«C2-103 CIGRE 2014 21, rue d’Artois, F-75008 PARIS : //Operational experience with Dynamic Line Rating forecast-based solutions ...»
C2-103 CIGRE 2014
http : //www.cigre.org
Operational experience with Dynamic Line Rating forecast-based solutions to
increase usable network transfer capacity
H.-M. NGUYEN*1, J.-J. LAMBIN2, F. VASSORT3, J.-L. LILIEN1
Université de Liège1, ELIA2, Ampacimon SA3
This proposed paper focuses on the criteria that need to be met to allow network operators to
effectively use Dynamic Line Ratings in real-life operations. Today DLR has reached a point where the focus of research & testing has moved on from how to determine the most reliable & accurate rating to how to effectively integrate DLR in the processes of the network operators and maximize the use of the network. Different pilot projects in Europe and around the world have proven the DLR technology works in the field and many papers within CIGRE and other organizations highlight those results, but now the focus is shifting to how this technology can be put to best use: where it makes sense and how the results should be used to maximize the benefits while reducing the operational risks. The paper will highlight the experience the Belgian TSO, Elia, has had regarding those questions.
The specific aspects detailed here is the usability of day-ahead forecasting of DLR. Indeed, most decisions regarding network operation and Electricity Market are taken many hours/days in advance; therefore if DLR is to influence these decisions, a reliable forecast of the dynamic rating values is required. This is very similar to the need for the forecast of wind & sun production that allows the safe integration of those intermittent energy sources into the power system. Within the EU-funded FP7 Twenties project, the University of Liège, Belgium, together with Ampacimon has developed such a capability. Elia and Coreso have evaluated the usability of such a DLR forecast value to increase the flexibility of the network, to allow more exchange capacities for the market, and help solve pan-european congestion issues related to the increasing share of intermittent power from RES (Renewable Energy Sources) in the energy mix. Two-day ahead DLR forecast has shown an average capacity improvement of more than 10% over seasonal rating with 98% confidence. The confidence interval may be adjusted to operational needs, as a tradeoff between more gain and more confidence in the forecast has to be set, depending on the risk policy. Different cases may even feature different risk policies, making them flexible as well, e.g. what are the other available options to increase flexibility at that moment? These forecast capacities can then further be used for dayahead management ofPSTs (Phase-Shifting Transformers) in a coordinated way, together HM.Nguyen@ulg.ac.be with stability forecast algorithms developed thanks to PMUs (Phasor Measurement Units) measurements.
The paper will further highlight 3 years of operation of two critical lines located near the North Sea and impacted by the connection of off-shore wind resources using intra-day and day-ahead forecasting of DLR. It will answer the following questions: what were the usable operational gains?, what were the lessons learned ?, how was DLR integrated in the operational tools & processes ?
The conclusion of those experiences shows that innovative solutions emerge from two-day ahead ampacity forecast provided by DLR. They release their full operational capabilities when combined with controllable assets (FACTS, PST, curtailment) and stability monitoring (PMUs) within integrated solutions. They hence achieve the objective of increasing the efficiency of the existing network and help integrate intermittent renewable energy sources in a safe and economical way.
Transmission lines - Dynamic line rating - Thermal rating - Weather forecast – Ampacity - Smart grids – Sensors – Planning – Network - Market.
INTRODUCTIONWind farms and PV development have continuously grown over the past years. In Europe only, wind farm installed capacity was 90GW in 2011 with more than 10% annual growth . This change in the production portfolio generates very significant needs for additional transport & distribution capacity at all levels of the network. It is more and more obvious that replacing, uprating and building the required new electrical power lines (50 000 km in Europe)  will become the main bottleneck to reach the EU 20-20-20 objectives. Therefore it has become mandatory to develop new approaches to increase the efficiency of the existing network assets in a secure way and deliver the required capacity in a timely and economically viable way.
Intermittent & distributed generation significantly changes the characteristics of the power flows in the various networks, increasing the need for capacity but at the same time reducing the line usage factor (MWh transmitted per MW of transmission/distribution capacity) of the network assets due to the increased volatility and variability of the flow patterns. One of the solutions to adapt the system to these new constraints is Dynamic Line Rating (DLR), which allows TSOs and DSOs to monitor their existing assets in real-time and significantly increase the dynamic line capacity, also known as ampacity, over the traditionally used static/seasonal ratings.
Moreover, Dynamic Line Rating of overhead lines combined with Active Network Management have proven to be very promising in this frame , as a strong positive correlation between wind farm generation and an increase of nearby transmission & distribution lines ampacity have been shown.
Extra line capacity is thus available when required, and this without waiting for infrastructure reinforcements/extensions that often lead to both long delays and cumbersome costs. The optimum efficiency is obtained when DLR is combined with the possibility to adapt/curtail generation. When DLR is used, allowing a small percentage of curtailment significantly increases the amount of renewable generation that can be connected to the existing network, and thus gives an optimal solution for all the concerned actors: TSO, DSO and wind farm owners and investors.
However, up to now, few experiments addressed ampacity forecasting, which is of prime interest for TSOs, DSOs and the whole electricity market. Indeed most decisions regarding the operation of the network are taken either one day ahead or 2 days ahead, such as the capacity nominations (NTC) for the cross-border energy markets .
The University of Liège (ULg), Belgium, successfully developed an algorithm based on real-time DLR measurements and weather forecasts within the EU Twenties project to provide two-day ahead ampacity forecasts with controllable prediction interval, despite high sensitivity of dynamic rating w.r.t. low wind speeds, typically hard to measure and forecast .
However, even though very conclusive results have come out of those experiments, system operators are still somehow reluctant to undertake large deployment of DLR systems on their network.
