39 research outputs found
Comparative analysis of high voltage alternating current & high voltage direct current offshore collection grid systems
No full textA dissertation submitted in fulfilment of the requirements for the Master of Engineering: Electrical Power Engineering, Faculty of Engineering and the Built Environment, Durban University of Technology, 2021.An increase in industries as well as the world’s population, is causing a strain on the
electricity supply. This coupled with the fact that fossil fuel supplies are decreasing, is
leading the world to new, greener methods of electrical energy generation. Offshore wind
farms are being developed far offshore and solar farms are being developed in remote
locations with intense sunlight. This allows for the optimal operation of these systems.
HVAC collection systems for offshore wind farms have traditionally been used but
imposes limitations on the transmission distance. Exuberant amounts of capital are
required for greater distances. HVDC systems have started to be recognised as a viable
method of transmitting this electrical energy at a much lower cost on longer distances.
This study shows a comparative performance and cost evaluation of both HVAC and
HVDC collection systems for offshore wind farms. It evaluates the efficiency of the wind
farm based on system losses, determines the advantages, disadvantages, and cost
implications of each system, and determines the best type of technology to be used in
offshore applications. The study looks at a case of a 40 MW wind farm at a distance of
120 km offshore. A simulation is developed for each system using MATLAB simulation
software to determine the performance of each system during normal operation and fault
conditions. From these simulations, it was found that HVDC collection systems have
much higher efficiency when compared to HVAC systems and perform better under both
normal operation and fault conditions. HVDC systems also have a lower cost once the
break-even distance point is passed. From the study, it is found that HVDC collection
systems are much better suited to allow offshore wind farms to have a high efficiency as
well as be located further offshore to allow for maximum wind usage. The technology
can be used for other long-distance transmission systems and incorporated for other
renewable energy generation systems.
Performance evaluation of control strategies for grid connected wind power generator
No full textDissertation submitted in fulfillment of the requirements for the degree of Master of Engineering: Electrical Power Engineering, Durban University of Technology, Durban, South Africa, 2022.South Africa is currently experiencing a significant load-shedding situation because of
rising electricity demand. The renewable energy power producer (RPP) sector is
growing rapidly to become an important source of power in South Africa and nations
across the globe. Companies within this sector provide a variety of clean energy
sources, including wind, solar, hydroelectric, biomass and geothermal. Despite its
ability to support the power system and conserve the environment that sustains life,
the rising usage of renewable distributed generators (RDGs) poses power quality
problems in the overall distribution network, such as the voltage instability at buses,
the increase in voltage/current harmonics distortions, etc. The technical requirements
for connecting RDGs to the power system have been defined in standard grid code to
ensure the safe, secure and proper functioning of the overall power system. The
specifications defined in the grid code include the limit of voltage variations (i.e., +/-1
pu), the limit of frequency variations (i.e., +/-5%), and the limit of current/voltage
harmonic distortions (i.e., total harmonic distortion voltage (THDv) of 0.1% and total
harmonic distortion current (THDi) of 5%), and a power factor limit of Pf = (0.9-0.95).
Additionally, RDGs must remain connected throughout a fault condition and assist in
voltage recovery.
In this dissertation, control strategies for grid connected wind energy conversion
system (WECS) are investigated for dynamic performance evaluation. This work
focuses on the doubly fed induction generator (DFIG) – based WECS incorporating a
proportional integral (PI) controller; the permanent magnet synchronous generator
(PMSG) – based WECS incorporating a PI controller; DFIGb-based WECS
incorporating a voltage source converter (VSC) with a fuzzy-logic controller, the
proportional integral derivative (PID), and fuzzy-PID controller. A comparative
analysis of the different WECS topologies was further conducted in terms of the
steady-state error, the percentage overshoot, and the settling time of the
voltage/current or power output signals and dc-link voltage signals.The VSC was
selected as compared to the line-commutated converters (LCCs) because of the
commutation that is not dependent on voltage and current AC signals. The grid-side
converter was applied to regulate DC-link voltage and reactive power to their reference
values. The rotor side converter provided rotor speed regulation on the DFIG to control the power output signal. The vector control method was used for the dynamic
performance analysis. The simulations were done using MATLAB/SIMULINK. From
the simulation results, it was found that the DFIG-based WECS incorporating a fuzzyPID controller performed efficiently compared to the other topologies of WECS.
