Green Electric Power Research Articles

Self-Standing Hierarchical Porous Nickel-Iron Phosphide/Nickel Foam for Long-Term Overall Water Splitting

Electrolytic water splitting is a promising path for the production of clean hydrogen when combined with green electric power, such as photovoltaic and wind power; however, the high current water electrolysis is mainly dependent on the utilization of Pt, Ru, and other expensive materials, while the transition metal-based catalysts still need improvement in electrocatalytic activity and stability. Here, we present the preparation of economic and scalable electrode materials, Nickel-Iron phosphide/Nickel foam (NiFeP/NF), with a hierarchical porous structure for overall water splitting as both the anode and cathode. An overall potential of 1.85 V for the current density of 100 mA cm−2, and a long lifetime of 700 h, were achieved by using NiFeP/NF as both the anode and cathode. The nanostructures of the composite phosphides were investigated and the spent electrode after long-term electrolysis was characterized to investigate the long-term failure mechanism of the phosphides. Surface shedding and reconstruction theories were proposed for the failure of the NiFeP/NF cathode and anode in long-term electrolysis, respectively. Furthermore, TiO2 coating was proved to be an efficient strategy to elongate the lifetime of the phosphide electrodes, which shows a slow current decline rate of 0.49 mA·cm−2 h−1.

An Enhancement of the Solar Panel Efficiency: A Comprehensive Review

Recently solar panels are gaining popularity in the field of non-conventional energy sources for generating green and clean electric power. On the negative side, the photovoltaic efficiency is reduced with an increase in ambient temperature. The production of energy is dropped by 0.33% for every degree Celsius above STC. Consequently, the electric power which is generated by the solar panel may not be sufficient to run the load. It is important to realize that in some applications, such as standalone electric vehicles, space for providing an additional solar panel to compensate for the decremented output power may not be feasible. By implementing the cooling arrangements, this excessive heat might be reduced. Several cooling techniques have been implemented, named as active and passive methods. This article presents a review on maximizing the efficiency of the solar panel by utilizing different cooling methods and by integrating TEG with solar panels.

Environmental - friendly Al2O3 based Hydroelectric cells for green energy production

In recent times, it was observed that green electrical power can be generated using Hydroelectric Cells (HEC), which can be alternative of solar and fuel cell for future energy generation systems. This hydroelectric cell uses few drops of water to produce efficient, safe and eco-friendly green power. HEC working process depends upon the splitting of H2O molecules with different metal oxides. Low-cost Al2O3 based hydroelectric cell has been fabricated to generate green electrical energy. Solid state sintering method was adopted for the preparation of Al2O3 sample for hydroelectric cell. Phase formation and structural information of the sample were investigated by X-ray diffraction analysis and Fourier transform infrared spectroscopy. A circular pellet of diameter 2-inch was prepared to examine hydroelectric properties and a circular pellet of diameter 10 mm was prepared for the study of conduction phenomenon of dissociated ions in the cell. The maximum voltage ~ 0.925 V, maximum current ~ 8.02 mA, and maximum power ~ 7.42 mW was obtained for the low-cost Al2O3 based hydroelectric cell. DC conductivity measurement confirmed the dissociation of water molecules and their conduction phenomenon. Al2O3 based hydroelectric cell provides us green energy with eco-friendly byproducts without any usage of acid/alkali/photocatalytic activity/electrolyte. Moreover, presented Al2O3 based hydroelectric cell can resolve the problem of industrial waste containing of alumina.

Potential contributions of wind and solar power to China's carbon neutrality

China's goal of being carbon-neutral by 2060 requires a green electric power system dominated by renewable energy. However, the potential of wind and solar alone to power China remains unclear, hindering the holistic layout of the energy development plan. Here, after taking temporal matching of supply and demand (60 min), land use, and government policy into account and assuming lossless transmission, we demonstrate that deploying wind and solar capacity of 2495 and 2674 GW, respectively, within flexible and optimized grids can meet ∼67% of electricity demands by all society sectors for 2050 (∼6.3% curtailment rate), even without other costly power sources or storage. Spatially explicit configurations of the grids are provided simultaneously to support this achievement. The resulting green electricity supply of 10.4 PWh per year help secure China's carbon-neutral goal and reduces 2.08 Mt SO2 and 1.97 Mt NOx emissions annually. Our findings recommend policymakers accelerate exploiting complementary wind and solar power as the dominant source of energy.