This paper deals with decision making issues TSO’s are facing today, including change in present processes, investment strategies, risk management, complementarity with other available technologies, line installation and operation.
Those issues being extremely vast, only the most prominent ones, gathered in-the-field, will be presented and discussed here.
MAIN ISSUES PREVENTING LARGE DEPLOYMENT OF DLR TECHNOLOGYEven though DLR is today a robust and reliable technology, system operators are still baulking at adopting it massively. The reasons are manifold , and are investigated below.
First, TSOs need to believe in the technology.
That’s the reason why many pilot installations have been driven with successful outcomes these last years. This point can be considered overcome today with collaborating TSOs. Independent measurements have shown that a reliable measurement of the sag (±20cm) could be achieved with the studied DLR sensor. New TSOs wanting to adopt the technology still systematically require a pilot phase, that may be long for the reasons explained below, which has been postponing large deployments. That delay shall however narrows as more and more TSOs adopt DLR to operate their network, particularly when figures can be put on the benefits brought by this technology.
Second, TSOs have to ensure a smooth and global integration of this technology in their IT system, in particular implementing DLR information in their EMS (Energy Management System), preferably through their SCADA. This enables operators to practically make use of the technology, by including DLR data in network security analyses (e.g. N-1 situations), and by keeping the information up-to-date continuously. In this regard, reliability in communication systems has become a major concern for smart grids technologies. In the case of communication failures, safe fallback modes have to be well thought up beforehand, to be able to maintain the system’s security — though functioning in a degraded mode —, until complete restoration.
Third, new processes have to be defined to adapt system operation to DLR. Indeed, highly regulated entities like TSOs follow very strict operating rules and processes. A large-scale deployment of DLR brings a lot of information, which has to be gathered, processed, and managed to come up with decision rules to apply on the field in due time. This thought process is somewhat heuristic, as those processes may vary from one TSO to another, depending on the availability of control tools (FACTS, PSTs, HVDC, ANM, etc.), the particular topology and regulation rules. System operators have to define the most efficient way to deal with this new piece of information and bring it in line with present operator’s
how to gather relevant information in real-time?, how to deal with alerts?, and what are the actions to take in those cases?
Beyond operating processes, installation processes have to be defined as well to speed up the technology deployment. Today, there are no generalised written procedures featuring criteria to determine what kind of line should be installed with DLR, nor which the critical spans to monitor are (including the probability of low wind speed occurrences, and the presence of obstacles below the span).
Fourth, DLR has to be considered from a global perspective. Balancing its investment and implementation with other available smart grids or conventional solutions, taking into account several variables like the type of issue to solve (congestion, curtailment, market,…), implementation lead time, return of investment (ROI), reliability, added flexibility, available manpower, investment prioritisation, as well as the regulatory framework. Some uncertainties, and the lack of preceding experience may push utilities to unfortunately opt for unsuited, but more familiar options. On top of that, no clear methodology has been developed yet to assess the ROI, or avoided costs, provided by DLR. This is a central point that determines large-scale deployment of DLR technologies. If investors don’t have a clear visibility on their investments, experiments will probably be limited to pilot projects. For that matter, the development of medium-term ampacity forecast at a horizon of 2 days brings a great deal of value to DLR, as forecasting firm extra capacity directly impacts the market in a deregulated environment.
PROPOSED SOLUTIONS AND IN-THE-FIELD RESULTS
Confidence in the developed technology has been built over the last six years with collaborating TSOs.
Remarkable reliability of the real-time measurements, significant gain on monitored lines, conclusive results and close cooperation between the product development team and TSOs have proven fruitful (Fig. 1 and 2).
Fig. 1: Studied DLR’s sag measurement vs. independent sag topography measurement showed very good agreement (±20cm).
Fig. 2: typical histogram of power line loading. Static rating is 1000 A. Actual loading on the left hand part (under normal operating conditions) and available ampacity, on the right-hand part, with a trend curve giving the corresponding effective wind speed (same scale as occurrences but in m/s). The black line features other equipment limits as for today.
Integration into TSO’s IT system is the second required stage. Regarding our experiments, a full stand-alone data processing and communication software has been developed, through iterative processes between the University of Liège, the DLR manufacturer, the Belgian TSO (ELIA), and the system integrator as early as 2008. Ampacity and other relevant information are sent in real-time to the EMS, through Electronic Highways (TASE.2 protocol), so that it may be used dynamically for network security calculations (PAS software). A full front-end web-based display has been implemented as well. Safe fallback modes have been implemented, yielding a conservative value for ampacity in case of data inconsistency or communication failure (Fig. 3).
IT operational implementation and integration in TSO’s EMS is today up and running, and is used in operation (real-time and 1h-4h forecast) for the 150kV Bruges-Slijkens line experiment with ELIA.
Less congestion alerts on the equipped line have been reported since by ELIA. The overall benefits (spared actions, redispatching cost, …) has still to be assessed.
Today, those two required stages experience different degrees of completion depending on the DLR system involved.
Fig. 3: IT platform developed for the studied DLR system providing real-time ampacity and short-term forecast.
Those outputs are coupled with TSO’s quarter-hourly network security calculation software.
Fig. 4: DLR and the corresponding one hour ahead forecast, over 12 hours.
Regarding processes, even though some line check-up procedures prior to DLR installation have begun to appear , adapted operation processes, on the other hand, have not been clearly defined today, as practical use of DLR technology remains occasional.
In fact, knowing dynamic rating in real-time is actually not enough, real added value comes with ampacity forecast. Indeed, transmission network is typically operated on a quarter-hourly basis and unless emergency has to be dealt with, dynamic ratings should be known in advance to operate the network properly.