Industry Insights

Unlocking Efficient Decarbonization: The Critical Role of Accurate Data

January 08, 2024

Alongside long-time Itron partner, Capgemini, I had the opportunity to attend Climate Week NYC last September – the largest annual climate event of its kind that facilitates around 400 events and activities across New York City. Every year, international leaders gather at this event to drive the energy transition forward and champion the positive change that is already underway. This year’s theme, “We Can. We Will,” reflects the investments needed to explore the challenges and opportunities ahead as the energy industry looks to halve carbon emissions by 2030 and be on the path to net-zero by 2050.   

I went into this event with a strong understanding of the valuable role data plays in achieving sustainability and efficient energy and water management. During my time at Climate Week NYC, it was made clear that the critical importance of data in enabling the energy transition is more top of mind for utilities and key stakeholders than ever before. Let me explain.  

The Challenge: Labor-Intensive, Inaccurate Data 

Climate disruption has a significant impact on Itron stakeholders, and investors want more transparency around sustainability risks. New regulatory reporting requirements, and companies own net-zero ambitions, are also making environmental social governance (ESG) more critical. However, corporations, financial institutions and ESG providers often rely on inaccurate data, old data or data that is time- and labor-intensive to access when it comes to energy and water use and carbon footprints.  

The Solution: Utility Decarbonization Analytics and Data Sharing 

To address this, Itron is thrilled to collaborate with Capgemini to perform a market analysis on decarbonization and ESG opportunities for utility systems. Utilities and utility data are key to the solution for several reasons: 1.) the ability for utility customers to decarbonize depends largely on the utility’s own decarbonization trajectory and 2.) utilities and their advanced metering infrastructure (AMI) create a wealth of data on how much and when energy is used by customers in addition to how load is shifted throughout the day to meet the needs of an increasingly dynamic grid, which impacts the carbon footprint of customers. 

Based on our findings with Capgemini, Itron is exploring two new solutions to help unlock the potential of utility data for more efficient decarbonization and better ESG reporting. The first utilizes consumption data and forecasts from smart endpoints to help utilities understand who their most carbon intensive customers are and provide insights and services to help those customers decarbonize quickly and cost-effectively. Utilities investing heavily in solar, for instance, doesn’t necessarily result in much decarbonization for customers that use most of their electricity at night. Helping utilities plan for and address these “hard to decarbonize” customers and industry segments will help both utilities and their customers meet decarbonization targets. 

Itron is also developing a data sharing platform for energy and water called DataHub. DataHub enables utilities and other authorized parties to publish and subscribe to a variety of data products. One use case of DataHub is providing one consistent mechanism for corporations to subscribe to all of their consumption and emissions intensity data from locations served by utilities that have deployed it. Providing customers that have facilities across multiple utilities a simple way to access their own data or to share that data with authorized third parties can streamline and improve the accuracy of their ESG reporting process.  

To explore other potentially valuable data products for DataHub, our market analysis also included the perspective of a variety of ESG index and investment stakeholders. We discussed with them the types of data we are analyzing when looking at how to help utilities decarbonize as described above. ESG stakeholders rely on a variety of means to access emissions and water data today, including web-scraping of ESG reports, which can be costly and error prone.   

There is substantial interest in a more streamlined and auditable way to acquire emissions and water data and forecasts directly from utilities, as this information impacts inclusion of corporations in various green and sustainable investment portfolios and helps stakeholders understand the carbon transition risk of various industry segments in different regions. This data becomes even more valuable when analyzed along with data the ESG index and investment firms are already tracking on companies and industry segments. We will continue to work with our utility customers and ESG stakeholders and hope to provide data products that will add transparency and increase the accuracy of ESG indexing and investing.   

