The ISP is executed as a Mixed Integer Linear Programming model.
The quantity of the upward ISP Balancing Energy Offer taken into account in the ISP corresponds to the difference between the Available Capacity of the Balancing Service Provider and the capacity resulting from the Balancing Service Provider's Market Schedule, as in force at the time of submission of the Offer. The quantity of the downward ISP Balancing Energy Offer corresponds to the difference between zero quantity and the capacity resulting from the Balancing Service Provider's Market Schedule as in force at the time of submission of the Offer. If the Balancing Energy prices of the ISP Balancing Energy Offers for the same Dispatch Period arithmetically coincide, and the respective Balancing Energy quantities of such ISP Balancing Energy Offers are not fully included in the ISP results, then the following order of priority shall be applied for the bidding segments: (a) Dispatchable RES Units Portfolio, (b) Dispatchable hydro Generating Units, (c) Dispatchable Load Portfolio, and (d) Dispatchable thermal Generating Units. Among bidding segments that belong to the same category, priority shall be given to the segments of the offers corresponding to the Balancing Service Entity with the highest Ramp Up Rate. For bidding segments that come into the same category and have the same Ramp Up Rate there will be random selection.
If the Balancing Capacity prices of the Balancing Capacity Offers for the same Dispatch Period arithmetically coincide, and the respective Balancing Capacity quantities of those Balancing Capacity Offers are not fully included in the ISP results, the bidding segments shall be selected in the following order of priority: (a) Dispatchable RES Units Portfolio, (b) Dispatchable hydro Generating Units, (c) Dispatchable Load Portfolio, and (d) Dispatchable thermal Generating Units. Among bidding segments that belong to the same category, priority shall be given to the segments of the offers corresponding to the Balancing Service Entity with the highest Ramp Up Rate. For bidding segments that come into the same category and have the same Ramp Up Rate there will be random selection.
The Integrated Scheduling Process Optimization Algorithm is briefly described as follows:
a) The ISP execution produces:
i. the commitment status of each Balancing Service Entity, for each Dispatch Period of the Dispatch Day,
ii. the upward and downward Balancing Capacity for FCR in MW per Balancing Service Entity for each Dispatch Period of the Dispatch Day,
iii. the upward and downward Balancing Capacity for aFRR in MW per Balancing Service Entity for each Dispatch Period of the Dispatch Day,
iv. the upward and downward Balancing Capacity for mFRR in MW per Balancing Service Entity for each Dispatch Period of the Dispatch Day,
v. the inter-zonal flows,
vi. the potential energy surplus in MW for every Dispatch Period of the Dispatch Day, and
vii. the Balancing Capacity requirements limitation in MW, when required, for every Dispatch Period of the Dispatch Day.
b) The algorithm works in such a way that the total Balancing Energy and Balancing Capacity procurement cost is minimized. The total cost of providing Balancing Energy may include the estimated cost of real-time activation of Balancing Capacity. Total cost of Balancing Energy and Balancing Capacity procurement means the sum of the Balancing Energy and Balancing Capacity procurement for all Dispatch Periods of Dispatch Day D in the case of ISP1 and ISP2, or for the remaining Dispatch Periods of Dispatch Day D in the case of ISP3 and any other execution of any ad hoc ISP during the Dispatch Day.
