METHODS AND APPARATUS FOR DLT-ENABLED DIGITIZED TOKENS FOR BASELINE ENERGY USAGE

Abstract

Disclosed embodiments include methods and computer-implemented distributed ledger technology (“DLT”) systems based at least in part upon electricity usage. Disclosed embodiments include instructions to cause at least one server device and related data processing and storage apparatus to operate over a peer-to-peer network to provide a system having an electricity tracker module that records a transaction comprising an amount of electricity incoming from a power grid and an amount of energy savings from energy savings equipment, along with the environmental and other attributes of such energy, wherein the transaction includes identifying data and the electricity tracker module functions as a node on a DLT network, and wherein the DLT network comprises a plurality of nodes that execute a software verification algorithm that includes a cryptographic hash value based at least in part upon transaction identifying data. Disclosed embodiments also include a predictive analytics module to compare the incoming electricity usage against the amount of energy savings from the energy savings equipment, a timer module to monitor the electricity tracker module through a defined term, and an invoice module for generating an invoice for the energy saved through the defined term.

Claims

1. A computer-implemented distributed ledger technology (“DLT”) system based at least in part upon electricity usage, the system comprising: instructions to cause at least one server device and related data processing and storage apparatus to operate over a peer-to-peer network to provide a system comprising: an electricity tracker module that records a transaction comprising an amount of electricity incoming from a power grid and an amount of energy savings from energy savings equipment, along with the environmental and other attributes of such energy; wherein the transaction includes identifying data and the electricity tracker module functions as a node on a DLT network; and wherein the DLT network comprises a plurality of nodes that execute a software verification algorithm that includes a cryptographic hash value based at least in part upon transaction identifying data; a predictive analytics module to compare the incoming electricity usage against the amount of energy savings from the energy savings equipment; a timer module to monitor the electricity tracker module through a defined term; and an invoice module for generating an invoice for the energy saved through the defined term.

2. The DLT system of claim 1, wherein the cryptographic hash value is additionally based upon at least one prior verified transaction.

3. The DLT system of claim 1 wherein the electricity tracker module comprises a physical monitoring device connected to an Advanced Metering Infrastructure (AMI) meter.

4. The DLT system of claim 3 wherein the physical monitoring device comprises an American National Standards Institute (ANSI) certified physical monitoring device.

5. The DLT system of claim 1 wherein the electricity tracker module communicates with the DLT network through a cellular network connection.

6. The DLT system of claim 1 wherein the invoice module for generating an invoice comprises a smart contract.

7. A computer-implemented method of operating a distributed ledger technology (“DLT”) token exchange system based at least in part upon electricity usage, the method comprising: executing instructions to cause at least one server device and related data processing and storage apparatus to operate over a peer-to-peer network to provide a method comprising: recording, with an electricity tracker module, a transaction comprising an amount of electricity incoming from a power grid and an amount of energy savings from energy savings equipment, along with the environmental and other attributes of such energy; wherein the transaction includes identifying data and the electricity tracker module functions as a node on a DLT network; and wherein the DLT network comprises a plurality of nodes that execute a software verification algorithm that includes a cryptographic hash value based at least in part upon transaction identifying data; comparing, with a predictive analytics module, the incoming electricity usage against the amount of energy savings from the energy savings equipment; timing, with a timer module, to monitor the electricity tracker module through a defined term; and generating an invoice, with an invoice module, for the energy saved through the defined term.

8. The DLT method of claim 7, wherein the cryptographic hash value is additionally based upon at least one prior verified transaction.

9. The DLT method of claim 7 wherein the electricity tracker module comprises a physical monitoring device connected to an Advanced Metering Infrastructure (AMI) meter.

10. The DLT method of claim 9 wherein the physical monitoring device comprises an American National Standards Institute (ANSI) certified physical monitoring device.

11. The DLT method of claim 7 wherein the electricity tracker module communicates with the DLT network through a cellular network connection.