The Result: Better Data and ESG Reporting 

Making data available to end customers, third parties and utilities can help them make better system-wide decisions and create more efficiency. Together, Itron and Capgemini are unlocking value for multiple stakeholders including utilities, businesses, ESG service providers and financial institutions. The result is the entire energy ecosystem has more accurate reporting and insights into emissions to help build a more sustainable plan moving forward. Learn more about Itron and Capgemini’s collaboration here.

 

Si è verificato un errore nell'elaborarazione del modello.
The following has evaluated to null or missing:
==> authorContent.contentFields  [in template "44616#44647#114455" at line 9, column 17]

----
Tip: It's the step after the last dot that caused this error, not those before it.
----
Tip: If the failing expression is known to legally refer to something that's sometimes null or missing, either specify a default value like myOptionalVar!myDefault, or use <#if myOptionalVar??>when-present<#else>when-missing</#if>. (These only cover the last step of the expression; to cover the whole expression, use parenthesis: (myOptionalVar.foo)!myDefault, (myOptionalVar.foo)??
----

----
FTL stack trace ("~" means nesting-related):
	- Failed at: contentFields = authorContent.content...  [in template "44616#44647#114455" at line 9, column 1]
----
1<#assign 
2	webContentData = jsonFactoryUtil.createJSONObject(author.getData()) 
3	classPK = webContentData.classPK 
4/> 
5 
6<#assign 
7authorContent = restClient.get("/headless-delivery/v1.0/structured-contents/" + classPK + "?fields=contentFields%2CfriendlyUrlPath%2CtaxonomyCategoryBriefs") 
8contentFields = authorContent.contentFields 
9categories=authorContent.taxonomyCategoryBriefs 
10authorContentData = jsonFactoryUtil.createJSONObject(authorContent) 
11friendlyURL = authorContentData.friendlyUrlPath 
12authorCategoryId = "0" 
13/> 
14 
15<#list contentFields as contentField > 
16   <#assign  
17	 contentFieldData = jsonFactoryUtil.createJSONObject(contentField)  
18	 name = contentField.name 
19	 /> 
20	 <#if name == 'authorImage'> 
21	    <#if (contentField.contentFieldValue.image)??> 
22	        <#assign authorImageURL = contentField.contentFieldValue.image.contentUrl />	 
23			</#if> 
24	 </#if> 
25	 <#if name == 'authorName'> 
26	    <#assign authorName = contentField.contentFieldValue.data /> 
27			<#list categories as category > 
28         <#if authorName == category.taxonomyCategoryName> 
29				     <#assign authorCategoryId = category.taxonomyCategoryId /> 
30				 </#if> 
31      </#list> 
32	 </#if> 
33	 <#if name == 'authorDescription'> 
34	    <#assign authorDescription = contentField.contentFieldValue.data /> 
35			 
36	 </#if> 
37	  
38	 <#if name == 'authorJobTitle'> 
39	    <#assign authorJobTitle = contentField.contentFieldValue.data /> 
40			 
41	 </#if> 
42 
43</#list> 
44 
45<div class="blog-author-info"> 
46	<#if authorImageURL??> 
47		<img class="blog-author-img" id="author-image" src="${authorImageURL}" alt="" /> 
48	</#if> 
49	<#if authorName??> 
50		<#if authorName != ""> 
51			<p class="blog-author-name">By <a id="author-detail-page" href="/w/${friendlyURL}?filter_category_552298=${authorCategoryId}"><span id="author-full-name">${authorName}</span></a></p> 
52			<hr /> 
53		</#if> 
54	</#if> 
55	<#if authorJobTitle??> 
56		<#if authorJobTitle != ""> 
57			<p class="blog-author-title" id="author-job-title" >${authorJobTitle}</p> 
58			<hr /> 
59		</#if> 
60	</#if> 
61	<#if authorDescription??> 
62		<#if authorDescription != "" && authorDescription != "null" > 
63			<p class="blog-author-desc" id="author-job-desc">${authorDescription}</p> 
64			<hr /> 
65		</#if> 
66	</#if> 
67</div>