Renewable Energy Focus最新文献

Renewable-diesel hybrid systems are increasingly common as remote communities, powered primarily by diesel fuel, seek alternatives to reduce costs and emissions while improving energy autonomy. This study goes beyond plug loads to include options for a northern remote community to eliminate imported fuels used in stationary combustion by displacing diesel electricity while electrifying heating loads. Four scenarios are developed using HOMER for a case study in the Kivalliq region of Canada to examine high renewable penetration potential energy systems, including heating loads. A 1200 km power line extension from a hydroelectricity grid in southern Canada has been proposed in the region. The powerline is compared to on-site renewables, such as wind and solar, and to the base case with increasing carbon prices. The highly seasonal nature of heating loads, and the acute risks of power loss in the winter results in high capacity, but low usage back-up infrastructure requirements. District heating is considered as a novel way to assist in increasing the renewable fraction in remote contexts to minimize fossil fuel back-up requirements. Assuming the grid extension can be developed on budget and that diesel prices inflate, this analysis shows the powerline presents the lowest cost path to full decarbonization, and lower costs than business as usual. Using a combination of local renewables and district heating, 60% renewable penetration could be achieved with comparable net present costs to the powerline. In high priced diesel fuel scenarios, increasing renewable energy either with onsite generation or the power line extension present lower cost options than continued reliance on imported fossil fuels.

This article proposes a novel energy management structure for electric vehicles, consisting of a supercapacitor and two types of batteries, to improve efficiency and navigable distance. The key features of a suitable energy storage system include high power and energy density, low cost and weight, minimal maintenance, and long life. Although batteries are the primary power storage source in electric vehicles, they have power limitations. Therefore, a high-power-density supercapacitor is added to the battery to create a hybrid energy storage system, reducing stress on the battery and increasing its lifespan. The article presents a new structure for hybrid storage systems based on the existence of a main battery, a replaceable battery, a supercapacitor, and a DC-DC converter. An active charge equalizer circuit for the main battery in standby mode and its control system are also introduced. A control method for dividing power between different sources under different conditions is presented, and the design parameters of the energy storage system are optimized using a genetic algorithm to minimize mass and losses. The performance of the proposed system is evaluated through simulation in MATLAB software and tested in a small-scale laboratory sample. The article also provides a detailed analysis of different working modes, including electric motor acceleration, low-speed mode, high-speed mode, and electric regenerative braking mode. Additionally, a control method for energy management between batteries and supercapacitors is introduced, aiming to increase efficiency. The results show that the proposed hybrid energy storage system can effectively improve the efficiency of electric vehicles.

A theoretical method is presented, called the energy-balance method, for maximising the energy extracted from a renewable energy converter in terms of determination of an optimal control. The method applies to control systems specified by linear graphs, and graph-theoretic techniques are employed. The method simplifies a number of optimal control problems by essentially expressing the performance objective — maximising energy extraction — in terms of an equivalent objective involving fewer variables, thereby reducing the complexity of the optimisation. As illustrated, in certain cases the optimal control problem may be reduced to one solvable by elementary calculus techniques. The theory is illustrated with examples from solar, wave and wind applications.

The specialized dairy cattle and porcine subsectors in the Region of Antioquia offer a sustainable and renewable energy source through anaerobic digestion of residual biomass. This process offers multiple advantages, including greenhouse gas emissions reduction, environmentally friendly fertilizer production, and the establishment of self-sustaining models for remote rural areas lacking access to traditional energy sources. Recent advancements in hydrogen production through methane conversion using biogas reforming technologies have garnered substantial attention as a viable fossil fuel alternative. The Colombian National Hydrogen Strategy, aimed at 2030, envisions an electrolysis capacity of 1–3 GW, requiring an estimated USD 5.5 billion investment in hydrogen production and demand projects, notably in mobility and refineries. This necessitates a specialized regulatory framework with incentives to drive lasting investments that align with decarbonization and reindustrialization objectives. This study conducted a comprehensive assessment of animal house boundary residual biomass sources to determine their biogas potential. Industrial livestock activities revealed substantial technical-energy potentials: 1,896 TJ/year for pig farming and 187 TJ/year for dairy cattle practices. The research’s primary objective was a geospatial analysis pinpointing hotspots for biogas production from residual biomass within the dairy cattle and porcine subsectors in the specific region of Antioquia, in Colombia. This research is of great interest as it contributes to the growing field of sustainable energy production. It highlights the potential of utilizing residual biomass to transform local energy landscapes in alignment with global sustainability imperatives.

Renewable energy sources, particularly solar and wind power, offer promising solutions for sustainable electricity generation. However, their inherent dependency on natural conditions and resulting intermittent generation pose challenges to the electricity grid.

This study investigates the strategy of wind-solar complementarity to partly mitigate this issue, leveraging open-source data from the Slovak Republic. Our analysis reveals that combined solar and wind generation aligns more closely with real consumption compared to individual solar generation. We employ two quantitative methodologies, ordinary least squares (OLS) and least absolute deviations (LAD) regressions, to demonstrate the consistency of our findings. Additionally, we assess the prevalence of dunkelflaute events using real-generation data, finding them to be infrequent and posing a minimal risk in the context of Central Europe.

We show that complementarity can be studied using open-source data for virtually any country in the world and thus quantitative methods can be used to advocate for renewable energy in general and balanced building of both wind and solar energy in particular. This research contributes to the broader understanding of renewable energy integration strategies and informs policymakers and stakeholders on optimizing energy systems for sustainability and cost-effectiveness.

