white paper JANUARY 2015 Powel Smart nergy Empowering smart decisions

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1 white paper JANUARY 2015 Powel Smart nergy Empowering smart decisions

2 suite - Empowering smart decisions for hydropower companies Table of contents Business benefits... 3 The main work processes Main work processes... 3 Simulation and Optimisation... 4 Inflow forecasting... 4 Outages and constraints... 5 Day-ahead spot market bidding... 6 Reserve market bidding... 6 Monitoring and intra-day replanning... 7 Conclusion About Powel... 8 Contact information

3 Introduction is a comprehensive software suite that is widely used by medium size and large power companies. We support a complete value chain within the following areas: Forecasting Production planning and optimisation Portfolio management Trading Nomination Settlement To support this, suite also offers time series database and data handling, process user interface, and market communication solutions. The is adaptable to a variety of companies within the power business. The focus area of this white paper is the hydropower branch. In particular, it covers short term planning, market bidding and operative intraday use. Business benefits By implementing suite, experience shows that a 2-5% increase in annual revenues from your generation portfolio will be reached. Even close to run-of-the-river systems with limited storage capacity will gain significantly increased revenues. Key success factors are detailed, correct models of the watercourses as well as reliable metering and forecasting of inflows and market prices. The largest achievements are normally caused by improved utilisation of available water resources. Based on precise inflow forecasts and advanced optimisation, the reservoir storage is fully utilised to generate as much hydropower as possible during hours with high demand and prices. Optimal, price dynamic bids in the day-ahead spot market as well as in the reserve markets will cause a higher average pricing level for your valuable water resources. Other main benefits are caused by smoother, safer and faster work processes during the planning work. The Powel Nimbus end-user interface allows daily tasks to be done in a step-by-step, straightforward way. Relevant input data is visualised in a very intuitive way, allowing the operator to detect and correct erroneous data before running e.g. an optimisation or simulation. Key results are immediately displayed, allowing the user to focus on important issues like constraint fulfilment, reservoir usage and total income. Intuitive dashboards allow the operator to monitor the simulated balancing and reserve situation in the hydropower system for coming hours and days, so that future imbalances or constraint violations are detected and resolved by fast replanning. This causes less imbalance costs for the company, and more satisfactory working days for the employees. The ease of use allows you to take full benefits from the system - this is the key success factor. The main work processes The figure below shows the main daily and weekly tasks that are supported by the solution. Starting from the left, input data and forecasts are collected and verified. The long term strategy is normally represented as a water value or end-level window per reservoir, calculated once or twice per week by seasonal planning tools. The input data, including planned outages and constraints are all considered when making optimal, price dependent bids in the day-ahead spot market. When contracts are received from the spot market operator, generation schedules are re-optimised in order to fulfil the contract in the cheapest way. Bids and obligations in reserve or intraday markets are also considered parts of the planning process. The task of sending reserve market bids to the system operator is seamlessly integrated into the work processes. Finally, the monitoring and replanning features are used for intraday planning and event handling during daily operations. Main work processes supported by 3

4 Simulation and optimisation When implementing a solution, one of the first and most important configuration jobs is to define watercourse models. Each hydropower system where reservoirs and power plants are linked by rivers and/or tunnels is normally modelled as a separate watercourse model. Such watercourse models is defined by means of drag and drop methods. A lot of detailed parameters like efficiency curves at different heads, loss factors etc. are supported. Input data, like start reservoir levels and inflow forecasts, is connected to the watercourse by means of multiple input datasets per model. Input data is stored as time series in the underlying time series database, which includes a rock solid Oracle database that is tuned for fast access to large volumes of time series. in order to create maximum revenues while still obeying all constraints in the watercourse. Price dependent bids in the day-ahead spot marked are prepared by optimising with different price forecasts. The optimiser is also used to find the optimal way of fulfilling a given day-ahead plan for all hydropower assets within each price area. The schedules suggested by the optimiser may be used as input to simulations, allowing the operator to make manual changes in the plans. Inflow forecasting Detailed knowledge of seasonal water inflow into your hydropower reservoirs is of course of vital importance for any hydropower system with natural inflow. In order to know your hydropower plant supply situation in the future, you need reliable inflow forecasts. In regions with snow and glaciers, the build-up of snowpack during winter and following snowmelt during springtime is of vital interest both for long term and short term hydropower planning. suite offers comprehensive inflow forecasting. Inflow forecasting contains a set of parameters that are calibrated to adjust the model to fit each given catchment area. An automatic calibration algorithm is used to do the initial calibration based on historical recordings of temperature, precipitation and observed inflow for a period of 2-20 years. If the climatic conditions change or the input data quality improves over time, recalibration may easily be done whenever needed by re-running the automatic calibration. Sample watercourse model, with 3 reservoirs and 3 plants The watercourse model and the connected input data can be used for simulations. A number of scenarios can be set up with different inflow forecasts, constraints and generation plans. For each scenario, the simulation is calculating the behaviour of all reservoirs, waterways, plants and turbines in the entire watercourse. Plans may be input as plant MW or m3/s, or as a reservoir rule curves. The main purpose of doing simulations is to analyse consequences of different plans and scenarios, and to visualise e.g. how reservoir levels will change in the coming days with existing plans and expected inflow. This allows the operator to foresee problems and change plans early enough to avoid spillage or constraint violations. The watercourse model can also be used for optimisation. This is an excellent option for easing the planning work, and at the same time increasing the value of available water resources. The main purpose of the optimiser is to calculate optimal schedules for one or more watercourses, Powel Inflow considers soil water, ground water, snow and glaciers in order to forecast the natural inflow. 4

