I-COSTE 2024 – Page 2 – NPS Australia Submission System

Study of a Hybrid Renewable Energy System to Produce Green Energy For Cooktown – a Far North Queensland

Abstract—Australia’s pledge to net zero in 2050 has seen a
dramatic increase in the use of renewable energy systems, particularly
solar photovoltaic (PV)-wind hybrids. This study aims to optimise
a solar PV-wind hybrid system to power a polymer electrolyte
membrane (PEM) electrolyser to produce green energy for Cooktown
as a case study. This study identifies the current hybrid systems within
the literature, develops a solar PV-wind hybrid system to meet load
demands and optimises the hybrid system through HOMER, reducing
Net Present Cost (NPC) and Levelised Cost of Energy (LCOE). Results
of the project identify that an NPC of AU$56.6 million and LCOE of
AU$0.55/kWh are achievable for a solar PV-wind hybrid renewable
system powering a PEM electrolyser in Cooktown, Far North
Queensland (FNQ). However, electrical output data identifies unmet
loads and capacity shortages, indicating electrical disruptions for the
PEM electrolyser regardless of implementation location. This paper
discusses economic and performance optimisation outcomes, with green
energy and fossil fuel technologies highlighted as possible solutions to
electrical shortages. The solar PV-wind hybrid is compared with its
counterparts, which identified cost differences and electrical production
ability. In conclusion, this project has developed a solar PV-wind hybrid
renewable energy system to power a PEM electrolyser. Economic
optimisation does occur through HOMER, with substantial reductions
in NPC and LCOE. However, performance issues limit the hybrid
system’s ability to meet the electrolyser’s load demands, and further
action is needed for the system to fulfil its electrical load requirements.

Title: Leveraging Web Applications for Enhanced Transportation Mobility: Integrating Taxi Booking and Volunteer Ride Services in Fiji

The significant research contribution of this project is the development of a web-based platform that integrates real-time taxi booking, ride-sharing, and volunteer ride services tailored for Fiji. This innovative solution addresses key challenges in Fiji’s urban transportation, such as traffic congestion, vehicle overuse, and lack of affordable transport for low-income individuals. By promoting environmental sustainability, fostering community engagement through volunteer rides, and leveraging secure online payment systems, this platform contributes to enhancing mobility and reducing greenhouse gas emissions in a unique socio-economic context.

Enhancing Transient Stability in DFIG-Based Wind Energy Systems using Resistive Fault Current Limiters

This paper presents the transient stability enhancement of Doubly-Fed Induction Generator (DFIG)-based wind energy systems through the implementation of a Resistive Fault Current Limiter (RFCL). DFIG technology has gained popularity due to its ability to efficiently harness wind energy under variable conditions. However, its vulnerability to faults, particularly during symmetrical and asymmetrical disturbances, poses significant challenges to grid stability. This study investigates various internal and external control strategies, highlighting the limitations of conventional methods. The RFCL is proposed as an effective solution to mitigate fault impacts and improve system resilience. Simulation results demonstrate that integrating the RFCL significantly enhances transient stability, outperforming traditional fault current limiting approaches. This research contributes to optimizing DFIG performance and ensuring reliable wind energy generation.

Energy Management in Microgrids Using Energy Storage Systems to Enhance Reliability

This paper investigates energy management in smart microgrids by incorporating energy storage batteries to improve the operational cost efficiency and system reliability. The considered cost and reliability index are respectively the battery costs and the loss of load expectation (LOLE). Since operational indices depend on location and costs on battery capacity, the main challenge is determining the optimal capacity and installation location for batteries. To achieve both objectives, the functions are consolidated into a single overarching objective function. This problem is addressed through a novel optimization algorithm known as the Symbiotic Organisms Search (SOS) algorithm. Unlike other heuristic algorithms, the SOS algorithm requires no specific tuning parameters, allowing for faster convergence. To verify its efficiency, the algorithm’s results are compared with those of the widely recognized Genetic Algorithm (GA). A sodium-sulfur (NaS) battery is selected for this study due to its high power density, efficiency, and long life cycle. Renewable energy sources utilized in this study are in the form of wind turbines and photovoltaic (PV) cells. The proposed methodology is tested on the IEEE 33-bus system, with results confirming its practical feasibility.