One key driver of sustainable goal development is the transition to sustainable electricity resources. The sustainability impact assessment of power production evaluates all potential impacts on society, the environment, and the economy, as well as finds a reasonable solution to shift towards renewable. Given the multitude of quantitative and qualitative methodologies for sustainability analysis, alongside the absence of a unified procedure, selecting an appropriate method poses a significant challenge in conducting this task. Therefore, this paper conducts an extensive review of the methodologies employed for assessing the sustainability of power generation within the future energy mix, as reflected in scientific publications over the past decade (2013–2024). The main objective of this paper is to compare the methodologies and assess their efficiency as suitable tools for analyzing the sustainability of technologies in different geographical regions. The research methodology, following the screening process, selects 102 papers within the study’s scope to undergo a critical examination based on sustainability evaluation approaches. It also provides an overview of novel dynamic methods and the application of artificial intelligence in sustainability assessment. The primary findings indicate a deficiency in a standardized approach for sustainability evaluation within electrical technology. In addressing uncertainties in impact assessment due to various parameters, dynamic methods with multiple temporal accuracies are recommended over a static life cycle. The paper includes a case study comparing methods—multi-criteria decision-making, and ranking, scoring—in the Indonesian context. Considering 15 environmental, social, and economic indicators to evaluate the sustainability in Lombok, results indicate that hydropower, gas, and solar technologies exhibit the highest sustainability scores, respectively.

Volt-VAr optimization (VVO) is an important tool in improving the efficiency of distribution system by simultaneously coordinating voltage and reactive power both. Today, loads are largely dependent on voltage and thus, this voltage-dependence affects both real and reactive power. So, minimizing apparent power is more important than minimizing the energy. VVO enables distribution system utilities to run their network on comparatively lower voltage which ultimately increases energy savings. Devices such as, on load tap changers (OLTC), and voltage regulators (VRs) are commonly adopted techniques to regulate/boost the voltage. Capacitive banks (CBs) are also used to inject reactive power (VAr) into the system keeping the operational constraints and system constraints specified and satisfied. This paper presents a new methodology of Volt-VAr optimization using Genetic algorithm considering a variety of constraints. The test is performed on IEEE-69 bus system and results validate the efficacy of the proposed algorithm.

Despite massive investment and carbon-neutral transition goals set around the world, gasoline-based internal combustion engine vehicles still form an absolute majority in the transportation sector. With the advent of technology, access to electricity, uncertainties in fuel prices and health awareness, people worldwide are moving towards a better, reliable, cost-effective and environmentally friendly mode of transportation, a hybrid electric vehicle. Such a vehicle, with its powerful electric motor and compact gasoline-based engine, offers better efficiency in terms of operating cost and reliability. Considering the advent of hybrid electric vehicles taking pace, studies related to its architecture types, power flow dynamics, control and modelling of its various components will form an essential part of the automobile industry and research. This paper proposes a power flow topology for a hybrid electric vehicle with series-parallel architecture. The developed vehicle model with such an architecture type consists of three main sub-systems: the electrical system, the control system and the mechanical system. The presented power flow topology being modelled and analysed in detail in the Simulink tool is being implemented via a mode logic controller, which forms part of the central control system. The developed hybrid electric vehicle model demonstrates various modes of operation, from starting to accelerating to de-accelerating and then finally coming to a complete rest. Each mode yields and explains the following: the vehicle reference speed; the engine and generator turn functions on/off; the dc bus and battery voltage; the motor, battery, and generator current; the motor, generator, and engine speed; engine torque; engine power; throttle demand; and the vehicle’s actual speed. The results thus obtained show that the waveforms associated with such topology, during its various modes of operation, are pretty stable and acceptable, thereby depicting and validating the operation of the developed hybrid electric vehicle model with proposed power flow topology in a precise and transparent manner.

This paper presents a novel application of the chaos game optimization (CGO) algorithm to optimally design PI controllers for power electronic interface circuits of offshore wind farms (OWF) consisting of a permanent magnet synchronous generator powered by a variable-speed wind turbine. The OWF is linked to the network via a high-voltage direct current (HVDC) transmission system. The CGO metaheuristic method is employed to fine-tune voltage source converter (VSC)-based HVDC transmission systems’ proportional-integral controller gains. The study explores multiple strategies to extract the highest power from the system while ensuring stability under symmetrical and unsymmetrical fault conditions. The CGO algorithm consistently yields superior results to other algorithms, improving system regaining and stability post disturbances. Consequently, the technique enhances the dynamic and transient stability of the OWF. The detailed study is implemented using MATLAB/Simulink.

In recent years, growing consumer demand for sustainable energy is driving down costs and paving the way for more clean energy in the future. Since these energies are sporadic, and the load pattern does not correlate to their generation pattern, a battery storage system is required. Operating dispersed alternative energy sources, connected to the grid in this situation makes energy control an unavoidable task. The difficulty is brought on by things like intermittent sources, daytime costs, solar panel and battery size restrictions, and limitations in battery charging and discharging rates. Moreover, integrating energy storage devices into the power system network is one of the recommendations made in this work to increase the performance and dependability of these systems. Compared to the existing works reported in the literature, this study offers enhanced control techniques for hybrid Photovoltaic and Battery Energy Storage System under fluctuating atmospheric scenario. Here, an innovative approach called Drone Squadron Optimisation, which tracks the Global Maximum Power Point, is used get maximum power. Further, suggested approach is tested with various partial shading instances and the uniform irradiance condition to validate it. This research also investigates photovoltaic models and the status of the battery storage device for improved energy management in the system. Finally, the proposed algorithm assists in quickly identifying the potential benefits of a grid-connected, battery-powered rooftop solar system.