METHODOLOGICAL APPROACH TO ASSESSING THE MANAGEMENT MODEL OF PROMOTING GREEN ENERGY SERVICES IN THE CONTEXT OF DEVELOPMENT SMART ENERGY GRIDS

Abstract. The transformation of the energy sector towards the development of the green energy sector provides a transition to climate-neutral economic development. In the presence of reserves of natural energy sources, a tendency towards a decrease in their use is monitored as a result of an increase in the share of consumption of green energy obtained from renewable energy sources (e.g. solar, wind). Taking this into account, the role of building an effective management model for the provision of green energy services is growing. The article proposes a methodological approach to assessing the effectiveness of the management model for promoting green energy services in the context of smart energy network development, based on the use of optimization methods and models. The promoting chain of green energy services is based on the rating assessment of energy service companies, the level of digitalization of business processes of enterprises and the formation of digital skills among consumers of various segments of the energy market, as well as a cybernetic approach to determining the ability to provide innovative energy services. For this, the peculiarities of artificial intelligence integration into socio-economic processes and the smart energy network constructions have been identified. The analysis of digital technology use level in the promotion of green energy services in the energy market of Ukraine is carried out. The determination of optimization criteria for assessing the effectiveness of the management model for promoting green energy services has been established. The determination of the optimization criteria for assessing the management model is based on obtaining an ecological effect, which made it possible to single out such criteria as maximizing the decarbonization rate of the environment and minimizing energy consumption costs. The using of such a methodological approach to assessing the effectiveness of the management model for promoting green energy services at energy enterprises will help to ensure a balance between production, distribution, supply of green energy and rational consumption of energy by different segments of consumers. Keywords: energy efficiency, energy saving, alternative energy, renewable energy sources, green electric power industry, energy enterprises, decarbonization. JEL Classification D29, L19, M31, Q21, Q40 Formulas: 10; fig.: 1; tabl.: 1; bibl.: 19.

Green hydrogen and electrical power production through the integration of CO2 capturing from biogas: Process optimization and dynamic control

This study describes the optimization of a modelling process concerning biogas’ use to generate green hydrogen and electrical power. The Aspen Plus simulation tool is used to model the procedure, and the approach employed to limit the emissions of gas from the hydrogen production process will be the CO2 capture method. This technique uses slack lime (Ca(OH)2) to absorb CO2 capture since it is readily available. The study analyzes many critical parameters in the process, including the temperature and pressure in the steam reforming (SR) and the water gas shift (WGS) reactions along with the steam to carbon ratio (S/C) to determine how the production of green hydrogen and electrical power will be influenced. Electricity generation is achieved by taking the residual water from the SR, WGS, carbonation reactions and converting it to the vapour phase, allowing the steam to pass through the turbine to generate electricity. To examine the effects of the synchronized critical parameters, response surface methodology (RSM) was used, thus allowing the optimal operational conditions to be determined in the form of an optimized zone for operation. The result of parameter optimization gave the maximum green hydrogen production of 211.46 kmol/hr, and electric power production of 2,311.68 kWh, representing increases of 34.86% and 5.62%, respectively when using 100 kmol/hr of biogas. In addition, control structures were also built to control the reactors’ temperature in the dynamic section. The tuning parameters can control the SR and WGS system’s reactor to maintain the system in approximately 0.29 h and 0.32 h, respectively.

Research on Prediction Method of Distribution Network Activity in Green Electric Power through PSO-WNN

The convergence and prediction accuracy of the artificial neural network prediction model are affected by the initial parameter settings of the model, and the wavelet neural network (WNN) modeling algorithm can effectively overcome this defect and achieve better prediction results. In this paper, the particle swarm optimization (PSO) algorithm is used to optimize the initial weights, and the optimal value of the particle swarm algorithm is assigned to the WNN to replace the initial random assignment of the WNN. The WNN is trained according to the backpropagation (BP) algorithm until convergence. The particle swarm optimization wavelet neural network (PSO-WNN) model is used to predict the cost of a single grid activity based on the cost driver parameters of the power grid. The prediction error analysis shows that the model significantly improves the accuracy of the activity cost prediction, which is beneficial to the grid enterprise to effectively manage the cost drivers and track the specific effects of the grid activity cost which produced by the driver parameters.

Titanium oxide nanowire clots with two-phase composition as multi-effect sulfur reservoirs for lithium-sulfur batteries

Lithium-sulfur battery (LSB) is one of the most promising battery systems for green energy plants and electric vehicle power sources. A high-performance sulfur reservoir is one of the most critical components for LSBs to protect the soluble lithium polysulfides (LPSs) from shuttling to lithium anode. Herein, titanium oxide nanowire clots (TOCs) with a two-phase composition and high effective absorption surface area (270.1 m2g−1) are designed as promising reservoirs to accommodate sulfur and LPSs. The synergistic effects generated from the unique structure of TOCs make the obtained S/TOCs cathode materials exhibit high specific capacity, high coulombic efficiency, and excellent cyclic stability at 1C and 2C rates. The corresponding capacity fading rates per cycle are around 0.14% and 0.11 % for the LSBs being (dis)charged 1C and 2C, respectively.