Optimising post-harvest farm yield through utilization of a machine learning based-fruit disease classification model
Get PDFA thesis submitted in fulfillment of the requirements for the Doctor of Engineering: Electrical Power Engineering, Durban University of Technology, Durban, South Africa, 2023.This research study proposed 4 key improvements to the classical fruit disease detection models which have been proven to increase their classification and accuracy levels. The globe and, more particularly, the economically developed regions of the world are currently in the era of the Fourth Industrial Revolution (4IR). Conversely, the economically developing regions in the world (and more particularly, the African continent) have not yet even fully passed through the Third Industrial Revolution (3IR) wave. Moreover, Africa’s economy is still heavily dependent on the agricultural field. On the other hand, the state of global food insecurity is worsening on an annual basis due to exponential growth in the global human population, which continuously heightens food demand in both quantity and quality. This justifies the significance of the focus on digitizing agricultural practices to improve farm yield to meet the global steep food demand and stabilize the economies of the African continent and countries such as India that are largely dependent on the agricultural sector for revenues. Technological advances in precision agriculture are already improving farm yields, especially in the more economically developed regions of the globe, although several opportunities for further improvement still exist. Hence, this study evaluated a particular area of precision agriculture, the plant disease detection models which fall under decision support systems. The aim was to gauge the status of the research in this field, identify opportunities for further research, and propose technical amendments to the traditional plant disease detection models to improve their functional efficiency and accuracy. Hence, through reviewing the available literature, this study has realized the dearth of literature focused on the real-time monitoring of the onset signs of diseases before they spread throughout the whole plant. There is also substantially less focus on real-time mitigation measures such as actuation operations, spraying pesticides, spraying fertilizers, etc., once a disease is identified. Very little research has focused on the combination of monitoring and phenotyping functions into one model capable of multiple tasks. Most of the proposed plant disease classification models are based on a 2-Dimensional ‘view’ of the sample, which might pose challenges in the case of spherical or cylindrical plant samples such as fruits. Therefore, four key proposals were made in this research study. Proposal 1 was an improved image pre-processing technique for Machine Learning-based plant disease classification models. This technique dissolves a Red-Green-Blue (RGB) image into individual red, green and blue planes and performs the thresholding process on one or more planes and superimposes the resulting binary images. This has proven to yield better feature segmentation depending on the application. Proposals 2 and 3 aimed to grant a classification model a ‘3-Dimensional view’ of the sample to eliminate any ‘blind spot’ which might be hiding important features that would directly impact the classification decision had they not been hidden. Proposal 2 achieved this by using multiple input image cameras, while Proposal 3 employed a revolving sample stand that allows a single input camera to take multiple input images (at different angles) from the sample. Proposals 2 and 3 were tested in classifying healthy from black rot-affected oranges, and they outperformed the traditional plant disease detection model by classifying correctly even the oranges with small and uneven distribution of black rot. Proposal 4 combined crucial processes that are traditionally stand-alone in farming operation into a single hybrid model, hence the Hybrid Fruit Disease-Quality Monitoring and Sorting Model. This model offers post-harvest benefits and has also been conceptualized based on fruit plant samples. This model could detect diseases; perform quality checks (punchers, skin pills, etc.); perform grading based on these quality checks; and sort the fruits into designated bins according to their assigned class. It aims to lower the price of digital farming technology and avail it to low-budget farms. This model was tested on oranges (healthy, black rot-affected, and generally damaged) and apples (healthy, botch-affected, and generally damaged). The model managed to classify each of these diseases; perform the quality check based on the general fruit damages; and sort/grade (conceptually) these fruits according to these different classes. Its classification accuracy was 100% since all the test samples were classified correctly. Although proposals 3 and 4 of this study were electromechanical systems, their modelling and testing have been limited to the electrical aspect. A full electromechanical design still needs to be implemented for a full capability study to be done in practical settings. Another limitation of this study was collecting the fruit samples with the desired disease symptoms distribution. The test samples were collected from the local vendors and the variety was greatly limited.
