Incentive Mechanism. An efficiency carryover mechanism will apply to operating expenditure. The incentive mechanism will operate in the following way: i the mechanism carries forward AGN’s incremental efficiency gains (or losses) for five years from the year those gains (or losses) occur; iii the annual carryover amounts are added to AGN’s total revenue in each year of the subsequent access arrangement period. If necessary, the annual efficiency gain (or loss) is carried forward into the access arrangement period commencing 1 July 2028 until it has been retained by the Service Provider for a period of five years. a The incremental efficiency gain (loss) for 2023/24 will be calculated using:: I2023/24 = (F2023/24 – A2023/24) – 2 × (FHY2023 – AHY2023) + (F2021 – A2021) where I2023/24 is the incremental efficiency gain (loss) for Regulatory Year 2023–24. F2023/24 is the approved forecast operating expenditure for Regulatory Year 2023–24. A2023/24 is the actual operating expenditure for Regulatory Year 2023–24. FHY2023 is the approved forecast operating expenditure for the six-month extension period from 1 January 2023 to 30 June 2023. AHY2023 is the actual operating expenditure for the six-month extension period from 1 January 2023 to 30 June 2023. F2021 is the approved forecast operating expenditure for Regulatory Year 2021. A2021 is the actual operating expenditure for Regulatory Year 2021. b Prior to the submission date for the Access Arrangement Period commencing 1 July 2028, actual operating expenditure data will be available for the regulatory year 2022. Where the Service Provider’s actual operating expenditure differs from the operating expenditure estimate used to calculate the efficiency carryover mechanism, a true-up will be made to account for the difference. The true-up for regulatory year 2022 will be: 𝑇2022 = −0.5 × [(𝐹2022 − 𝐴2022) − (𝐹2021 − 𝐴2021)] where: 𝑇2022 is the true-up for Regulatory Year 2022 𝐹2022 is the forecast operating expenditure for Regulatory Year 2022 𝐴2022 is the actual operating expenditure for Regulatory Year 2022 𝐹2021 is the forecast operating expenditure Regulatory Year 2021 𝐴2021 is the actual operating expenditure for Regulatory Year 2021 c Prior to the submission date for the Access Arrangement Period commencing 1 July 2028, actual operating expenditure data will be available for the six-month extension period from 1 January 2023 to 30 June 2023. Where the Service Provider’s actual operating expenditure differs from the operati...
Incentive Mechanism. There are neither other stock option or other similar performance-based incentive arrangements (including stock appreciation rights scheme) for employees (or former employees), directors (or former directors), supervisors (or former supervisors) or consultants (or former consultants) or contractors (or former contractors) of the Group Company, nor other similar arrangements that are affecting any of the above persons.
Incentive Mechanism. (a) The incentive mechanism will apply to operating expenditure.
Incentive Mechanism. As contemplated by Rule 98, this Access Arrangement incorporates an incentive mechanism that permits Service Provider to retain certain returns (if any) from the Reference Tariffs during the Fourth Access Arrangement Period that exceed the level of returns expected at the beginning of the Fourth Access Arrangement Period. In particular, this Access Arrangement incorporates a rolling carryover incentive mechanism that permits Service Provider to retain efficiency gains from the Fourth Access Arrangement Period in the Fifth Access Arrangement Period as discussed in clause 8.2.
Incentive Mechanism. Rule 98 of the NGR provides for an Access Arrangement to include an incentive mechanism.
Incentive Mechanism. In environments with independent users, it might be necessary to provide some form of incentive to motivate users to collaborate in a federated learning network. Some researchers have been looking into strategies for providing compensation to users to reward them for their compute power of input data. Federated Learning in DECICE The two main advantages of FL are privacy, due to not sharing raw training data with peers, and reduced bandwidth usage, as raw training data is processed locally instead of transmitted via a potentially slow network. This comes at the cost of having to provide enough compute power to perform the train locally. Assuming a number of nodes, including cloud and edge nodes, are controlled via the DECICE framework then these nodes are all also running a Kubernetes or KubeEdge stack in order to connect to the cluster. Furthermore, in this assumption, the edge nodes are connected to sensors that collect data, which is interesting for training a machine learning model. If all the nodes are connected into a cluster, they already have to trust the master nodes as these may submit arbitrary workloads on the other nodes, including accessing the locally stored data. Therefore, the advantage of privacy via FL is negated as there is no privacy for the edge nodes in this scenario from the master nodes. Nevertheless, considering the second advantage of reduced bandwidth usage, if the training data is, for example, a camera feed, then the network of the edge nodes could be incapable of streaming this data to a central server while maintaining a level of quality required for training a ML model. In this case, the solution would be to perform pre-processing or even training via FL on the edge nodes to reduce the load on the network. This still requires the edge nodes to be capable of performing said computations themselves. While it is certainly possible for FL to operate on top of a cluster managed by DECICE and to benefit from local computation, it still highly depends on whether a given use case can actually benefit from FL and whether the hardware setup available also calls for FL. Given this limited applicability, implementing federated learning on top of DECICE is currently not within the scope of the project.
Incentive Mechanism. The incentive mechanism works as follows: • in a Month where there are no Events scheduled, no Availability Incentive or Performance Incentive is payable; • in a Month where there are Events and the Participant delivers 100% of its Flexibility Target for each Event (i.e. Achieved Flexibility = Flexibility Target) Western Power will pay 100% of the Availability Incentive and 100% of the Performance Incentive for each Event; • in a Month where there are Events and the Participant delivers to between 50% and 99% (inclusive) of its Flexibility Target, Western Power will pay 100% of the Availability Incentive for each Event and the pro-rated Performance Incentive in line with their Achieved Flexibility for the each Event; • in a Month where there are Events and Participants delivers between 1% and 49% (inclusive) of their Flexibility Target for each Event, Western Power will pay an Availability Incentive for each Event but no Performance Incentive is paid; • Availability Incentive will be paid for scheduled Events in which Participants have participated; • no payments will be made for Events where the Participant was not available or chose not to participate; and • payment of the Performance Incentive and the Availability Incentive for each Event is capped where the Achieved Flexibility is 100% of the Flexibility Target for each Event.
Incentive Mechanism. There are no share options or other similar performance-based incentive arrangements (including stock appreciation right schemes) for any employees (or former employees) or directors (or former directors) or advisers (or former advisers) or contractors (or former contractors) of any members of Little Star Group, nor are there any arrangements affecting any such personnel.
Incentive Mechanism. There are no share options or other similar performance-based incentive arrangements (including stock appreciation right schemes) for any employees (or former employees) or directors (or former directors) or advisers (or former advisers) or underwriters (or former underwriters) of Xxxxxx, nor are there any arrangements affecting any such personnel.
Incentive Mechanism. An efficiency carryover mechanism will apply to operating expenditure. The incentive mechanism will operate in the following way: i the mechanism carries forward AGN’s incremental efficiency gains (or losses) for five years from the year those gains (or losses) occur;