A streamlined 17-level cascaded H-bridge multilevel converter with solar PV integration

The quest for a green electrical power system has increased the use of renewable energy resources and power electronic converters in the existing power system. These power electronic converters, however, are a major cause of harmonics and result in the degradation of power quality. In the last two decades, researchers have proposed various designs of multilevel converters to minimize these harmonic distortions, however, a comprehensive solution for stand-alone solar photovoltaic (PV) systems with low total harmonic distortion (THD) is still missing in the present body of knowledge. This paper proposes a single-phase 17-level cascaded H-bridge multilevel converter (CHMC) model for a stand-alone system using solar PV arrays. The proposed model employs eight different flexible PV arrays that can be replaced with DC voltage sources when required to meet the load demand. The proposed model does not include any capacitor and filter thus saving a lot of cost in the overall system. The model has been implemented in the Simulink environment using a model-based design approach. The simulation results show that the proposed model has reduced the THD to almost 7% as compared to the existing models. The cost comparison of the proposed converter also proved its economic benefit over other types.

Analysis and Countermeasures of China’s Green Electric Power Development

The green development of electric power is a key measure to alleviate the shortage of energy supply, adjust the energy structure, reduce environmental pollution and improve energy efficiency. Firstly, the situation and challenges of China’s power green development is analyzed. On this basis, the power green development models are categorized into two typical research objects, which are multi-energy synergy mode, represented by integrated energy systems, and multi-energy combination mode with clean energy participation. The key points of the green power development model with the consumption of new energy as the core are reviewed, and then China’s exploration of the power green development system and the latest research results are reviewed. Finally, the key scientific issues facing China’s power green development are summarized and put forward targeted countermeasures and suggestions.

Titanium Oxide Nanowire Clots with Two Phase Composition as Multi-Effect Sulfur Reservoirs for Lithium-Sulfur Batteries

Lithium sulfur batteries (LSBs) is one of the most promising battery systems for both green energy plants and electric vehicles power sources. High performance sulfur reservoirs have been considered as the most important component for LSBs to protect the soluble lithium polysulfides (LPSs) from shuttling to lithium anode. Herein, a desired titanium oxide nanowires clots (TOCs) with a two phase composition and high effective absorption surface area (270.1 m2g-1) is developed as the promising LPSs’ reservoirs for the accommodation of sulfur and LPSs. Benefitted from the synergistic effect generated from the unique structure of TOCs, the obtained S/TOCs cathode materials exhibit high specific capacity, high coulombic efficiency and excellent cyclic stability at 1C and 2C rate. The corresponding capacity fading rate of each cycle is only ~0.14% and 0.11 % for the LSBs being (dis)charged 1C and 2C, respectively.

Demand Responsive Market Decision-Makings and Electricity Pricing Scheme Design in Low-Carbon Energy System Environment

The two-way interaction between smart grid and customers will continuously play an important role in enhancing the overall efficiency of the green and low-carbon electric power industry and properly accommodating intermittent renewable energy resources. Thus far, the existing electricity pricing mechanisms hardly match the technical properties of smart grid; neither can they facilitate increasing end users participating in the electricity market. In this paper, several relevant models and novel methods are proposed for pricing scheme design as well as to achieve optimal decision-makings for market participants, in which the mechanisms behind are compatible with demand response operation of end users in the smart grid. The electric vehicles and prosumers are jointly considered by complying with the technical constraints and intrinsic economic interests. Based on the demand response of controllable loads, the real-time pricing, rewarding pricing and insurance pricing methods are proposed for the retailers and their bidding decisions for the wholesale market are also presented to increase the penetration level of renewable energy. The proposed demand response oriented electricity pricing scheme can provide some useful operational references on the cooperative operation of controllable loads and renewable energy through the feasible retail and wholesale market pricing methods, and thereby enhancing the development of the low-carbon energy system.