12. The DLT method of claim 7 wherein the invoice module for generating an invoice comprises a smart contract.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0031] FIG. 1 is a schematic overview of an energy credit DLT ecosystem in accordance with disclosed embodiments.

[0032] FIG. 2 is a schematic of utility meter in accordance with disclosed embodiments.

[0033] FIG. 3 is a schematic flow diagram illustrating electricity and data flow in accordance with disclosed embodiments.

[0034] FIG. 4 is a flow chart for an exemplary method in accordance with disclosed embodiments.

[0035] While the disclosure is susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and will be described in detail herein. However, it should be understood that the disclosure is not intended to be limited to the particular forms disclosed. Rather, the intention is to cover all modifications, equivalents and alternatives falling within the spirit and scope of the invention as defined by the appended claims.

DETAILED DESCRIPTION

[0036] FIG. 1 is a schematic overview of an energy credit DLT ecosystem 100 in accordance with disclosed embodiments. As illustrated, system 100 may include a number of energy generators 102 which may comprise solar, wind, hydro, waste gasifiers, nuclear, coal fired, or the like electrical generation systems.

[0037] Electric energy generated by the electrical generators 102 is measured by a module 104 embodiments of which may be an ANSI certified physical monitoring device connected to any standard AMI meter which monitors and stores the measurements of the amount of the flow of electricity measured on a utility feed or interconnect line 106 by such standard AMI meter. Embodiments of module 104 may also store the time history of the electricity flow through the interconnect line 106 (e.g., power grid). Embodiments of module 104 can use public or other cellular communications 108, or other wireless, mesh technology, WiFi, or the like networks to communicate to the nodes of the system distributed ledger 112 to provide an immutable history of the generation of electricity at the attached module 104 location. Geolocation is used through cellular (or other) communications networks 108 to ensure production is from the specific source it is tied to.

[0038] As part of the above noted validation process, embodiments of the module 104 receive calibration information from an associated electricity meter as it is calibrated to ensure production of tokens 114 is not manipulated, rigged, or otherwise fraudulently created. The transaction is shared on the system's distributed ledger network 112. As also shown, smart contracts within and across DLT network 112 are used to create tokens 114 based on provable power generation (or other energy related) data and are the transactions that are shared and validated between the nodes. As one of ordinary skill in the art having the benefit of this disclosure would understand, “smart contracts” is an industry term describing a self-executing contract with the terms of the agreement between the buyer and seller being directly written into the lines of software code. The code and the agreements contained therein exist within/across the DLT network 112. The code controls the execution and the transaction is traceable and irreversible.

[0039] Embodiments of system 100 include one or more applications (which may be represented by a digital wallet 116) incorporated in the system 100 that allows consumers 118 and producers 102 to access the system 100 token 114 exchange. Embodiments of the system 100 application(s) can be available on any computing device (i.e., smartphone, tablet, or PC, laptop, or the like) and can be used for purchase or sale of goods and services using the token 114, or the trade of tokens 114, on the basis of the underlying value of the token 114 used representing a kilowatt of electricity or other metric or measurable property based on an amount of electricity or power. As the cost of a kilowatt of electricity may vary from region to region, the system 100 also acts as an exchange to equalize the amount of tokens 114 necessary to pay for goods and services in such region. As a result, cross-regional and cross-border trade can be fomented on the basis of a standard set around a kilowatt of electricity, a definable, measurable metric.

[0040] As also shown in FIG. 1, feed lines 106 (e.g., from the power grid) provide electricity to power consumers 118 which, as noted herein, may be paid for using tokens 114 stored in the consumer 118 digital wallet 116. Token 114 consumption is recorded on the DLT network 112 and distributed to each node on DLT network 112 and consumed tokens 114 are removed from circulation as indicated at 120.