5 inflow forecasting considers soil water, ground water, snow and glaciers in order to forecast the natural inflow. The model state is updated every morning, based on measured temperature and precipitation for the previous 24 hours. Then new inflow forecasts are calculated based on local temperature and precipitation forecasts. Both a main inflow forecast as well as scenarios can be created. One method for creating scenarios is using weather forecast ensembles as input, preparing approximately 50 different inflow forecasts with various weather conditions. This is an efficient way to analyse the uncertainty in the inflow forecast. The operator may choose among selected alternatives (e.g. dry, normal, wet) for hydropower planning purposes, and may analyse the impact from various inflows on the reservoir levels. Such scenarios are normally created for 14 day forecasts. For long term planning, Powel inflow is able to combine the weather forecast with historical weather data for the past years, to create inflow forecasts based on the current soil and snow conditions. Observed temperature (red) and forecasted snow pack during 1 year Powel Energy inflow forecasting is based on a proven model concept. The model is fast and well suited for inflow forecasting for hydropower generation and gives very precise forecasts. The model is used by our customers for hundreds of catchments every day. The quality of the inflow forecast depends on the quality of the input data. This data needs to be collected automatically, and monitored both by the system and preferably by the operator every day. The only reliable way to forecast the future is by knowing the past! Plant availability example suite offers the possibility to manage both. Revisions (or outages) are defined on unit level, as an ON/OFF parameter which is time dependent. A lot of different repetitive patterns may be applied to ease the definition of complex plant availability schemes. In the example to the left, the availability of a three-unit plant is displayed for a week where one unit is on repair during weekday working hours, and two units are unavailable on Friday. Such revision patterns are easily defined in Powel Smart Energy suite, and the resulting plant availability is automatically calculated. Similarly, various types of restrictions or constraints are also defined. Restriction types range from simple constant restrictions, to complex state and time dependent restrictions. An example of the latter is: When the reservoir level is below 280 meter during spring time, the maximum allowed discharge from the reservoir is 50 m 3 per second. Ensemble forecast example Outages and constraints Both when doing long and short term generation planning, it is very important to know the level of generation capacity available at any time. Basically, the generation capacity is limited in two ways: Due to plant and unit revisions and outages Due to different types of restrictions and constraints Both time and state dependent restrictions are supported by Powel Availability Both revisions and restrictions defined in suite are published as so-called virtual time series. A virtual time series is a time series that has no stored values, but is connected to a calculation expression that generates the contents of the virtual time series whenever it is used. From the outside, the virtual series appears like a normal time series, except that it is read-only. 5

6 These virtual time series are used to calculate plant availability and constraints, both during simulation and optimisation. A wide range of restriction types are supported, among others: Time dependent min/max for reservoir levels and discharge Time dependent min/max for plant and unit generation level Maximum allowed reservoir level change per hour or day (ramping) Maximum allowed discharge level change per hour Min/max average discharge during any part of the optimisation period Min/max average generation during any part of the optimisation period Block restrictions, i.e. optimising with generation unchanged in each block If 3rd party outage planning tools are used, availability data may be imported into the Powel database in XML format, and stored as virtual time series. Day-ahead spot market bidding The generation level of storage based hydropower plants can be varied up and down extremely quickly and at relatively low cost. This allows hydropower to play a key role in the day-ahead electrical energy markets, as a favourable source of energy during peak-demand hours. In addition, hydropower is a major source of ancillary services, as discussed on next page. Calculations of day-ahead spot bid based on multiple scenarios Combined hourly and block Bid Form in Powel Nimbus Reserve market bidding The electricity markets of today are very dynamic, with a wide range of reserve and intraday markets in addition to the day-ahead spot market. If your hydropower assets are to some extent storage or pumped-storage based, it is very important to continuously exploit the possibilities in primary, secondary and tertiary regulation markets as well as in hour ahead markets. The hydropower scheduling and constraint management has a great impact on your options in the intraday and reserve markets. Every time your hydropower schedules are changed, a new set of market possibilities occur. Hence, the hydropower scheduling and the market bidding should preferably be based on one common tool, where the results from short-term optimisation and simulation are seamlessly used as decision support when preparing bids in the ancillary services markets. From suite, you are able to fill in the bid form for ancillary service markets. The bids are sent electronically to the system operator (TSO) as part of the work process, after approval by the operator. When accept or reject messages from the TSO are received, this is monitored in a separate event window and visualised as a dynamic bid status. By utilising the combined possibilities in day-ahead and ancillary services markets in an optimal way, the value of hydropower will be much higher than normal base generation. Optimiser is used to find the generation price sensitivity for every hour of the next day, prior to making the day-ahead bid. Multiple deterministic optimisations are run with Shop for a range of hourly spot price forecast. Based on the optimal generation levels for different prices, a dynamic price dependent bid is calculated. The day-ahead spot Bid Form is built as an integral part of the Powel Nimbus work process. As shown below, Nimbus allows the user to work with both hourly bids and block bids at the same time. The total bid volumes for each hour is shown in the right part of the screen, making it easy to check that bid volumes do not exceed the available generation capacity for each hour. If there is a lower limit for the bid level e.g. due to bilateral agreements or non-regulated generation, Nimbus will notify the user if the bid level is too low. When the Bid Form is filled in and approved by the operator, it is sent to the Power Exchange electronically, directly from the Nimbus work process. 6

