0002-FGTP-REC-Location-Matcher.md

FGTP	title	status	original author	created
0002	REC Location Matcher	Idea	redransil	2021-10-28

Title

REC Location Matcher

Abstract

We need to be able to algorithmically determine whether renewable energy credits (RECs) match energy consumption. One component of this is determining whether consumption and production are close enough to each other on the grid. This is currently done in the industry manually by accounting firms.

Authors

Feel free to add your name if you make contributions beyond fixing typos or formatting

redransil

Status

Idea

What is the goal

Given a consumption location and generation location, tell whether they are in the same bidding zone.

What are the inputs

1. Consumption location may be address, GPS, city, county or zip code where a minerID is located.

• If a minerID is distributed, say it seals in one location and stores in another, this may not exactly map to a minerID
• One way to do this is minerID -> IP and IP -> location. We are developing a methodology separately to validate this info with other data (for example, power bills) but IP is probably a good starting point.
• What location info should we store to facilitate this?

2. Location information from a REC certificate

• You can find them linked from Filrep
• Example I-REC
• Example Green-e REC
• Example GO 1
• Example GO 2, Norway
• What location data should we store along with REC purchases to facilitate this?
• In the near-term, we are expecting to have REC location and amount be available at an EWF endpoint, for example here for f01234

3. Spatial resolution

What are the outputs

True / False whether the consumption and generation match

Proposed Solution

• The goal here is to make sure that the generation and consumption are on the same power grid. No good across-the-board standard exists for this right now
• One easy solution is political boundaries: ie country (if the country is reasonably small) or state/province
• The best solution would look similar to European bidding zones which are intended to reflect physical electric transmission constraints.
• In the US, NERC Regions are a good level of granularity.
  • See GIS data for these regions
• This configuration may need to be updated over time

Implementations and Artifacts

No implementations

Relevant Background

• See above.
• The ultimate goal is to come up with an easy way of mapping points in the transmission system which electricity flows easily between. See for example how this gets translated into Locational Marginal Prices (LMPs) in real-time maps
• For more on LMPs, see this report on energy pricing
• There are many ways of carving up power grids; in addition to NERC maps above see eGRID maps here

Also for the US, see grid interconnections and system operator / balancing authority data.