Feasibility Study of Hybrid Energy System Towards Decarbonisation

To combat global greenhouse gas emissions and
ensure energy security the role of renewable energy is crucial.
Implementation of renewable energy-based hybrid energy
system at diesel-energy based remote places is vital for
decarbonization offering beneficial use of underutilised
resources. In this study a hybrid energy system is examined at
regional Australia including solar, hydrogen and bioenergy
using HOMER Pro software. To address the transportation
sector carbon emission, electric vehicle loads have been
included. Result shows, by including photovoltaic, battery, fuel
cell, and biodiesel generator with carbon-based generators can
reduce the system and the energy cost. Exclusion of carbon
based generators can provide zero carbon emission, however
with the highest cost indicating the need of cost reduction of
renewable components and renewable fuel as biodiesel and
hydrogen energy to avail the decarbonization benefits

Numerical investigation of performance, combustion and emission fuelling with hydrogen in a spark ignition engine.

Global greenhouse gas emissions resulting in
climate change are the concerns for researchers and
policymakers. As per compliance with Net Zero emissions by
2050, it is obligatory to explore sustainable fuels for internal
combustion engines. Aiming this target, a numerical model was
developed using GT-Suite software for hydrogen port injection
in a single-cylinder, four-stroke gasoline engine. The reason for
choosing hydrogen is that green hydrogen is the cleanest fuel and
can be produced from renewable sources. The model was
developed to provide performance, combustion, and emission
data for both hydrogen port injections. The performance data
included brake power, brake mean effective pressure, and brake
thermal efficiency, while the combustion data included incylinder pressure, rate of heat release, and in-cylinder
temperature. The hydrogen port injection performance,
combustion and emission data were compared with those of
gasoline port injection. Compared to gasoline port injection, no
significant variations in performance and combustion data were
observed with hydrogen port injection. However, Carbon
dioxide emissions were entirely removed with hydrogen p

Modelling and simulation of performance, combustion and emission of a diesel engine fueled with renewable dimethyl ether-ethanol blend

Due to price hikes, stringent emission regulations
(Net Zero emissions by 2050), and global climate change issues,
researchers are driven to explore sustainable fuels. This study
reports on 1-dimensional (1D) modelling and simulation of
performance, combustion and emission of a direct injection
diesel engine using dimethyl ether (DME)-ethanol blend as one
of the carbon-footprint compliance fuels. DME can be sourced
from sustainable feedstocks, which are considered one of the
cleanest fuels due to their inherent oxygen content in the
molecular structure. Like DME, bioethanol can also be sourced
from renewable feedstocks and is considered an oxygenated
fuel. For the 1D modelling and simulation, GT-Suite Software
was used. Using DME 50%+Ethanol 50% (henceforth termed
DME50), the modelling and simulation were performed for
performance, combustion and emission characteristics. The
different performance, combustion and emissions data were
compared with those of base diesel fuel. The results showed that
DME50 outperforms diesel fuel in terms of engine performance,
combustion, and emissions, including greenhouse gas emissions,
carbon dioxide (CO2) in this investigation.

A Poincare Map Algorithm to Determine the Optimum MPPT for Solar Photovoltaic Panels

Despite the large uptake of solar energy around the world, low efficiency of the photovoltaic (PV) panels is their main drawback. This paper presents a novel maximum power point tracking (MPPT) for PV panels based on the Poincare Map technique that aims at increasing the efficiency of the solar panels. Using this technique, not only will make the solar panels more affordable from efficiency perspective, but also the external maloperations cannot jeopardize the accuracy of the plan, as shown by the study. Moreover, the studies show that the reliability of the plan under the standard operation of the solar panel is more than 98.94%, and is over 97.19% under external disturbances.

Wavelet-ARIMA-based Forensic Analysis of Synchrophasor Data Using Machine Learning

— Integration of distributed energy resources into
power grids fosters the development of precise monitoring,
protection, and control applications by employing immense
spatiotemporal data from micro-phasor measurement units
(µPMUs). For enhanced situational awareness, a comprehensive
methodology is required for real-time synchro phasor forensic
analysis, using advanced machine learning techniques to detect
and classify anomalies in grid events. This paper presents a twostage analytical framework that combines WaveletAutoregressive Integrated Moving Average (ARIMA)-based
analysis with a machine learning approach to enhance the
identification and classification of events by leveraging
historical frequency and spectrum data. The raw data from the
New England ISO and the European Continental Split dataset
is preprocessed in the initial phase as it includes multiple events.
The process involves Stationary Wavelet Transform (SWT) for
denoising and sliding window ARIMA model to identify the
Rolling Standard Deviation (RSD) for feature extraction and
threshold setting. The frequency excursions and oscillations are
classified based on the Synchro phasor Event Detection
Algorithm (SPEDA) as per statistical thresholds. The retrieved
features of the detected and localized events are cross-validated
using machine learning classifiers in the next stage, enhancing
the overall efficiency and effectiveness of the study. The study
will demonstrate that advanced computing facilities accelerate
sophisticated calculations and reduce model training time.

Conference Site: I-COSTE 2024