7 Monitoring and intra-day replanning At most hydropower companies, there are different groups of employees serving different purposes in the planning process. There might be a diverse mix of hydrologists, power market analysts, traders, short-term planners and power plant operators. By means of the Roles and Tasks concepts in Powel Nimbus process user interface, suitable work processes for all these groups are implemented in a unified way. Each user is assigned to one or more Roles; and will get a personalised To-do task list which is shared with other users of the same Role. The power plant operators who are responsible for the 24/7 dispatch and the real-time unit scheduling, normally have full focus on current and next day. By using a dashboard, both the current status and the expected behaviour of the hydropower system for coming hours are visualised. While a SCADA system is normally limited to monitoring the past, the Nimbus dashboard simulates and shows the expected future as well. This allows the operator to discover and solve potential problems before they occur! Whether generation imbalance is expected in coming hours, a reservoir will spill later today, or primary reserves will be too low, it is discovered in due time and solved by optimal replanning directly from the Dashboard. The Dashboard may be setup so that it automatically re-simulates and refreshes every minute, based on the latest input data and forecasts. This Dashboard allows intuitive monitoring and event-based replanning. Vertical line = now! 7

8 Conclusion When implementing a market bidding and operative planning system for your hydropower assets, there are many considerations to be done. To some extent, your conclusions will depend on the type of hydropower assets you have in your portfolio and the market conditions in your region. However, there are some fundamental rules and advice that will have a great impact on the daily work situation and the average profit margin for almost any hydropower producing company. With customers ranging from 2 to 200 power plants, and from 300 to GWh/year of hydropower generation we hope and believe that our experience is valid also for you. As a summary of our lessons learnt and the topics described on previous pages, we have compiled a top-five list of issues to consider: 1. Make sure the quality of your input data is continuously improving: both by installing high quality metering equipment and by automating the collection, verification and correction of input data. 2. Start building a historical archive of correlated temperature, precipitation and observed inflow as early as possible. Knowing the history is the only way to get reliable inflow forecasts in the future. 3. Define how the bidding and planning tasks should be solved in your company, and make the planning system support your chosen work processes in a user friendly way. In order to take full advantage from advanced optimisation models, ease of use is crucial. 4. Use detailed hydropower models to find the hourly price/volume curves for your hydropower assets, in order to generate robust and profitable price dependent bids in the day-ahead markets. 5. The rapidly growing markets for electricity reserves and ancillary services have opened a new range of business possibilities for pumpedstorage and storage based hydropower. To catch these possibilities, make sure that your hydropower planning system gives decision support for your reserve market bidding in a seamless way. About Powel Unique IT competence and comprehensive knowledge of the power industry experience and in-depth knowledge of open, deregulated and highly competitive markets have positioned Powel as the leading player in its field on the advanced Nordic market. Leading power companies like Axpo, E.ON, Fortum, Norsk Hydro and Statkraft have chosen Powel as their strategic, long-term partner. Business-critical software has been developed in close collaboration with our customers to help them make strategic and operational decisions based on access to timely and accurate information. Since 1996, Powel has grown to be an international corporation with a staff numbering 350, comprised of developers, consultants, and service personnel. Still, the Powel head office remains in Trondheim, Norway, close to the campus of the highly recognised technical university NTNU. All these factors come together to make Powel a world-leading software supplier to the energy sector. Contact information Powel AS Klæbuveien 194, NO-7037 Trondheim Tel: info@powel.no If the above list appeals to you, please contact Powel for further discussions. By combining your knowledge of your hydropower assets and market challenges with our experience and knowledge of the software possibilities, we will together analyse the potential for mutually beneficial cooperation. 8