offis-1
Enhanced monitoring and control of MV/LV network – Optimal MV network monitoring and automation
1. Description of the Use Case
1.1. Name of the Use Case
| ID | Area /Domain(s)/Zone(s) | Name of the Use Case |
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| 1 | | offis-1 |
1.2. Version Management
| Version No. | Date | Name of author(s) | Changes | Approval status |
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| 2 | 2014-11-06T00:00:00.000+01:00 | Iberdrola | Final version for XML export | final |
1.3. Scope and Objectives of Use Case
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| Scope | Analysis for optimal automation and monitoring of MV/LV networks |
| Objective(s) | Facilitate the selection of level of automation in terms of Quality of Service and investment. |
| Related business case(s) | |
1.4. Narrative of Use Case
Short description
Nowadays the operation of MV networks creates new challenges for automation. Coupling this
with the worldwide economic situation, efforts for reaching a balance between Quality of Service indexes and
investments in automation and grid reinforcement through simplify methods are worthy. This Use Case
describes this process.
Complete description
Why? Requirements for increasing the level of automation in actual MV networks are rising
currently. The relation between investment in automation and Quality of Service it is not linear. For
example, the location of the same number of devices could lead to a variety of costs as well. Moreover,
initial investment plans might be not affordable due to the actual economic crisis. Therefore, a simulation
program to evaluate different scenarios is proposed to select a compromised point between costs, number of
equipment and propose criterion to locate them. What expectation? / When It is expected a definition of a
methodology to decide the level of automation in MV grids in a simplify manner. It would be based on a
simulation algorithm taking into account investment on equipment in different types of SS and lines, power
reinforcements and evaluation of their impact on the Quality of Service (TIEPI). It is intended to
facilitate decisions during the network planning phase fulfilling technical, cost and regulatory
constraints. What occurs? The main three steps in the process are: Use average values of outages (for
example rate of outages in SS, lines, cables…) and cost units of work to install telecontrol equipment
(cabinet at SS and breakers at lines) to increase the automation of the network. These data are managed by
the DSO after analysing historical records collected in their systems. Simulation phase to evaluate
different scenarios of outages over a simplified MV network portion Selection of compromise solution between
cost and quality of service achieved
| ID | Name | Description | Reference to mentioned use case objectives |
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1.6. Use case conditions
| Assumption | Prerequisite |
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| Availability of historical records of outages, quality indexes and cost for field operations for |
| the selected MV zone. | |
| Relation to other use cases |
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| Level of depth |
| Prioritisation |
| Operational track 1 |
| Generic, regional or national relation |
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| Nature of the use cases |
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| Further keywords for classification |
| MV automation, QoS indexes |
| General remarks |
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| The hypotheses/conditions under which the Use Case is developed are the following: The analysed MV network area is divided in small sections. These sub-sections are selected between two consecutive automatic Secondary Substations (SS). A simplified MV network representation is required in PSS/E to simulate each outage scenario (power flow calculations) Average rates of outages are needed to know the network performance of each area to identified critical zones. These values would be for example per SS (outage/100SS/year), underground lines (outages/100km/year) and aerial lines (outages/100km/year). Regulatory values are used to decide objective targets for simulation (penalties due to QoS). Through the results (graph of QoS vs Investment) a criterion of location for pieces of control equipment (automatic cabinets and telecontrol breakers at lines) is proposed. The proposed level of automation is taking into account by the responsible of each control zone to install the equipment. In Spain the Distribution of electricity is a regulated activity. The remuneration of DSO is charged on customers through the Access Tariffs. This tax joins different concepts. One of them is devoted to cover, theoretically, the distribution activity. The value is decided by the Ministry. From 2008, all DSO are subjected to the same procedure and legal conditions. The remuneration is individually assigned to each DSO taking into account issues such as: incentives per Quality of Service improvements, incentives to reduce the losses, valuation of overcast, effects to cover the foreseen demand and geographical restrictions. Each four (4) year the base value is fixed while yearly some parameters are corrected depending on the DSO performance. The architecture developed in the following section corresponds to the Use Case implementation within a DSO system architecture. However, in the PRICE pilot the approach has been simpler. |
2. Diagrams of Use Case
text
3. Technical Details
3.1. Actors
| Actor Name | Actor Type | Actor Description | Further information specific to this Use Case |
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| Network Operation Statistics and Reporting | | This actor makes it possible to archive on-line data and to perform feedback analysis about system efficiency and reliability. | In the pilot this actor represents the fact of having already average ratios of outages. One possible way to get these values is to analyse historical outages tickets (normally in the DMS- Distribution Management Systems) where information about the outages are stored (start/end times, equipment that failed, power shortage, number of client affected…) |
