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Baran Yildiz

Baran Yildiz
UNSW Sydney | UNSW · School of Photovoltaic and Renewable Energy Engineering

PhD

About

17
Publications
3,501
Reads
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589
Citations
Citations since 2016
17 Research Items
588 Citations
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Introduction
Baran holds a PhD from the School of Photovoltaic and Renewable Energy Engineering, UNSW. Since 2019, he has lead and worked in different CRC Projects in collaboration with leading industry partners of Australian progressive energy market. His research and professional experience includes: integration of distributed energy resources, demand response and demand side management, residential and commercial electricity load analysis and forecasting, home energy systems, grid-connected PV systems.
Additional affiliations
September 2015 - September 2018
UNSW Sydney
Position
  • PhD Candidate/ Researcher

Publications

Publications (17)
Article
Electricity load forecasting is an important tool which can be utilized to enable effective control of commercial building electricity loads. Accurate forecasts of commercial building electricity loads can bring significant environmental and economic benefits by reducing electricity use and peak demand and the corresponding GHG emissions. This pape...
Article
The emergence of smart grid technologies and applications has meant there is increasing interest in utilising smart meters. Smart meter penetration has significantly increased over the last decade and they are becoming more widespread globally. Companies such as Google, Nest, Intel, General Electric and Amazon are amongst those companies which have...
Technical Report
Full-text available
The Energy Security Board commissioned the Centre for Energy and Environmental Markets at the University of New South Wales to undertake analysis of voltage on the LV networks within the NEM, as well as distributed PV’s influence on that voltage. This work used a unique dataset of maximum and minimum voltage measurements over 12,000 sites in the LV...
Article
Water heating is one of the most energy intensive applications in households and domestic electric water heating systems (DEWH) offer large thermal storage for moving electrical load across the day. This study uses a unique dataset from 410 households and presents a comprehensive analysis of electricity consumption and hot water draw of DEWH for th...
Article
Appliance level control and automation is an increasingly promising demand-side management tool with growing installation of advanced metering, monitoring and control infrastructure in both residential and commercial contexts. Successful implementation of appliance control and automation can alleviate network peak demand and improve distributed pho...
Article
Full-text available
Electric Vehicles (EVs) are a rapidly growing technology which can lower greenhouse-gas emissions in the transport and energy sectors. The EV batteries can discharge the stored energy back to grid, also known as Vehicle-to-Grid (V2G) which can support the integration of variable distributed renewable generation. Previous research identified financi...
Conference Paper
Australia has world leading uptake of distributed PV (D-PV) and increasing installations of battery energy storage systems (BESS). D-PV and BESS can provide various economic and environmental benefits to energy users, network companies and other industry stakeholders. However, integrating increasing levels of D-PV into electricity networks present...
Technical Report
Australia has world leading uptake of distributed PV (D-PV) and increasing installations of battery energy storage systems (BESS). Recent reports estimate one in four households own D-PV and installation rates are anticipated to grow in the years ahead. D-PV and BESS can provide various economic and environmental benefits to energy users, network c...
Technical Report
Full-text available
One of the main goals of the Cooperative Research Centre (CRC) Project, Integrated Smart Home Energy Management is to control and automate major electrical appliances to bring financial and environmental benefits to household owners. Successful implementation of the project on a large number of households can also assist DNSP and networks as a dema...
Presentation
Full-text available
Presenting the results obtained from the analysis of 630 households from Solar Analytics data-base with rooftop solar and electric hot water heating system (inc. heat pump)
Article
A clustering analysis on net meter energy data collected from 2779 solar households. • K-means clustering and random forest are used for data extrapolation. • Through clustering net meter energy data, a battery sizing model is developed. • The proposed battery sizing model shows robustness to limited input data. • More seasonal clusters result in m...
Thesis
This thesis researches the forecasting of individual household electricity loads, which has been identified as a major challenge for forecasting models, due to the high volatility of household loads. To address the reporting and methodological inconsistencies found in previous household load forecast studies, a coherent analysis framework is develo...
Conference Paper
The uptake of smart grid technologies and increasing deployment of smart meters have brought greater attention on the analysis of individual household electricity consumption. Within the smart grid framework, home and battery energy management systems are becoming important demand side management tools with various benefits to households, utilities...
Article
Full-text available
Smart grid components such as smart home and battery energy management systems, high penetration of renewable energy systems, and demand response activities, require accurate electricity demand forecasts for the successful operation of the electricity distribution networks. For example, in order to optimize residential PV generation and electricity...
Conference Paper
Smart meter data can be used for various purposes within smart grids, including residential energy applications, such as Home Energy Management Systems (HEMS) and Battery Energy Management Systems (BEMS). Considering the low feed-in tariffs for rooftop photovoltaic (PV) and increasing customer electricity prices, maximizing PV selfconsumption becom...
Conference Paper
Smart grid components such as smart home energy and battery management systems, high penetration of renewable energy systems, and demand response activities, require accurate electricity demand forecasts for the successful operation of the electricity distribution networks. For example, in order to optimize residential PV generation and electricity...

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Cited By

Projects

Projects (3)
Project
The Curtailment and Network Voltage Analysis Study (CANVAS) is a RACE for 2030 project conducted by the Collaboration on Energy Markets at UNSW, with industry partners AGL, SA Power Networks (SAPN) and Solar Analytics. In the initial phase of the project, CANVAS’s main motivation is to develop preliminary socio-technical insights to inform industry stakeholders and policy makers about the current state of DER curtailment due to power quality response modes (PQRM) requirements of solar and battery inverters. CANVAS consists of two research streams, social science and technical, with both delivering evidence-based results that have important implications for Australia’s fast growing and ever-changing energy landscape, where previous evidence-based results and studies have been limited.
Project
To develop and deploy cost-effective demand management and home energy control solutions that deliver value to customers, local manufactures, and network operators.
Project
The project will develop algorithms for a customer-focussed software solution that interprets energy supply and demand at the system level (focussing on residential, but applicable also to small commercial). Interpreting the complex relationship between cost, supply and load along with accurate data and analytics will enable end users to proactively manage demand. The algorithms will take local load, weather and energy generation inputs and automate the analysis of the electricity production and consumption http://lowcarbonlivingcrc.com.au/research/program-1-integrated-building-systems/rp1023-forecasting-and-home-energy-analysis