Patented D-Sharing Technology in Japan: Consumers’ Emission Factor

The Detailed Summary of Survey Responses on GHG Protocol Scope 2 Guidance (November 2023) (the "Survey Summary") makes the following points

"Also consider load management strategies that optimize energy consumption to increase during times when clean energy is abundant and to reduce energy consumption during times when the grid is dependent on more carbon-intensive resources."

The purpose of the Scope 2 Guidance is, among others, to help companies (and households) create GHG inventories that provide an accurate and fair picture of their emissions "by using a standardized approach and principles" and provide businesses with the information they need to develop effective strategies to manage and reduce their GHG emissions."

In addition, Section 2.1 of the current GHG Protocol Scope 2 Guidance further outlines the business objectives for Scope 2 accounting and reporting. Consistent with the Corporate Standard and the Scope 3 Standard, it states that businesses that consume electricity can aim to, among others,

1. Identify and understand the risks and opportunities associated with emissions from purchased and consumed electricity,
2. Identify internal GHG reduction opportunities, set reduction targets, and track performance,
3. Engage energy suppliers and partners in GHG management, and
4. Enhance stakeholder information and corporate reputation through transparent public reporting.

Thus, it is fair to say that the intent of this revision is to encourage more granular emissions "reductions" by companies and households through more detailed emissions "calculations" and to objectively measure their effectiveness. In addition, electricity suppliers may be required to assist in their accurate management.

In the survey summary, the rationale for increasing the granularity of location-based methods is that "some respondents indicated that the current location-based method of matching annual activity data with annual grid average emissions data is not granular enough to accurately account for an organization's grid-based GHG emissions, Some referred to a 2022 study showing that it does not incentivize corporate behavior such as load shifting or changes in overall consumption patterns." The report states.

The study summary uses "consumption-based emission factors rather than production-based emission factors." And, more specifically, "some respondents stated that it is necessary to require emission factors for electricity consumption, as opposed to production, to properly reflect the potentially significant impacts of net physical energy imports and exports across grid boundaries, rather than using only generation within a given grid territory. Some commented that the This is necessary to accurately represent the emissions associated with end-user electricity consumption." The statement states.

In light of these statements, it is possible that in the future, if the current revisions are made, regulators will be required to use objective measures to evaluate the emission reductions achieved by individual companies and households and their efforts, as well as to evaluate and compare how electricity suppliers are managing and supporting them, also using objective measures. In fact, in the survey summary, it is stated that "the power suppliers are not only reducing their emissions, but also reducing their emission reductions.

In fact, the Survey Summary mentions the following as "Feedback on Guidance Objectives"

1. The emissions from the reporting entity's value chain should be accurately reflected.
2. Reflect the physical consumption of energy and the emissions associated with the operations to produce that energy.
3. Facilitate decarbonization through accurate accounting and reporting.
4. Prioritize and promote actions and strategies for quality emission reductions and removals.
5. Comparability among reporting organizations.

To this end, D-Sharing has developed and patented technology to objectively measure, compare, and trade emission reduction efforts and effectiveness of consumption and generation (on- and off-site) in an integrated manner. An overview of this technology is provided below. In addition, with the aim of disseminating this Japan-originated technology to the world, D-Sharing is licensing it to consumers, electricity retailers, carbon accounting and management service companies, and others who agree with the advanced approach.

Development of Objective Indicators

In D-Sharing, the objective indicators to measure and compare emission reduction efforts and effects are the calculation of periodic and weighted average carbon intensity (kG-CO2/kWh), absolute and relative evaluation of the carbon efficiency and emission reduction effects of companies and households, and trading of their environmental value to provide monetary and non-monetary incentives, as well as the development of a carbon accounting system to measure and compare emission reduction efforts and effects. The company has already developed a practical method to encourage companies and households to change their behavior.

In addition to its commercialization for industrial users, electricity suppliers, and carbon accounting servicers, the company has already conducted a large-scale social experiment to promote behavioral change among households (including EV users and prosumers) as part of the Ministry of the Environment's Nudge Demonstration Project. If the effectiveness of the business model is confirmed, the plan is to commercialize the service for households.