| Network Operation Simulation | | This actor performs network simulations in order to allow facilities to define, prepare and optimise the sequence of operations required for carrying out maintenance work on the system (release/clearance orders) and operational planning. | In the pilot this actor represents the fact of performing simulations with electrical tools. These analyses consist on evaluating scenarios with different level of automation. |
| Asset Investment Planning | | Asset investment planning involves strategy definition and prioritisation, maintenance strategy planning, risk management, programme management and decision-making. It drives the condition, configuration, performance, operating costs, and flexibility of the asset base, with the aim of maximising value. | In the pilot this actor represents the process of analysing the result of the simulation (a curve of QoS vs Investment) |
3.2. References
| No. | References Type | Reference | Status | Impact on Use Case | Originator / Organisation | Link |
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| 40 | Regulatory constraint | RD 1955/2000 from December 1st | Release 2000 | Business Layer – Definition of QoS indexes and their regulatory limits | Ministry/System Operator | |
| 41 | Regulatory constraint | RD 1634/2006 from December 29th | Release 2006 | Business Layer – update of some QoS limits | Ministry/System Operator | |
| 42 | Regulatory constraint | RD 222/2008 | Release 2008 | Business Layer – description remuneration methodology for DSO activities | Ministry/System Operator | |
| 43 | Regulatory constraint | Orden ICT/3801/2008 | Release 2008 | Business Layer – incentives/penalties for QoS | Ministry/System Operator | |
| 44 | Regulatory constraint | Orden ITC/2524/2009 | Release 2009 | Business Layer – incentives/penalties for losses | Ministry/System Operator | |
| 45 | Report | Ministry web page | Web page | Business Layer – Spanish data base of QoS | Ministry/DSO | |
4. Step by Step Analysis of Use Case
4.1. Overview of Scenarios
| No. | Scenario Name | Scenario Description | Primary Actor | Triggering Event | Pre-Condition | Post-Condition |
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| 1 | Quality Index Analysis | Enhanced monitoring and control of MV/LV network – Optimal MV network monitoring and automation | Network Operation Statistics and Reporting | An outage happens in the network | The outage consequences are storage | QoS indexes and outage ratios are calculated |
| 2 | Switching Simulation | Enhanced monitoring and control of MV/LV network – Optimal MV network monitoring and automation | Network Operation Simulation | Need for simulating different levels and location of automation. | -The model of the network is available with the capacity to simulate different scenarios. -Availability of average cost units for field operations -Availability of average fault rates | Investment vs QoS achieved per each scenario is calculated. |
| 3 | Decision Support | Enhanced monitoring and control of MV/LV network – Optimal MV network monitoring and automation | Asset Investment Planning | End of the simulation of automation scenarios | The curve with Investment vs QoS achieved per each scenario is available | A compromise solution for the level of automation is taken based on technical, economical and regulated aspects. |
Notes
4.2. Steps – Scenarios
| Scenario Name: |
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| Quality Index Analysis |
| Step No. | Event. | Name of Process/ Activity | Description of Process/ Activity. | Service | Information Producer (Actor) | Information Receiver (Actor) | Information Exchanged | Requirements, R-ID |
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| 1 | Periodically | Get outage average ratio | Enhanced monitoring and control of MV/LV network – Optimal MV network monitoring and automation | INTERNAL PROCESS | 523 | 523 | | not sure how to get this |
| Scenario Name: |
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| Switching Simulation |
| Step No. | Event. | Name of Process/ Activity | Description of Process/ Activity. | Service | Information Producer (Actor) | Information Receiver (Actor) | Information Exchanged | Requirements, R-ID |
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| 1 | Punctual | Ask for simulation | Enhanced monitoring and control of MV/LV network – Optimal MV network monitoring and automation | GET | 511 | 526 | | not sure how to get this |
| 2 | Punctual | Ask for information | Enhanced monitoring and control of MV/LV network – Optimal MV network monitoring and automation | GET | 526 | 523 | | not sure how to get this |
| 3 | Punctual | Send information | Enhanced monitoring and control of MV/LV network – Optimal MV network monitoring and automation | SHOW | 523 | 526 | | not sure how to get this |
| 4 | Iterative | Algorithm operation | Enhanced monitoring and control of MV/LV network – Optimal MV network monitoring and automation | INTERNAL PROCESS | 526 | 526 | | not sure how to get this |
| Scenario Name: |
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| Decision Support |
| Step No. | Event. | Name of Process/ Activity | Description of Process/ Activity. | Service | Information Producer (Actor) | Information Receiver (Actor) | Information Exchanged | Requirements, R-ID |
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| 1 | Punctual | Send simulation results | Enhanced monitoring and control of MV/LV network – Optimal MV network monitoring and automation | SHOW | 526 | 511 | | not sure how to get this |
| 2 | Punctual | Decision taken process | Enhanced monitoring and control of MV/LV network – Optimal MV network monitoring and automation | INTERNAL PROCESS | 511 | 511 | | not sure how to get this |
| Information exchanged ID | Name of Information | Description of Information Exchanged | Requirement |
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6. Requirements (optional)
7. Common Terms and Definitions
| Key | Value | Refers to Section |
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