Our presentations at the APSRC 2021

The Asia-Pacific Solar Research Conference (APSRC) is an annual event organised by the Australian PV Institute (APVI), to provide “a regional forum for communicating research outcomes covering all aspects of solar-related research”. The most recent conference was held on the 16th and 17th of December 2021 at UNSW Sydney. The technical team at Exemplary Energy submitted four extended abstracts under the Solar Buildings and Solar Heating & Cooling stream and the following titles were presented at the conference:

“Extending Real-Time Year Weather Data Services with Bureau of Meteorology Data“, authored by Naman Jain, Nihal Abdul Hameed, Trevor Lee and David Ferrari. The paper was presented by Trevor Lee who described Exemplary Energy’s plans to integrate the new real-time solar radiation data, recently made available by the Bureau of Meteorology, into our software. This will bolster our ability to provide our clients with the latest weather data and allow us to expand our free monthly public service, the “Exemplary Weather and Energy (EWE) Index”, to cover all eight Australian capital cities. The EWE Index has been published by Exemplary Energy since November 2014 as a free service to industry which evaluates the impacts of recent weather on the energy performance of buildings and solar PV generation.

Energy consumption comparison and trends for the three archtypical buildings in different locations

“Verification of ClimateCypher Climate Data Outputs with System Advisor Model (SAM)“, authored by Naman Jain, Nihal Abdul Hameed, Trevor Lee and ZhongRan Deng. Presented remotely by Nihal Hameed, this work outlines a recent enhancement in Exemplary Energy’s in-house software ClimateCypher to produce eXtreme Meteorological Year (XMY) data. XMY weather data are hypothetical years with extreme weather conditions, and allow for a better understanding of energy performance under extreme conditions. There are a number of design and financial applications for XMY weather data, such as calculating the expected unserved energy (USE), and managing the risk of variability of renewable sources to determine factors like the Debt-Service Coverage Ratio (DSCR). This new ClimateCypher capability is verified by comparing with simulated energy outputs from the System Advisor Model (SAM), and almost all percentage differences between SAM and ClimateCypher outputs were within ±2%.

The paper flags a potential shortcoming in that and extreme year for solar PV performance does not necessarily represent an extreme year for buildings. The team plans to undertake further work to better understand this issue and may soon develop capabilities to define XMYs for buildings.

“Updating Australia’s Reference Meteorological Years with the Addition of Hourly Precipitation Data” authored by Chithral Kodagoda, Masoume Mahmoodi, Nihal Abdul-Hameed and Trevor Lee. The presentation for this project was given remotely by Chithral Kodagoda. In this project, Exemplary Energy developed algorithms to estimate hourly precipitation data derived from 30 years of daily precipitation data. An important application of the resultant hourly rainfall data is their usage as input to models of building moisture to allow for better understanding and management of condensation issues.

“Effect of Energy Efficiency Rating (EER) of Dwellings on Sale Prices in the ACT 1999-2021” authored by Trevor Lee, Yoke Yeong Fung and Chun Yin Wu. This work was presented by Trevor Lee who described Exemplary Energy’s ongoing evaluation of the Energy Efficiency Rating (EER) as a valuation tool underlying the Canberra property market. Despite well-documented demonstration of the “higher EER, higher prices” relationship, Exemplary Energy observed an inverse correlation between EER and sale prices for all dwellings since late 2014. Key reasons for this anomaly are proposed to be:
1. Proximity of the worst-performing properties to the city centre where the value of the land is higher
2. Apartments priced low in the market, yet are the better performing dwelling type
3. Data analysis and representation (i.e. using mean instead of median home prices) may skew aggregated value upwards due to a small number of high-value homes

To achieve better representation, Exemplary Energy implemented a revised methodology into the analysis, by disaggregating dwelling types (houses, townhouses, and apartments/units), and using median prices. This resulted in a more apparent positive relationship between price and EER. This study is part of a growing body research to improve energy efficiency of properties for higher sale/rental price

Access to all four extended abstracts are available on the APSRC conference website.

Introducing our new engineering intern: Jean Tan (RMIT)

Hello, my name is Jean and I am one of three new interns recently recruited by Exemplary Energy. I am a postgraduate student at RMIT, undertaking a Master of Engineering in Sustainable Energy. I was previously awarded a Bachelor of Engineering (with honours) from the University of Western, majoring in Applied Ocean Science.

My first graduate employment was with a multidisciplinary consulting firm in Perth, working as a maritime engineer on various aspects of coastal and offshore structure design and analysis, on projects for both local and international clients. I then took a year’s break to go to countryside Japan on a teaching program. That one year turned into 12 years overseas, where I gained invaluable experiences while living in Japan and Hong Kong. During my time overseas, I travelled the globe, gave birth to three babies, and gained 10 years of teaching experience while supporting my husband’s career and raising our children.