Overview of Objective Indicators

CO2 emissions by electricity consumption are factorized into the electricity consumption (kWh) of each consumer and the period/weighted average carbon intensity (kG-CO2/kWh) to extract the period/weighted average consumer CO2 emission factor (kG-CO2/kWh).

This makes it possible to manage, evaluate, and trade each consumer's CO2 emission reduction behavior by dividing it into reduction of electricity consumption (kWh) and reduction of period weighted average consumer CO2 emission factor (kG-CO2/kWh), and visualization of the results will encourage more concrete behavioral changes.

The reduction of period and weighted average consumer CO2 emission factor (kG-CO2/kWh) is achieved by time-shifting consumption to the time of day when the CO2 emission factor by transmission and distribution network time period (kG-CO2/kWh) is low, i.e., generally when the ratio of renewable energy is high.

For example, if there are two companies, Company A and Company B, engaged in the transportation business, it is difficult to make a simple comparison because the distance traveled depends on the volume of business, but it is relatively easy to compare fuel efficiency. The operators can increase the average fuel efficiency of all vehicles and over the entire period by introducing fuel-efficient vehicles and by devising eco-driving practices for the drivers, i.e., sudden acceleration and sudden braking.

The same applies to shifting electricity consumption to a time with a higher ratio of renewable energy (daytime shift). We have categorized the paths of efforts to achieve this goal into (1) autonomous manual, (2) autonomous automatic, and (3) other-autonomous automatic, and have constructed a model of behavioral change for each.

Of these, autonomous automatic (1) is the act of shifting the use of electric loads (e.g., washing machines and dryers) to times when the sun is shining, as in eco-driving. Autonomous automatic operation (➁) is the act of shifting the operating time of a water heater by setting a timer, for example. In addition, autonomous automatic control (③) is the act of an external aggregator, for example, as part of a VPP, remotely and in real time controlling electricity consumption when supply and demand are tight (lower DR) or increasing electricity consumption when there is a surplus (higher DR). This is an automatic control action.

The management of consumer decarbonization behavior based on periodic and weighted average consumer CO2 emission factors (kG-CO2/kWh) can be an effective tool to effectively promote load leveling and renewable energy supply tracking through a combination of these factors.

Innovative Technologies from Japan

D-Sharing is actively promoting this approach abroad for international deployment. The UN 24/7 CFE Compact recognizes as one of the five principles of its work: "Technology Inclusive: Recognize the need to build zero carbon power systems as quickly as possible. All carbon-free energy technologies can play a role in creating this future." The UN 24/7 CFE Compact has featured our technology as a good example in its newsletter, and Energy Tag has also featured it as a case study.

GHG Survey Summary: Feedback on Additional Guidance, New Technologies and Use Cases

The GHG Survey Summary states, "Nearly all respondents agreed that updated and expanded clarification and new guidance on how to perform specific Scope 2 emissions calculation steps in a variety of situations would be beneficial in the Scope 2 guidance. Feedback also included suggestions related to new technologies, types of data, and other topics." The document states.

The GHG Protocol Secretariat is organizing a workshop to revise the Scope 2 Guidance, which suggests issuing guidance (or equivalent documents) specific to new technologies that will be needed to put new methods such as Hourly Matchig into practice.

In the following documents presented at the workshop, seven specific examples of required technologies are listed below.

(2) More geographically detailed grid emission data★

(iii) Hydrogen as an energy carrier (hard infrastructure technology)

(iv) More time granular grid emission data ★

(v) EV charging and grid integration★

(vi) Demand-side load management★

(vii) Advanced power metering infrastructure★

It should be noted that only two of the hard infrastructure technologies, (1) energy storage technology and (3) hydrogen as an energy carrier, and the remaining five, marked with ★ (our company), are soft data management technologies.

The remaining five technologies, i.e., (2) more geographically detailed grid emission data, (4) more time granular grid emission data, (5) EV charging and grid integration, (6) demand-side load management, and (7) advanced electricity metering infrastructure, use AI to analyze big data such as smart meters are all related to　D-Sharing’s patented technologies in terms of measuring grid emission data and managing demand-side load using the above methods. Therefore, D-Sharing hopes to contribute to the more practical diffusion of the Hourly Matching methodology worldwide by licensing the technology domestically and internationally.