Volume: 1 Issue: 5 August - September 2015 ` 10/- Bimonthly, Chennai

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1 Volume: 1 Issue: 5 August - September 2015 ` 10/- Bimonthly, Chennai

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3 A Bi-monthly Magazine of Indian Wind Turbine Manufacturers Association Volume: 1 Issue: 5 August - September 2015 Chairman Mr. Madhusudan Khemka Managing Director Regen Powertech Pvt. Ltd., Chennai Vice Chairman Mr. Chintan Shah President & Head, (SBD) Suzlon Energy Limited, Pune Honorary Secretary Mr. Devansh Jain Director, Inox Wind Limited, Noida Executive Members Mr. Ramesh Kymal Chairman & Managing Director Gamesa Renewable Pvt. Ltd., Chennai Mr. Sarvesh Kumar Deputy Managing Director RRB Energy Ltd., New Delhi Mr. V.K. Krishnan Executive Director Leitner Shriram Mfg. Ltd., Chennai Mr. Ajay Mehra Director, Wind World India Limited, Mumbai Secretary General Mr. D.V. Giri, IWTMA, Chennai Contents Page No. Message from Ms. Varsha Joshi, IAS, Joint Secretary, MNRE 3 By 2020 Denmark to Meet its 50% Wind Energy Target 4 With contribution from the Danish Wind Industry Association - by Shruti Shukla (Director, Policy and Projects, GWEC) Wind Energy under Full Sail? 5 Clinton Davis, VP Renewable Solutions, Enterprise Software, ABB, Sacramento, California, USA Forecasting Project in Tamil Nadu - Interview with 9 IWPA Chairman Prof. Dr. K. Kasthurirangaian Scheduling & Forecasting in Rajasthan - An IWTMA Initiatve 12 Om Taneja, Associate Director, IWTMA, New Delhi Wind Energy Forecasting and Scheduling in India 14 Balawant Joshi, Managing Director, Idam Infrastructure Advisory Pvt. Ltd. Mumbai Framework for Scheduling and Forecasting of Renewable Energy 18 Dr. Balaraman K and Chandra Shekhar Reddy Atla M/s Power Research & Development Consultants Pvt Ltd., Bangalore Wind/Solar Power Forecasting and the Way Forward 26 Siddhartha Priyadarshi and Vishal Pandya, REConnect Energy Solutions Private Limited Scheduling and Despatch in Indian Power System 30 Balaji V., Deputy General Manager, SRLDC, POSOCO, Bangalore Know Your Wind Energy State - Tamil Nadu - A Snapshot 34 Compiled by Mr. Nitin Raikar, Suzlon Energy Limited, Mumbai Snippets on Wind Power 36 Photo Feature: Tamil Nadu Global Investors Meet, SAD Meeting 39 Know Your Member - WINDAR Renewable Energy 40 Associate Director and Editor Dr. Rishi Muni Dwivedi, IWTMA, Chennai Views expressed in the magazine are those of the authors and do not necessarily reflect those of the Association, Editor, Publisher or Author's Organization. Indian Wind Turbine Manufacturers Association 4 th Floor, Samson Tower, 403 L, Pantheon Road, Egmore Chennai Tel : Fax : secretarygeneral@indianwindpower.com associatedirector@indianwindpower.com Website : (For Internal Circulation only)

4 From the Desk of the Chairman - IWTMA Dear Readers, Greetings from IWTMA! The Ministry of New and Renewable Energy has announced the 2nd Edition of RE-Invest in February The inaugural session of RE-Invest 2015 inaugurated by the Hon ble Prime Minister of India, made the industry think from MW to GW with a laudable target of 100 GW of Solar, 60 GW of Wind and 15 GW from other RE sources. The endorsement of enthusiasm is still active in the minds of the manufacturing community and the investment community and to a large extent the financial institutions as well. However, State issues of Policies and Regulations on a concurrent subject like power is not allowing capacity addition to take place as the industry expected. As against a target of 4 GW in , the industry lingers around 2.2 GW to 2.3 GW annually. To address this issue, IWTMA along with CII-GBC is conducting Regional Workshops in prominent wind states with all the stakeholders as they are the prime movers in this number crunching game. The Regional Workshops will cover the states of Andhra Pradesh, Telangana, Maharashtra, Gujarat, Rajasthan and Madhya Pradesh and culminate with a National Conclave in Delhi. Various agencies have estimated the wind resource potential of the country and we now have final official Wind Resource Assessment document from National Institute of Wind Energy (NIWE) with a potential of 302 GW. This was formally launched by the Hon ble Minister for Coal, Power and Renewable Energy, Shri. Piyush Goyal, recently in Delhi. While the Green Corridor Development Programme to help connectivity and evacuation is progressing, Government is seized of the exciting opportunities in interstate transaction and not limit to the host state alone. The industry expects waiver of CTU charges and rationalizing STU charges. Wind Power over the years has carried the label of infirm power which is a limitation to higher penetration and a source worry for the State Load Management Centre. Forecasting and Scheduling and its techniques have been practiced in many countries. NIWE has taken up a programme along with MNRE, TANGEDCO and IWPA for forecasting and scheduling of wind power in Tamil Nadu. Similarly, IWTMA has taken up a programme in Rajasthan to be replicated in other wind states. In this issue of INDIAN WIND POWER, we have a special theme on Forecasting and Scheduling with articles contributed by renowned persons in this field. COP21 on Climate Change and Global Warming is due in November 15 in Paris. Many countries are endorsing energy security through RE sources and a few countries have given up coal and oil stocks. IWTMA dedicates itself for energy contribution to control pollution and carbon foot print. We do hope that the thinkers and planners of our country share the same thoughts in our movement towards Clean Green Power Forever. Wishing our Readers a Happy Dussehra and Colourful Diwali to brighten our hopes and future of our nation. With warm regards, Madhusudan Khemka Chairman 2 Indian Wind Power August - September 2015