I am an environmentalist with a drive to help develop a more sustainable world for future generations, and I am excited to join Exemplary Energy as an Engineering Intern. My interests and hobbies are many and varied, including but not limited to food (eating and cooking), travel, music, photography, astronomy, reading, movies, dancing, health and fitness.

Still no precipitation data despite NCC compliance requiring moisture management

A critical review of the CSIRO Weather and Climate Data (Part 3 of 3)

The CSIRO weather and climate data sets discussed in our previous post are widely employed by building energy modellers, including applications to demonstrate compliance with the energy efficiency requirements of the National Construction Code (NCC). Exemplary Energy’s timely critique of the CSIRO weather and climate data sets ahead of the 2022 publication of the NCC, and highlighted three major shortcomings:

1. Reliance on weather data ending in 2015 for the characterisation of a warming climate;

2. A 30-minute error in solar data in the .epw format; and

3. A lack of coincident precipitation data despite the .epw format expressly inviting it.

Discussions of the first two issues can be accessed here and here. In this final article of our three-part series, we investigate the opportunity for incorporation of coincident precipitation.

Precipitation data is important for a wide variety of applications. The AIRAH DA07, Criteria for Moisture Control Design Analysis in Buildings, provides specifications for predicting, mitigating, or reducing moisture damage to buildings, and requires detailed consideration of precipitation. In 2019, minimum condensation requirements were incorporated into the NCC, designed to minimise impacts related to moisture on the health of the occupants in the building. Further measures for moisture management are being proposed for the NCC 2022.

One challenge is that, until recently, many sources of precipitation data are reported at inadequate temporal resolutions. For instance, the Bureau of Meteorology’s (BOM) observations network typically only reported daily totals prior to the early 2000’s.

Exemplary Energy has developed algorithms to estimate hourly precipitation from the daily historical figures reported by the BOM for over 200 Australian locations, including the 69 locations built into NatHERS. This work was recently peer reviewed and was presented by Exemplary Energy in the Asia Pacific Solar Research Conference (APSRC) in December 2021.

The issues outlined herein need to be considered by policymakers and modellers alike. We have advised our colleagues at CSIRO of these findings and will continue to work with them to avoid further propagation of the errors and offer our support to improve the data going forward. We urge policymakers to be mindful of these issues as modelling inaccuracies arising now are embedded in building operations for many years to come.

In the interests of full disclosure, we note that Exemplary Energy offers high quality climate and weather data, including ersatz future climate data, that avoid the issues of the CSIRO datasets. These are available for modellers demonstrating compliance through the JV3 pathway, along with non-regulatory applications in design and optimisation and resilience testing of buildings and energy systems.

Solar data timing error skews simulation results

A critical review of the CSIRO Weather and Climate Data (Part 2 of 3)

1. Reliance on weather data ending in 2015 for the characterisation of a warming climate;

2. A 30-minute error in solar data in the .epw format; and

3. A lack of coincident precipitation data despite the .epw format expressly inviting it.

Discussion of the first issue was previously covered on this blog. This article will review the 30-minute error in the solar data. In this second article of a three-part series, we investigate the 30-minute time offset in the CSIRO solar data.

The issue is likely caused by transcription error. One of the key differences between the .epw and NatHERS formats relates to the timestamp applied to solar irradiation data: the .epw format requires that the solar irradiation data represents the period prior to the timestamp, whereas the ACDB format specifies that the solar irradiation represents the hour centred on the timestamp. Failure to adjust to this time convention most notably affects the time of peak loading, and has major impacts on evaluations which incorporate on-site renewable energy generation.

Hourly plots comparing the diffuse radiation of the CSIRO .epw data with the Exemplary Energy .epw and ACDB datasets for Canberra for Days 13 to 24 in January. Note the half-hour time offset and the difference in radiation

A comparison between CSIRO’s datasets and those produced by Exemplary Energy further illuminates the differences. As an example, a detailed analysis of the Canberra climate – where the two datasets theoretically share the same source for January’s data – reveals a difference of 2.3 kWh/m² in global horizontal radiation for the month, 7.3 kWh/m² direct normal radiation, and 9.1 kWh/m² in diffuse radiation. These differences highlight the shortcomings of transcription between formats – even when applied correctly, interpolation between datapoints to account for timestamp differences will always introduce errors¹.

Applying these data to a one-month simulation of a 3-storey office building in Canberra, the Exemplary data resulted in increased cooling by 4.4% and increased peak cooling load by 3.3%, along with a 30-minute timing offset in the peak cooling load.

The opportunity for including precipitation data will be discussed in a future article.

¹ Exemplary Energy’s weather and climate data products are always produced from meteorological observations at the highest-available temporal resolution. In the case of solar data, our datasets are directly based on Himawari satellite observations recorded at ten-minute intervals.