Maximizing Power Generation of a Solar PV System for a Potential Application at Musselwhite Gold Mine Site in Northwestern Ontario, Canada

Increasing global concern for greenhouse gas emission, air pollution, fossil fuel prices, and electricity demand has generated a significant increase in research of promising renewable energy technologies for green electrical power generation. Solar photovoltaic (PV) systems are known for their capabilities to directly convert renewable solar energy into electrical energy for locations with abundant solar energy where there is a desperate need and demand for electrical power. This includes mining industries in remote locations. Solar PV systems generate more power if they are installed and operated efficiently. The inclination angle at which a PV panel is tilted from the horizontal plane is one of the most influential system parameters that affect the amount of electrical power output from the PV system and the system’s overall efficiency. Typically, the variation in the PV tilt angle determines the amount of incident solar radiation received on a PV panel to be utilized by a connected electrical load for use at a given site. In this paper, a mathematical model with numerical simulations are used to determine the total solar radiation incident on a tilted PV surface and to predict the optimum tilt angle for maximizing power generation from a solar PV system for potential application in Musselwhite Mine located in the remote northwestern region of Ontario, Canada. The total solar energy received on the optimally tilted PV surface is computed for all months in a year at the Musselwhite mine site. The results show that the monthly average optimum tilt angle of the PV system varied from a minimum value of 4o in the month of June to a maximum value of 74o in the months of January and December. It was also found that the highest maximum incident radiation of approximately 22.89 MJ/m2 for the whole year occurred in the month of April, whereas approximately 43.9% of this value (the lowest in the year) occurred in the month of December. The numerical simulation results suggest that PV systems are best be installed directly facing south at a fixed optimum tilt angle of 43o throughout the year at the Musselwhitemine site. This will improve the overall efficiency and save operating cost of the proposed PV system which in turn improves the commercial feasibility for the mining industry as an example of application.

Jaya Learning-Based Optimization for Optimal Sizing of Stand-Alone Photovoltaic, Wind Turbine, and Battery Systems

Renewable energy sources (RESs) are considered to be reliable and green electric power generation sources. Photovoltaics (PVs) and wind turbines (WTs) are used to provide electricity in remote areas. Optimal sizing of hybrid RESs is a vital challenge in a stand-alone environment. The meta-heuristic algorithms proposed in the past are dependent on algorithm-specific parameters for achieving an optimal solution. This paper proposes a hybrid algorithm of Jaya and a teaching–learning-based optimization (TLBO) named the JLBO algorithm for the optimal unit sizing of a PV–WT–battery hybrid system to satisfy the consumer’s load at minimal total annual cost (TAC). The reliability of the system is considered by a maximum allowable loss of power supply probability (LPSP max ) concept. The results obtained from the JLBO algorithm are compared with the original Jaya, TLBO, and genetic algorithms. The JLBO results show superior performance in terms of TAC, and the PV–WT–battery hybrid system is found to be the most economical scenario. This system provides a cost-effective solution for all proposed LPSP max values as compared with PV–battery and WT–battery systems.

Performance analysis of PI and Fractional order PI Controlled Quadratic Boost Converter System using MATLAB/Simulink

The depletion in the fossil fuel and increase in global warming has shifted the focus of researchers to green alternative energy. Wind power electrical generation is one such alternative where the kinetic energy of wind power is harnessed to generate green electrical power. India, being the fourth largest wind power generator has attracted numerous researchers towards the improvement of wind energy conversion system. This paper also presents improved controller techniques for a Permanent Magnet Synchronous generator (PMSG) based wind turbine coupled with Cascaded Quadratic Boost Converter (QBC) and Space Vector Modulation (SVM) based inverter. The digital simulation and execution of PMSG based wind turbine a long with QB Converter and SVM Inverter in a closed loop is presented. The closed loop is realized using Proportional Integral (PI) and Fractional Order Proportional Integral (FOPI) controllers. Initially, the AC power from PMSG wind turbine is converted to DC using bridge rectifier. The DC output from the rectifier is then boosted to the required level using quadratic boost converter. The output from QB converter is then fed to the SVM inverter. The closed loop investigations are carried with PI and FOPI controllers. The simulation results of both PI and FOPI controlled QBC are compared. The outcome of FOPI controller represents that the steady state error and settling time are reduced when compared to PI-controlled closed loop quadratic boost converter.

High Temperature Electrolysis: Combining Metal Extraction and Energy Storage?

The promise of deploying green electric power faces the challenge of intermittency and integration within existing infrastructure. Meanwhile the global demand for metals, whether from primary or recycled sources, is steadily growing. The processes of the latter sector are not currently able to utilize a surge in inexpensive, clean electricity while being a large energy consumer (of the scale of 20 to 100MW). A window of opportunity exists where metal processing technologies can be re-designed to act as an electricity consumer or producer, depending on the electricity market conditions. In this work, we analyze and discuss conditions in which high temperature electrolysis techniques can fulfill this role.