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6 By 2020 Denmark to Meet its 50% Wind Energy Target With contribution from the Danish Wind Industry Association - by Shruti Shukla (Director, Policy and Projects, GWEC) expected to happen more frequently in the future with more capacity to be built and integrated. Denmark used this surplus electricity in other parts of the energy system especially in the transport and heating sectors. The Danish district heating system covers over 60% of all buildings and provides excellent opportunities for using electricity at times when wind energy production is high and prices are low. Denmark is a unique case study for wind power generation and integration both onshore and offshore. The government s strategic intent is to carry this renewables based transition of its energy system to its logical end i.e. zero dependence on oil and gas. By 2020 Denmark plans for wind energy to occupy a 50% share of its electricity generation as part of its plans to phase out fossil fuels by The share of wind power in the Danish electricity consumption has increased steadily during the last three years from 30% in 2012, to 33% in In 2014, wind turbines provided 39.1% of Danish electricity. This share is expected to grow further this year. Today globally, Denmark has the highest consumption of wind energy on a per capita basis. In 2014, 860 kw of wind energy was installed per 1,000 Danish citizens. In comparison, this number was 250 kw for the other EU-28 countries. Denmark has been a historical leader in the development of wind power technology. It has focused on developing a robust, transnational and flexible integrated energy system, which is capable of handling large volumes of variable renewable energy generation. Denmark s energy system provides secure and stable electricity supply to its consumers, while increasingly integrating wind energy into the grid. From time to time there are days when wind turbines produce more than a 100% of Denmark s electricity needs. This is Decades of successfully integrating wind energy into the power system have given Denmark the know-how and confidence to set a deadline for moving beyond fossil fuel use. According to Energinet.dk, the transmission system operator supplying Denmark with electricity and natural gas, Denmark is in the process of transitioning from an energy system where generation is adapted to consumption to one where consumption is adapted to generation. Implementation of this long-term energy plan requires an increased scalability in energy production, consumption and trading. Grid operators and energy companies are specialised in forecasting the production and demand for renewable energy in Denmark and neighbouring countries (Germany, Norway and Sweden) as part of the Northern European power market. Further efforts are on-going to interlink to the Dutch and the UK power markets. Energinet.dk is working closely with the transmission system operator TenneT, supplying the Dutch and German markets, to build a 700 MW and 320 km submarine cable linking the Danish and Dutch electricity system. Energinet. dk is also working together with National Grid, the transmission system operator in England to assess the possibilities of laying a 600 km cable to the UK. By 2035 wind is likely to meet 75% of the demand for heat and power, with about half of that coming from offshore wind capacity. Denmark s experience with wind power can provide valuable lessons for Indian grid operators and power producers towards meeting the government s stated target of 175GW of renewables based generation by Indian Wind Power August - September 2015