Optimal placement of large-scale electric vehicle and distributed generation in power system to enhance power quality
No full textThesis submitted in fulfillment of the requirements for the degree of Doctor of Engineering: Electrical Power Engineering, Durban University of Technology, Durban, South Africa, 2024.The widespread adoption of electric vehicles (EVs) and renewable distributed generators
(REDGs), including photovoltaic (PV) systems and wind turbine generators, has garnered
significant attention in global power systems. These energy sources are recognized as
environmentally friendly. However, substantial integration of EVs and REDGs can lead to
voltage fluctuations that exceed acceptable limits and result in reverse power flows at
interconnection points within the power grid. Such excessive voltage variations can adversely
affect consumer electric loads, while reverse power flows can disrupt the overall power
transmission system. Consequently, the extensive integration of EVs and REDGs poses
challenges for both consumers and power utilities. To address these issues, previous studies
have suggested reactive power control strategies, such as employing power electronic
converters linked to distributed generations (DGs) to mitigate voltage deviations. This research
proposes a method for the optimal integration of EVs through bidirectional charging and
REDGs within power systems, aiming to effectively manage voltage, active power, and
reactive power flows at interconnection points. Additionally, it involves identifying suitable
locations and sizes for electric vehicle charging stations and calculating associated system
costs. The control objectives are framed as an optimization problem, which is addressed using
a hybrid genetic algorithm combined with an improved particle swarm optimization algorithm
(HGAIPSO).
The research was structured into three distinct sections, with the efficacy of the proposed
methodology illustrated through numerical simulations conducted in MATLAB. The initial
section focused on identifying the optimal location for the charging station and the appropriate
number of electric vehicles (EVs) per charging station within the power system, utilizing the
GA, PSO, IPSO, and HGAIPSO algorithms. This analysis was performed on an IEEE-30 bus
system. The simulation outcomes from this initial case revealed that the strategic placement
and coordination of EV charging stations, as facilitated by the HGAIPSO algorithm, led to a
reduction in power losses, an enhancement of voltage profiles, and an overall improvement in
power quality. Specifically, the results indicated a decrease in real power loss of 40.70%,
36.24%, and 42.94% for types 1, 2, and 3 of EV allocation, respectively, while the voltage
profile at the buses improved to approximately 1.01 pu. The second section involved the allocation of EVs to function as loads in a grid-to-vehicle
(G2V) system and as generators in a vehicle-to-grid (V2G) system, in conjunction with
renewable energy distributed generators (REDGs). This was tested on a more advanced
distribution network, specifically the IEEE-118 bus test system, employing the HGAIPSO
algorithm. The simulation results indicated that the proposed HGAIPSO method significantly
improves power quality and reduces the overall installation costs when compared to the
baseline scenario.