Performance enhancement of wind energy harvester utilizing wake flow induced by double upstream flat-plates

Small-scale wind energy harvesting system is being considered to provide green long-term electric power to unattended sensor network nodes which are widely used in urban and natural environments. This paper proposes that placing a double-plate structure upstream of the bluff body in the wind energy harvesting system can significantly improve the output performance. At a certain wind speed, two wake flow zones with low-pressure are formed behind two upstream side-by-side plates, which induced the bluff body at the downstream intermediate position to deviate to both sides. Even at a low wind speed, the vibration of bluff body can still occur because the pressure fluctuation of the wake zone disturb the static equilibrium. Placing the double plates upstream of a wind energy harvester with a cylinder can change the vibration response from VIV (vortex-induced vibration) to galloping. Moreover, when the ratios of the horizontal and vertical distances to the windward width of the cylinder are 1 and 0.5, respectively, the cut-in wind speed is as low as 1.5 m/s. For the galloping-based wind energy harvester with a square prism, after the double plates are placed upstream, the cut-in wind speed decreases from 3.5 m/s to 1 m/s and the output voltage increases from 1 V to 12 V at 1.5 m/s. The increase of voltage caused by the addition of double plates to the upstream of six different bluff bodies indicates the good adaptability of this structure. The higher voltage output capability by this method at low wind speed significantly expands the application scope of wind energy harvesters.

Power Quality Improvement in a Grid Coupled Solar PV System using Grey Wolf Optimization

Since the PV penetration in the utility grid is increasing rapidly, there is a need of a control strategy for the purpose of energy optimization and for providing clean and green electric power to the utility grid. In this paper, a dynamic technique is proposed employing a Fractional Order PI controller tuned using Grey Wolf Optimization Technique. The strategy provides the independent control active as well as reactive power being injected into the grid. A complete investigation on performance analysis and THD levels at different solar irradiation value were conducted on MATLAB/SIMULINK software. The efficacy of the work is validated by comparing the results obtained by using Grey Wolf Optimization with permissible IEEE standards and the observations proves the power quality improvement by reducing the THD i.e. Total Harmonic Distortion levels.

Electrolytic splitting of saline water: Durable nickel oxide anode for selective oxygen evolution

Increasing generation of renewable electricity offers a source of green electric power, which can be exploited for the sustainable production of hydrogen through the electrolysis of water. Scarcity of fresh water resources promotes the search for electrode materials, which could be used for splitting of saline water into hydrogen and oxygen without formation of hazardous chlorine compounds, and also withstand highly aggressive chloride medium. In the present study we demonstrate that nickel oxide layer formed by means of simple spray-pyrolysis technique on conductive glass substrate can be used as corrosion resistant and 100% O2-selective anode for the electrolysis of alkaline (pH 14) chloride solution. Dimensional stability and durability of the anode is secured by the absence of metallic phase, whereas selectivity towards oxygen evolution and absence of chloride oxidation is shown to be controlled thermodynamically. The obtained experimental evidence that hydrogen peroxide is formed as intermediate in oxygen evolution reaction under conditions investigated has led to new mechanistic insights and the mechanism of Ni(IV)-mediated electrocatalytic oxidation of water molecules in alkaline chloride medium has been proposed.

Regional goods delivery: How to reduce its CO2-, NOx- and PM10-emissions?

Regional goods delivery fulfils an essential socio-economic function, in particular, in dense urbanized areas in countries like The Netherlands. Shippers (producers or traders), transport service providers, businesses and private households favour road transport, because of logistic and financial reasons. Delivery and pick-up vehicles are mainly powered by internal combustion engines (ICE). ICE is a major source of ambient air pollution by NOx and PM10 and of global warming (CO2). More recent and well-maintained engines have much lower emissions of NOX and PM10 than older and less well maintained ones, but their CO2-emission has not been reduced as much. With (local) freight transport growing exponentially, these emissions are likely to rise. The aim of the paper is to estimate how a combination of logistic, technical and policy choices may reduce emissions of CO2, NOX and PM10. The authors follow an integrative, interdisciplinary approach, because the past has taught that align- ment of decisions by companies and government is inevitable to effectively deal with the root causes of these emissions. The main research question is as follows: What is needed to reduce the key emissions by regional goods delivery? This was addressed by literature analysis and micro simulation. The lat- ter was used to compare the emissions of diesel, CNG and electricity to power trucks and truck-vans combinations in a region to inner-city delivery scenario. CNG is currently the better option in terms of emissions for the whole trip, largely because of the Dutch grey electric power mix. Replacing the city leg of the trip by vans leads to more emissions, more vehicles, higher parking needs and logistic complexity. Full electric trucks and vans cut out the local air pollution, which is beneficial, but not the emissions by power plants. A green(er) electric power mix is necessary to go to zero emission regional goods delivery.