7 Wind Energy under Full Sail? Despite Challenges, Forecasting and Scheduling Technology is helping Wind to become an increasingly Important and Reliable Source of Energy Clinton Davis, VP, Renewable Solutions, Enterprise Software, ABB, Sacramento, California, USA There has never been a more challenging time in the power industry than today, but also perhaps never a time so full of opportunity. One the one hand, modern electricity transmission and distribution networks are undergoing dramatic changes. They have to cope with more distributed and renewable energy resources, more data from smart power equipment and meters and more regulatory pressure to run efficiently. Adding to the complicated changes at play, the typical distribution network is changing from one that connects producers and consumers in a one-way power flow to one that carries flow in both directions in a complex, dynamic way. On the other hand, each day seems to present power producers with new and better ways to leverage the growing resource of renewable energy, particularly wind as installations over the last several years have demonstrated. The ABB Energy Advisors Reference Case models, which provide 25-year forecasts of power markets demonstrate this fact in key markets such as the US and Germany, generally seen as bellwethers for the renewable power industry (see Figures 1 & 2). Thanks to recent developments in energy resource forecasting and scheduling technology, wind has an increasing capacity for greater integration onto the power grid, enhancing wind s reliability as a power source. Figure 1 Source: Internal ABB - ABB Energy Advisors Reference Case model; North American Reference Case August - September 2015 Indian Wind Power 5

8 Figure 2 Source: Internal ABB - ABB Energy Advisors Reference Case model; German Reference Case Improvements in Wind Forecasting Another area where technology is helping power producers to leverage wind is the area of forecasting. Weather-based business forecasting has become a serious business. Advancements in forecasting technology are having a tremendous impact for energy executives calculating future renewable investments. While the nature of forecasts means that outcomes are sometimes far from what was forecasted, no prudent investor or utility will get involved in a renewables project without some pretty serious consideration of how things might look in the future. There s a rough continuum from higher to lower certainty in making predictions. For the forecasting done to determine the viability of prospective wind or solar farms, we can look backward and do a solid job of projecting forward to predict potential availability of sun and wind at a given site. Current forecasting systems also do a good job of helping asset managers and maintenance crews schedule service more efficiently. We see less of the run-to-failure or fixedinterval approaches to decide when to dispatch crews. Instead, asset managers are increasingly assessing actual asset health information to forecast probable mean time between failures. That enables service at a time when it s really needed, but before the turbine blades stop spinning. Short-term forecasts of renewable energy availability continue to improve due to more sophisticated sensors, monitoring and data processing capabilities, and highly granular fundamental climate predictions. Both renewable energy providers and utilities need to know how much power can be produced and available in the coming hours in order to optimize generation and ensure a sufficient supply of power. As the timeframe moves out from hours to decades, we enter the realm of big picture, long-term forecasting that is far more challenging. It s tough to answer questions like What is the value of this wind farm over the next 25 years? with a great deal of certainty. Which isn t to say that this kind of forecasting has no value. It does a tremendous job of providing scenarios related to technical and commercial factors. What happens if the portfolio of available renewables goes up 20 percent in 10 years? Forecasting helps answer some really interesting questions about what should be done to best profit from renewables investment. 6 Indian Wind Power August - September 2015

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10 Advanced Technology for Enhanced Forecasts ABB helps make this a reality with its advanced solutions like Nostradamus and PROMOD. Nostradamus is used for mainly short-term forecasting of renewable resources such as wind and solar, and regional demand. It uses a neural network enabling users to track forecasts with actual values as well as update new information as it becomes available. The neural network algorithm learns the pattern of load or price changes from numerous weather variables as well as day of week, time of year and holidays by learning from historical data. Other input data includes historical load, weather, price, customer /account, transmission, congestion, and generation data. During day to day operations, the system can augment what it has learned with new information (called dynamic weighting adjustment ). Furthermore, Nostradamus can plot actual vs. forecast over time to give the finest detail needed to clearly isolate specific points in time where the new model is not measuring up (see Figure 3). This allows users to make necessary changes quickly. PROMOD takes as input the forecasts and optimizes system operation (generation and transmission) to ensure system demand is met at least cost while conforming to transmission and generation operational, technical and commercial constraints. A generator and portfolio modeling system, PROMOD provides nodal Locational Marginal Price (LMP) forecasting and transmission analysis by producing algorithms that align with the decision focus of management. Among its nodal features are renewable energy curtailment to simulate the effects of intermittent energy schedules from wind on transmission congestion, and forecast the amount of energy that would be curtailed considering the opportunity costs from production tax credits. And, a key zonal feature is power market analysis for quantifying the operating risks associated with each facility and developing a detailed forecast of market prices and system operation under various conditions. Summary Forecasting will never be perfect, but it can be very accurate. Even when it isn t, it is helpful for planning around the volatility and uncertainty of policy, weather, prices and a host of other issues. Considering the critical need to predict commercial, technical and operational aspects of renewable energy generation, forecasting is certainly something to which investors, planners, and operators need to devote considerable attention. Figure 3 Source: Internal ABB 8 Indian Wind Power August - September 2015