The final section provided a comparative analysis regarding computation time and iterations
between the proposed HGAIPSO and various other optimization techniques, including GA,
PSO, and IPSO. This analysis was conducted on the IEEE-118 bus system with the allocation
of V2G, G2V, and REDGs. The simulation results demonstrated that the proposed HGAIPSO
method is faster and more effective in terms of computation time for complex networks,
achieving optimal solutions more efficiently
Voltage rise mitigation at the point of common coupling of large renewable distributed generation and distribution network
No full textThesis submitted in the fulfilment of the requirements of the degree of Doctor of Engineering in Electrical Engineering, Durban University of Technology, 2022.A lot of changes are taking place in the power system as a result of the introduction of
Renewable Distributed Generation (RDG) (e.g., wind and PV systems). Gradually,
electricity generated by fossil fuel is being replaced by electricity generated from
Renewable Energy Sources (RESs). The deregulation of generation, transmission, and
distribution systems due to the introduction of RDGs has brought competition to the
electricity market. The electricity generation assets are no longer owned by one or a few
owners, as investors have been attracted to the electricity market. Individuals can now
generate their own electricity from renewable energy sources such as solar, wind, hydro,
wave, tide, and geothermal etc. RDGs are predicted to play a crucial role in the power
system transformation in the near future; they are the key to a sustainable energy supply
infrastructure because of their inexhaustible and non-polluting nature. However, the
integration of RDGs into the power system would have an impact on power system
planning, voltage profiles and power quality requirements within the Distribution Network
(DN). The voltage rise (or over-voltages) at the busbars within the conventional power
system with centralized large power generating units are actually of less concern due to
advances in control and protection technologies, but the issue of excessive voltage drop
at the far end of transmission lines cannot be overemphasized. The introduction of RDGs
into the power system has eliminated the occurrences of the severe under voltage at the
far end of transmission lines, but the voltage rise effects and the bidirectional power flow
issues at the point of common couplings (PCCs) between RDGs and DN are now of major
concern. Indeed, the integration of RDGs can make the power system become
bidirectional as electricity can flow from RDGs as well as from DN with a centralised
generator. This causes various problems with regards to the power quality, power flow
control, frequency control, system voltage profile, etc. Furthermore, the voltage rise
effects at PCC with connected-RDG has been a noticeable issue in recent years and
requires remedial action. The standard grid code requires that output parameters of
RDGs (i.e., voltage profile, current, voltage-current harmonic distortions, power factor,
frequency, etc.) at PCC shall be regulated to avoid damage to sensitive equipment
connected to the DN, meet up with the power quality criteria, and shall continue providing
power support to the DN. Hence, this study focuses on the following two main problems: – firstly, the voltage rise effect, and secondly, the bidirectional power flow constraint at
the PCC between RDGs and DN.
The analysis and simulations in this thesis are conducted on an IEEE 13-bus sample
model and DUT Steve Biko network with penetration of a large RDG. The capacity of the
RDG integrated to DN is 1 MW (solar PV). In order to investigate the effect of voltage rise
and bidirectional power flow in a DN, a mathematical model of a power distribution
network connected with RDG is developed. Intensive simulations are carried out using
MATLAB/Simulink software. Furthermore, a control strategy is recommended at PCC for
mitigating or minimizing the impacts of voltage rise and reverse power flow when
operating at a worst critical scenario, such as minimum load and maximum generation.
The control structure consists of the installation of a static compensator (STATCOM) with
Pulse Width Modulation (PWM), and the block/deblock and in-loop filtering circuit control
scheme to control the active and reactive power. The proposed control strategy also
mitigates the voltage-current harmonic distortions, improves the power factor and voltage
stability at PCC, and also protects the converter-PWM scheme from grid disturbances
and fault currents, as the control of active and reactive power is independent of the grid.
This thesis also provides a review of various types of renewable energy resources (RERs)
prospects in Africa, looking at how they can be deployed faster within the continent. The
thesis also analyses power quality and compensators.