[0041] As will be apparent to those of ordinary skill in the art having the benefit of this disclosure, the system exchange stores an order book in the DLT network 112 and a plurality of digital wallets 116 associated with different clients (e.g., 118). The computer system receives new data transaction requests from the individual modules 104 and/or digital wallets 116 at timed intervals and transactions are added to the order book in the DLT 112. This data (timestamp and transaction information) is then verified by the modules 104 on the network 100. If verification is successful, the transactions are added to the distributed ledger 112. The system 100 then monitors the distributed ledger 112 to determine its ongoing validity. The integrity (e.g., confidence that a previously recorded transaction has not been modified) of the entire distributed ledger 112 is maintained because each transaction refers to or includes a cryptographic hash value, generated in the module 104 at the electrical production facility 102, of the prior transaction.

[0042] Generally, a hash is a type of algorithm that takes any input, no matter the length, and outputs a standard-length, random output. This string of characters (output) is the hash, and it is deterministic, meaning the data that is hashed will always produce the same output (string of characters). Accordingly, once a transaction refers to a prior transaction, it becomes difficult to modify or tamper with the data (e.g., the transactions) contained therein. This is because even a small modification to the data will affect the hash value of the entire transaction. Each additional transaction increases the difficulty of tampering with the contents of an earlier transaction. Thus, even though the contents of a distributed ledger (e.g., 112) may be available for all to see, they become practically immutable.

[0043] As noted, consumers 118 can purchase tokens 114 through a pre-purchase of electricity from a generator 102. These tokens 114 can be used or exchanged with other consumers 118 for goods and services. The tokens 114 can be used multiple times for multiple transactions and are only redeemed when used for purchase of electricity from a generator 102 within the system 100, which then takes that token 114 out of circulation as shown at 120. Generators 102 that produce the tokens 114 may also sell or exchange the tokens 114 with other consumers 118 for goods or services. In a like manner, characteristics of the energy associated with the token, can be traded as part and parcel of the energy, or potentially be traded separately.

[0044] In some embodiments, consumers 118 may also include modules 104 (e.g., AMI meters with modules 104) to measure their electric consumption or energy usage. This data may be stored in their digital wallet 116 and can serve as the basis for payment through tokens 114 stored on the digital wallet 116. The module 104 itself may also be used as a node on DLT network 112 to help in validating transactions on the distributed ledger 112.

[0045] FIG. 2 is a schematic of utility meter 200 in accordance with disclosed embodiments. Embodiments of utility meter 200 may include metering equipment 202 mounted to, or near, a facility where energy consumption/creation/saving is desired to be monitored in accordance with disclosed embodiments. Embodiments of utility meter 200 include a kWh meter display 204 mounted via a collar 206 to the metering equipment 202. Other embodiments and types (e.g., digital, smart, or the like) of utility meters 200 may also be used.

[0046] Embodiments of utility meter 200 also include a data tracking device 208 (also referred to herein as “tracker”) which includes one or more circuit boards and associated software that connect to the facility's electrical circuits 210 being monitored as part of the energy savings program in order to determine the energy usage in the equipment (including its characteristics), or sector of the building, for which the tracker 208 has been connected. Embodiments of the tracker 208 can be incorporated directly within the existing electric utility meter 200 already utilized by the utility on site (e.g., through prior permission or arrangement with the meter supplier) or attached to an existing utility meter 200 through collar 206 that fits to the existing meter 200. Embodiments of collar 206 are designed to fit with any size or type of smart or other meter through standard size couplings. The tracker 208 collects the information on the electricity use from the client's site and equipment installed 210 at the client's site on an ongoing basis, stores it, and then transmits it to the DLT 218. Depending on the size of the facility, multiple metering devices 200 may be employed.

[0047] The tracker 208 also reads information relating to the energy used in the facility, depending on the equipment 210 that is the source of use (e.g., lighting, air conditioning, refrigeration, electric vehicle charging, etc.). In some embodiments the energy savings equipment 210 installed may communicate with the tracker 208 through a wired (212) or wireless (214) system.