11 Forecasting Project in Tamil Nadu - Interview with IWPA Chairman Prof. Dr. K. Kasthurirangaian Introduction: IWPA has taken the initiative in Tamil Nadu for setting up of a State-wide Forecasting mechanism for 7500 MW to enable optimal evacuation of wind energy. To understand this mechanism, Editor, Indian Wind Power magazine and Associate Director, IWTMA (Indian Wind Turbine Manufacturers Association) Dr. Rishi Muni Dwivedi had an interview with IWPA Chairman Prof. Dr. K Kasthurirangaian. We thank him for very clear and specific answers about the project. 1. What is the future of wind energy within the overall energy mix? Dr. K.K.: Wind energy is the only source of energy which does not require water at all. Wind energy installations in India are growing at 27% CAGR (Compound Annual Growth Rate). Currently, India is the fourth largest country in the world in terms of wind energy installations. Given the decisions of various State Electricity Regulatory Commissions about the RPO fixation and its enforcement, we believe it will take the growth of wind energy to 20% of the total energy required by We are hopeful that India will achieve the target of 60 GW, set by the Government. 2. Please tell why your Association has taken up this Forecasting Project? Dr. K.K.: Ideally, this infrastructure should have been facilitated by the Government. Two to three billion units of wind power was being lost each year in 2013 and 2014 because of back down of Wind Mills since there is no mechanism to predict the wind generation and the investors are affected financially. Industries depending on captive power from wind mills were affected the most. Utility lost the opportunity to buy cheap and clean power available in the State. The consumers were also affected. Hence the Association with the support of its Wind Generator Members decided to come forward and sponsor the setting up of the facilities as an industry sponsored project utilizing the capability of NIWE. We are thankful that the MNRE, State Government and NIWE had readily accepted the offer and thus the project is taking shape. Forecasting at Substation Level As you are aware, the high wind season lasts only for five months from May to September every year. If evacuation does not take place during these five months, we will not only lose God s gift of free and clean energy but investors will also loose heavily. 3. Why is Forecasting so essential in evacuating wind energy? Dr. K.K.: Forecasting is essential for scheduling wind energy primarily for the following two reasons: a. Energy should be consumed as soon as it is generated. Presently, we do not have a storage mechanism for such large quantum of energy. b. Wind energy is not only seasonal but is variable and intermittent. We have to provide a visibility to Grid operator as to how much of wind energy is likely to be generated. Wind energy is termed as infirm power since there is wide variation from one day to the next and also the intraday variation can be high. August - September 2015 Indian Wind Power 9

12 Thankfully these days we have the technology to assess with a reasonable degree of accuracy of how much wind energy is likely to be generated in the next 15 minutes, next one hour, next day, one week ahead, etc. The information regarding the likely generation of wind power, will help the SLDC to give visibility of the likely quantum of generation of wind energy and helps to schedule the power thus facilitating evacuation optimally. 4. Why was NIWE chosen as the Forecasting Service Provider? Dr. K.K.: This is an interesting story. We have made this offer of installing the forecasting infrastructure to Tamil Nadu SLDC almost two years back. We had even mentioned that the infrastructure once installed would be the property of the SLDC. However, the SLDC was hesitant to accept this offer from the generators. In February 2015, the Government organized the REINVEST at New Delhi. An ambitious target of 175 GW of renewable energy, which includes 60 GW of wind energy was announced by the Government. The very next month sometime in May 2015, Government soon realised that in order to increase capacity the evacuation problems primarily in Tamil Nadu had to be resolved. As you know, Tamil Nadu accounts for 40% of the wind energy installations in the country. MNRE came to the conclusion that having a reliable forecasting mechanism is the only answer to ensure further growth of the wind industry. Therefore, MNRE in consultation with the SLDC had sanctioned expeditiously a Pilot Forecasting Project in Tamil Nadu at Ayyanaruthu Wind Pooling substation. NIWE was given the responsibility of implementing the project. It was a coincidence that just a year back four of the scientists at NIWE were trained in Spain in the Forecasting software. When we learnt of this development, with the support of most of our Wind Generator Members we offered to sponsor the entire project thus enlarging the scope of the Pilot Project. This proposal was readily accepted by MNRE, NIWE and TANGEDCO. That is how NIWE became an important Forecaster in this Project. 5. What is the MNRE s role in this project? Dr. K.K.: MNRE has been a pillar of support for RE development. Without MNRE s intervention and push this project would not have taken off in such a short notice. The role played by MNRE is crucial not only in the sanctioning of the project but also getting all the constituents together and bringing coordination amongst them. This project is complex and numerous hurdles are coming when we are taking this project forward. Thankfully we are in the last leg and we hope to complete the project by the end of August Therefore, this wind season, the wind generators had benefitted partially but next year we will see the full benefits of installing this Forecasting mechanism. 6. Is the State Utility using the forecast data given by NIWE/IWPA? Dr. K.K.: Presently, we are giving forecast based on the partial installations. However, this has a fairly good accuracy. It is through this process that on August 11, 2015, million units was evacuated which is the highest evacuation till date. The system needs to be finetuned for better accuracy. Since this is the first project of its kind, there is obviously a few teething troubles and some learning involved. It is like learning to ride a bicycle. We may falter here and there before mastering the art of riding the bicycle. Same analogy holds good for the Forecasting exercise. 7. Tell us briefly how this system works? Dr. K.K.: To give a forecast we need the following three inputs: a. Past historical data for two years. This will give the generation pattern in the immediate past. This is a crucial input to the software algorithm for generating the forecast. This data is taken from the past hand written records maintained at the individual Wind Pooling Substations. b. Real time generation of wind energy. This is provided by the setting up of self-consuming energy meters at the Wind Pooling Substations. The meters will furnish real time data i.e. how much wind energy is being generated right now. This real time data is relayed to the servers located at NIWE / SLDC automatically as configured. Generally, when generation is taken across a larger geographic area, the accuracy is better & works out deeper. c. Meteorological Data. This involves getting satellite data of the prevailing weather condition (present and predicted) where all the wind mills are located. Therefore, the GPS coordinates i.e. Latitude and Longitude of each and every wind mill and substation is needed for the purpose as well as hub height & Power curve of WEG. All the three types of data are synthesized in the Forecasting software and the Forecast output is generated. It is through this process that we are able to predict with a reasonable level of accuracy the likely wind generation. It may be mentioned that the accuracy level depends upon the quality of input. If reliable input is given 10 Indian Wind Power August - September 2015