Kernel estimation modelling and optimization of hybrid power system for a typical South African rural area
No full textA dissertation submitted in fulfillment of the requirements for the degree of Master of Engineering in Electrical Power Engineering, Durban University of Technology, Durban, South Africa, 2022.To increase the accessibility of electricity even to those rural sparsely scattered isolated rural regions, renewable energy seems to be a viable and sustainable option. Before investing in renewables in these areas, a feasibility study is of paramount importance starting with assessing and determining the amount of available solar irradiance and wind speeds for the area. In addition, a techno-economic feasibility study is of paramount importance to determine the most economical and sustainable standalone hybrid system. This research presents a study using a nonparametric kernel density estimation method to determine solar irradiance and wind speeds. In addition to this kernel determination method, the study performs a feasibility analysis using a hybrid renewable energy system that consists of two renewables with biodiesel and battery backup to supply the energy demands of a rural household in South Africa. The research commences with a literature review of several probability distribution functions (pdfs) commonly used in testing both solar irradiance and wind speeds. It established that not all sites can be defined by the same pdf and there is no science in selecting a distribution function but rather random testing of a range of functions. The parametric probability functions tested in this work are Gamma, Weibull, and Lognormal. The work then compares the performance of these parametric pdfs with the nonparametric kernel density estimation method which this study advocates for its application. In judging the performance and correctness of these pdfs, mean bias error (mbe) and root mean square error (rmse) are used as performance test criteria for the parametric probability distribution function. As for the nonparametric pdf which this research advocates for its use, an integral squared error, ISE is used for the presentation assessment with the conventional parametric normal distribution. From the results, it is observed with the proposed nonparametric kernel density estimator gives precise estimation and improved adaptableness, as opposed to the widely used conventional parametric distribution for both the use in solar irradiation and wind, speeds estimations. In addition, the research results demonstrated that the commonly used Epanechnikov and Gaussian KDE methods were the most adjustable methods for all seven tested stations. The second aspect of the study applies the tested data to design and perform a feasibility study of using a hybrid renewable energy system that consists of two renewables with biodiesel and battery backup to supply energy demands for a typical rural household. Thus, the study makes use of a simulation to design and determine an optimized hybrid renewable energy system for application in rural households. The energy resources considered for this standalone hybrid system are solar PV, wind, diesel generator, and a storage battery system. In performing the system simulation and optimization concerning economic viability, sustainability, energy efficiency, and environmental impact is carried out using the Hybrid Optimization Model for Electric Renewables (HOMER) simulation and optimization software tool. Concerning the results obtained, HOMER gave seven best-optimized systems. In breaking down the seven optimized results, four of the results were hybrid energy systems and three with only one energy resource. Moreover, from these results, three systems were pure green energy supplied and not utilizing any diesel generator (DG). The best-optimized system for this rural household consisted of PV/DG with an NPC of 79,272. The use of only renewable resources for this region was fourth-ranked with NPC of $ 86,760. The study demonstrates the feasibility and viability of having rural areas benefit from electricity access. Moreover, this study will contribute towards the strides of just energy transition envisaged by the country in solving the energy crisis currently being experienced.
Power loss minimization and voltage profile improvement in transmission networks using a network modification algorithm
No full textDissertation submitted in fulfillment of the requirements for the degree of Master of Engineering: Electrical Power Engineering, Durban University of Technology, Durban, South Africa, 2022.A number of algorithms that aim to reduce power system losses and improve voltage profiles by
optimizing distributed generator (DG) location and size have already been proposed, but they are
still subject to several limitations. Hence, new algorithms can be developed or existing ones can
be improved so that this important issue can be addressed much more appropriately and effectively.
In their formulations, the majority of algorithms focused only on real power loss minimization.
Power systems operate with reactive power controller installed at various locations, which are
essential to their operation. Therefore, the effect of reactive power control must be taken into
consideration when optimizing DG allocation for voltage profile improvement. State-of-the-art
optimization algorithms can be used to improve the effectiveness of the existing one in taking into
account the effect of reactive power control. This study proposed a modification methodology
based on a hybrid optimization algorithm, consisting of a combination of the genetic algorithm
(GA) and the improved particle swam optimization (IPSO) algorithm m for minimizing active
power loss and maintaining the voltage magnitude at about 1 p.u. The buses at which DGs should
be injected were identified based on optimal real power loss and reactive power limit. When
applying the proposed optimization algorithm for DGs allocation in power systems, the search
space or number of iterations was reduced, increasing its convergence rate. The proposed
modification methodology was tested in an IEEE-30 bus electrical network system with DGs
allocations and the simulations were conducted using MATLAB software. The hybrid GA and
IPSO (HGAIPSO) method has less iterations and is more effective at solving optimization issues
than other optimization algorithms like GA, PSO, and IPSO. An IEEE-30 bus network system
with DGs allocations was used to evaluate the effectiveness of the proposed HGAIPSO, and the
test results were compared to those from alternative techniques (i.e. GA, PSO and IPSO). The
outcomes of the simulation demonstrate that the suggested HGAIPSO can be an effective and
promising optimization technique for issues with transmission network modification. IEEE-30 bus
test system with DGs included at various locations, Type 1, Type 2, and Type 3 DGs allocation,
respectively, showed decreases in overall real power loss of 40.7040%, 36.2403%, and 42.9406%.