[0048] FIG. 3 is a schematic flow diagram illustrating electricity and data flow in accordance with disclosed embodiments. As the bi-directional data 216 is measured and collected, the data is transmitted into the tracker 208 which will then upload the data to the DLT 218. The DLT 218, in this example running in a cloud environment, then verifies and validates the data 216 through comparison of a time stamp and other signatures available in the cloud environment. In some embodiments the data is communicated to the DLT 218 by the tracker 208 through a cellular connection, for example, contracted with a cellular service.

[0049] The data 216 is then run through predictive analytics 220 to compare the energy usage against the calculations of the energy usage utilizing the previous installed or replaced equipment, the specifications of which may be stored also in DLT 218 in the cloud-based environment. The difference calculated between the actual energy usage and the predicted energy usage is then also be verified and validated. This data 216 may be collected continuously through a defined term (e.g., one month), at which point the total savings for such period will be determined and the client invoiced automatically for the energy saved through a smart contract tied to the DLT 218, based on contract parameters agreed between the client and the ESCO. The smart contract can generate and publish the data and demonstrate validation through the DLT.

[0050] As data is collected by the tracker 208 from the facility meter itself as well as directly from the energy savings devices installed, AI and machine learning algorithms 220 can then be applied to analyze the data 216 stored in the DLT 218 providing predictive analytics to the client based on all the various attributes collected by the tracker 208. This optimizes energy usage and preventive maintenance measures to ensure optimal cost reduction.

[0051] FIG. 4 is a flow chart for an exemplary method 400 in accordance with disclosed embodiments. As shown at 402 meters 200 measure electricity flow into the facility, which is also read by a tracker 208. At 204 electrical usage at various energy savings or generation equipment 210 installed at the site by the ESCO is also measured and sent to the tracker 208 by internal wireless or wired networks. At 406 operating data and specifications for the equipment modified or replaced is stored in the DLT 218. As indicated at 408 and as should be apparent from the present disclosure, each tracker 208 is a node that feeds generation and energy related data 216 through a cellular or other connection to the DLT 218 stored in the cloud. As indicated at 410 each node (e.g., tracker 208) in the DLT 218 cross-validates the data 216 with other nodes as well as with time stamps and other data available through the cloud.

[0052] As will be understood by those of ordinary skill in the art having the benefit of this disclosure, data 216 loss is protected from network failure by the distributed nature of the DLT 218. As disclosed herein embodiments may be cell network enabled (i.e., reliable communications that may be “always on”). Additionally, the tracker 208 is designed to be “agnostic” to the meter installation and is not tied to any particular meter type or manufacturer and can be provided with the facility utility meter 200 or retrofitted to existing smart meters. The DLT 218 is utilized to calculate the actual energy savings versus the predicted energy usage and determines the payments due on a periodic basis, based on parameters agreed between the client and the ESCO. The smart contracts automatically process payments to the ESCO based on the savings calculated and the relevant parameters agreed and incorporated in the smart contract.

[0053] As also will be understood by those of ordinary skill in the art having the benefit of this disclosure, numerous application of the disclosed systems and methods are possible. For example, in energy service or performance contracts, the energy tracking systems accurately track each block of reduced, saved or recalculated power in the immutable DLT 218 stopping disputes related to how much real power was actually saved or made available to the facility. Additionally, the tracking system can be used to accurately track and store all environmental attributes related to the power produced or saved, such as all types of global carbon credits, green energy production tax credits, green energy investment tax credits, low carbon fuel standard credits, various other local and municipality specific credits, and the like. Further, the verification of these credits through the applied DLT 218, combined with data available on the value of such credits, would allow for trading of such credits and other enhancements. Likewise, the operating characteristics of the energy savings device may also be stored in a DLT 218 along with the measured operating data to be utilized by AI and/or machine learning programs to determine when maintenance or replacement might be required. Other embodiments and application are also possible.

[0054] Although various embodiments have been shown and described, the present disclosure is not so limited and will be understood to include all such modifications and variations would be apparent to one skilled in the art.