c) The algorithm must comply with the following constraints:
i. the HETS Imbalances constraint, according to which the sum of the allocated upward and downward ISP Balancing Energy is equal to the forecasted HETS Imbalances, per Bidding Zone and as a total,
ii. the inter-zonal constraints,
iii. the sum of the Balancing Capacity for FCR of all Balancing Service Entities that have been chosen to provide Balancing Capacity for FCR must be greater than or equal to the total requirements per Bidding Zone or/and of HETS as a whole with respect to upward and downward Balancing Capacity for FCR,
iv. the sum of the Balancing Capacity for aFRR of all Balancing Service Entities that have been chosen to provide Balancing Capacity for aFRR must be greater than or equal to the total requirements per Bidding Zone or/and of HETS as a whole or of the bidding zone with respect to upward and downward Balancing Capacity for aFRR,
v. the sum of Ramp Up or Ramp Down Rates of Balancing Service Entities that have been selected to provide Balancing Capacity for aFRR must be greater than or equal to the total requirements of the HETS with respect to Ramp Up and Ramp Down Rates for aFRR,
vi. the sum of the Balancing Capacity for mFRR of all Balancing Service Entities that have been chosen to provide Balancing Capacity for mFRR must be greater than or equal to the total requirements per Bidding Zone or/and of HETS as a whole with respect to upward and downward Balancing Capacity for mFRR,
vii. the updated operation schedules of generating units in Commissioning Operation,
viii. the updated operation schedules of Dispatchable Generating Units in Testing Operation,
ix. the daily mandatory hydro management declarations,
x. the technical constraints of the Balancing Service Entities that are included in their Declared Characteristics such as Balancing capacity supply constraints, Balancing Energy constraints, Technically Minimum Generation and Maximum Net Capacity and Available Capacity constraints under normal operation or under AGC, synchronization time, soak time and desynchronization time, time and generation of the Dispatchable Generating Unit between synchronization and the Technically Minimum Generation, the logical status of commitment constraints, the minimum up/down time constraints, the ramp rate of power output and Balancing Capacity of the Units constraints, the Maximum Operating Time per activation and the Maximum Number of Activations per Dispatch Day,
xi. the constraints on the maximum daily energy injection from Dispatchable Natural Gas Generating Units,
xii. the constraints on the maximum daily energy injection from Dispatchable Hydro Generating Units based on the constraints declarations for maximum daily energy injection from Dispatchable Hydro Generating Units,
xiii. in each Dispatch Period, pumped storage Dispatchable Hydro Generating Units shall operate either as Dispatchable Generating Units or as pumping loads,
xiv. in each Dispatch Period the Dispatchable Multi-Shaft Combined Cycle Generating Units shall operate only in one configuration,
xv. in each Dispatch Period, the Dispatchable Load Portfolios may be allocated either as (a) Balancing Energy for mFRR and/or FCR or (b) Balancing Energy for aFRR and/or FCR. Additionally, if the Dispatchable Load Portfolio has a non-zero Market Schedule or a non-zero ISP Schedule during a Dispatch Period, it cannot be assigned aFRR Balancing Energy.
xvi. In each Dispatch Period, Dispatchable Intermittent RES Units Portfolio may be allocated either as (a) Balancing Energy for mFRR and/or FCR or (b) Balancing Energy for aFRR and/or FCR. In addition, if the Dispatchable Intermittent RES Unit Portfolio has a non-zero ISP Schedule during a Dispatch Period, it cannot be assigned aFRR Balancing Energy,
xvii. the constraints for the transition between two virtual entities, as those are defined and specified in the Technical Decision “Integrated Scheduling Process”.
d) In cases where observance of the energy balance is not feasible, in order to achieve the desired convergence of the algorithm, and especially in cases of excess energy, the algorithm may resolve it by displaying the energy surplus in the ISP results. Relevant details are described in the Technical Decision “Integrated Scheduling Process”.
e) In cases where maintaining Balancing Capacity zonal/systemic requirements is not feasible, in order to achieve the desired algorithm convergence, the algorithm may solve by limiting the Balancing Capacity requirements up to a maximum specified volume. Relevant details are described in the Technical Decision “Integrated Scheduling Process”.
In the event that, after resolution of the ISP, coverage of anticipated imbalances and/or zonal/systemic Balancing Capacity requirements remains impossible, any available ISP Balancing Energy Offers for Contracted Generating Units shall be included, the following constraints shall be gradually lifted, and the ISP shall be executed again. The procedure for lifting constraints is as follows:
a) First of all, the constraint on Balancing Capacity requirements for upward and downward mFRR is not implemented across its full range,
b) Then, the Balancing Capacity requirements constraint for upward and downward FCR is not implemented in its entire range,
c) Furthermore, the constraint on Balancing Capacity requirements for upward and downward aFRR is not implemented across its full range,
d) Finally, the HETS Imbalances constraint is not implemented in its entire range.
The HETS Operator shall include in the ISP data the declarations of maximum daily energy injection constraint from Dispatchable Natural Gas Generating Units. The quantity of injected electricity that is included in the ISP for the Dispatchable Natural Gas Generating Units, to which the submitted declarations of maximum daily energy injection constraint from Dispatchable Natural Gas Generating Units refer, may not exceed the quantity specified in the above declarations.
The HETS Operator shall include in the ISP data the declarations of maximum daily energy injection constraint from Dispatchable hydro Generating Units. The quantity of injected electricity that is included in the ISP for the Dispatchable hydro Generating Units, to which the submitted declarations of maximum daily energy injection constraint from Dispatchable hydro Generating Units refer, may not exceed the quantity specified in the above declarations.
SECTION IV INTEGRATED SCHEDULING PROCESS
CHAPTER 13 EXECUTION OF THE INTEGRATED SCHEDULING PROCESS
Article 13.2 Integrated Scheduling Process Optimization Methodology and Algorithm