For the IEEE-30 bus, the highest bus voltage profiles are up to 1.01pu.
Design and application of passive filters for improved power quality in standalone PV system
Get PDFA dissertation submitted in fulfillment of the requirements for the award of the degree of Master of Engineering in Electrical Power Engineering, Durban University of Technology, Durban, South Africa, 2024.Harmonic components have developed in power systems due to the non-linear properties of the
circuit components utilized in power electronics-based products and their rapid application. Power
systems rely on fundamental quantities like sinusoidally varying voltage and current, which
oscillate at a frequency of 50 Hz. The standard restrictions of IEEE-519-1992 were utilized as a
benchmark in this study. To generate the best output, the total harmonic distortion (THD) should
be decreased below the limit, even for certain individual harmonic numbers, and reflect the power
factor output. Using the results of the simulation and projections for each mitigation strategy, the
THDI can be reduced below the IEEE-519 standard whilst also providing cost and electrical
advantages. Analysed and modelled is the PV system, which comprises solar panels, a DC-DC
converter, a DC-AC inverter, and a non-linear load.
Passive filters are an effective solution for improving power quality in standalone photovoltaic
(PV) systems. This dissertation provides an overview of the design and application of passive
filters for this purpose. Firstly, an introduction to PV systems and the power quality issues
associated with them was preferred. Next, different types of passive filters, namely LC filters, LCL
filters and LLCL filters, are discussed along with their advantages and disadvantages, and the
design considerations for these filters, including the selection of filter components and the
calculation of filter parameters. The application of passive filters in standalone PV systems was
then discussed, including their implementation in DC-DC converters and Z-Source inverters and,
the design of PWM controllers such as the constant boost control method and simple boost control
method.
The analysis of the outcome of the engineered systems was conducted according to the IEEE
standard and SANS 10142 Standard to protect the connected equipment within the off-grid
network. The outcomes pertain to the single-phase stand-alone/off-grid photovoltaic system and
the single-phase Z-Source inverter. The Z-Source inverter is equipped with two distinct methods
for PWM control, namely the constant boost control method and the simple boost control method.
All three designs incorporate three passive filters, namely the LC filter, the LCL filter and the
LLCL filter. The results were obtained from the network consisting of three distinct designs. LLCL
demonstrates superior performance as a passive filter, substantiating its position as the optimal
choice. The optimal outcomes of a single-phase off-photovoltaic (PV) network can be achieved
using LC, LCL and LLCL filters, with corresponding percentages of 2.99%, 2.45% and 1.71% respectively. Unfiltered was 89.05%, which is not good for the equipment connected to the
network.
The Z-Source showcases the capability of voltage amplification to an infinite level, rendering it
highly effective in minimizing total harmonic distortion. This research investigation further
demonstrated the efficacy of the Z-Source Inverter with Constant Control Boost Method and
Simple Boost Control Method, achieving unfiltered total harmonic distortion levels of 38.85% and
44.96% respectively. The Z-Source inverter, when combined with the Constant Boost Control
method and Simple Boost Control method, exhibits various filter configurations such as LC, LCL,
and LLCL filters. In the context of the constant boost control and simple boost control methods, it
is imperative to assess the total harmonic distortion percentage of voltage and current for LC, LCL,
and LLCL configurations. The constant boost control voltage (LC, LCL, LLCL) and current total
harmonic distortion (LC, LCL, LLCL) are measured at 4.177%, 2.655%, 1.951%, and 2.958%,
2.09%,1.465% correspondingly. The voltage-based boost control methods, namely LC, LCL and
LLCL, exhibit total harmonic distortion levels of 2.345%, 1.920% and 0.211%, respectively.
