven by the proliferation of Distributed Energy Resources (DER) and variable demands from hybrid electric vehicles, necessitates a departure from traditional centralized dispatch methods. This research proposes a novel ADMM-based solution tailored for non-responsive and responsive demand units that integrates demand response mechanisms to adaptively manage real-time fluctuations while enhancing security and privacy through distributed data management. The testing of the algorithm on the IEEE 39 bus system under various load conditions over 24 h demonstrated the algorithm’s effectiveness in handling traditional and renewable energy sources, particularly highlighting the economic benefits of shifting controllable loads to periods of low-cost renewable availability. The findings underscore the algorithm’s potential to reduce energy costs, enhance energy efficiency, and offer a scalable solution across diverse grid systems, contributing significantly to advancing global energy policy and sustainable management practices. Full article

This article presents the development and execution of a Single-Ended Primary-Inductor Converter (SEPIC) multiplier within a Hardware-in-the-Loop (HIL) emulation environment tailored for photovoltaic (PV) applications. Utilizing the advanced capabilities of the dSPACE 1104 platform, this work establishes a dynamic data exchange mechanism between a variable voltage power supply and the SEPIC multiplier converter, enhancing the efficiency of solar energy harnessing. The proposed emulation model was crafted to simulate real-world solar energy capture, facilitating the evaluation of control strategies under laboratory conditions. By emulating realistic operational scenarios, this approach significantly accelerates the innovation cycle for PV system technologies, enabling faster validation and refinement of emerging solutions. The SEPIC multiplier converter is a new topology based on the traditional SEPIC with the capability of producing a larger output voltage in a scalable manner. This initiative sets a new benchmark for conducting PV system research, offering a blend of precision and flexibility in testing supervisory strategies, thereby streamlining the path toward technological advancements in solar energy utilization. Full article