Similarly, the current-based boost control methods, LC, LCL and LLCL, demonstrate total
harmonic distortion levels of 2.346%, 1.921%, 0.211%, and 2.346%, 1.921%, 0.211%,
respectively.
Finally, the dissertation wrapped up by exploring the potential of passive filters for enhancing
power quality in standalone PV systems. The thesis offers a comprehensive investigation of the
design and implementation of passive filters in standalone PV systems, providing valuable insights
for engineers and researchers in the field. It enhances understanding and utilization of these
imperative devices.
Comprehensive Evaluation of Waste-Derived Fuels As Sustainable Alternatives in Cement Production
Get PDFThe cement industry accounts for approximately 7–8% of global carbon dioxide (CO2) emissions, primarily due to the energy-intensive clinker production process and reliance on fossil fuels. The environmental impact of this industry is particularly evident in the release of greenhouse gas (GHG) emissions. Therefore, the industry is exploring ways to reduce its energy costs and reliance on traditional fuels and mitigate environmental concerns by using waste-derived materials as a fuel substitute for cement production. In response to increasing environmental pressures, the substitution of fossil fuels with alternative fuels (AF) such as refuse-derived fuel (RDF), biomass, sewage sludge (SS), and used tires has emerged as a viable decarbonization strategy. This paper aims to provide a comprehensive analysis of AFs within the cement industry by reviewing previous studies, focusing on their GHG emissions and the technical, environmental, and economic implications of AFs adoption in cement kilns. A structured literature analysis was employed to evaluate fuel types, heating values, thermal substitution rates, combustion stability, and their effects on clinker quality. Data trends indicate that thermal substitution rates exceeding 80% are achievable with RDF and tire-derived fuels under optimized conditions, while biomass and SS require pretreatment for stable combustion. Environmental assessments report up to 30% reduction in CO₂ emissions and significant decreases in SOx and NOx with proper blending. The review also highlights key gaps in regional adoption and long-term performance evaluations. It concludes by recommending targeted policy support, plant-specific feasibility assessments, and integrated LCA-MCDM frameworks to scale the sustainable use of Afs
Load Profile and Load Flow Analysis for a Grid System with Electric Vehicles Using a Hybrid Optimization Algorithm
No full textAs they become more widespread, electric vehicles (EVs) will require more electricity to charge. It is expected that a range of grid transportation solutions that complement one another and considerable transmission infrastructure changes will be needed to achieve this goal. Strategic planning and control, including economic models and strategies to engage and reward users, can reduce energy loss on the power network. This would eliminate grid upgrades. Bidirectional charging of EVs can help transmission systems cope with EV allocation. Power loss and voltage instability are the transmission network’s biggest issues. Adding EV units to the transmission network usually solves these problems. Therefore, EVs need the right layout and proportions. This study determined where and how many radial transmission network EVs there should be before and after the adjustment. To discover the best EV position and size before and after the dial network modification, a hybrid genetic algorithm for particle swarm optimization (HGAIPSO) was utilized. Electric vehicles coordinated in an active transmission network reduce power losses, raise voltage profiles, and improve system stability. Electric vehicles are responsible for these benefits. The simulation showed that adding EVs to the testing system reduced power waste. The system’s minimum bus voltage likewise increased. The proposed technology reduced transmission system voltage fluctuations and power losses, according to the comparison analysis. The IEEE-30 bus test system reduced real power loss by 40.70%, 36.24%, and 42.94% for the type A, type B, and type C EV allocations, respectively. The IEEE-30 bus voltage reached 1.01 pu