13 then the accuracy goes up otherwise there could be deviations. Nevertheless with the passage of time the Forecasting model has to be trained to provide better accuracy over a period of continuous real time data the accuracy will improve. The deviations can be contained to a single digit. 8. How these data are analysed? Dr. K.K.: The data analysis is done at NIWE. Firstly, the historical data given to NIWE is digitized in a specific form and fed into the software model developed by NIWE in collaboration with Vortex Factoria de Calculs, S.L. a Spanish company which is specialised in Forecasting. NIWE has created an automated system to pick up and process the real-time generation data. This processed input is continuously fed into the forecast model. 9. What are the difficulties in adapting the data? Dr. K.K.: Generally, it is the quality pertaining to the onetime input of historical data. These data are manually recorded since SCADA systems are not available in all the Wind Pooling Sub-stations. Since the historical data is recorded manually it is time consuming to collect data at Site & to digitize and verify the accuracy of the data entry. This has caused a delay in implementing the project. At a few substations, which were newly installed, there are no SCADA data. The specification of the meters as approved by TANGEDCO/ TANTRANSCO had meter reading with two decimals. NIWE wanted more accuracy and insisted on the meter reading to reflect to one millionth of a unit. The meters had to be recalibrated to six decimal units and this further delayed the process. All these meters were custom built exclusively for the project. There were also connectivity issues due to network. For example, a few SS located in remote areas when they face power outages, there is a break in the transmission of data from the individual SS to NIWE. Such incidents affected the flow of real-time data. Real-time generation data is one of the key inputs in updating the forecast data. Due to sudden changes in atmospheric conditions, the pattern may suddenly change, which the software is not able to at times quickly adapt to these sudden changes. These are some of the difficulties we faced when NIWE was analyzing the data, but all have been overcome. 10. What is the current deviation and how can this deviation be minimised and improve the accuracy? Dr. K.K.: Presently on an average the deviation is contained within 10%. With more training and accuracy of inputs, we expect the deviation could be brought down. 11. How will this project fit within the overall framework of the REMC (Renewable Energy Management Centre) proposed by PGCIL (Power Grid Corporation of India Ltd.)? Dr. K.K.: We have been given a draft of the REMC framework and a clear picture is yet to emerge. PGCIL may be installing REMC in TN in We have requested PGCIL officials to expedite installation and promise them all support from IWPA. These details will emerge in the coming months. Wind Atlas Released by NIWE NIWE has released its wind resources assessment findings in the form of a wind atlas launched by the Minister of State (Independent Charge) Power, Coal and New & Renewable Energy, Piyush Goyal, on 2nd September India s installable wind energy potential has been estimated to be 302 GW with towers of a height of 100 metres. This will help in development of hybrid solar and wind systems which would help stabilize the grid and better utilize the transmission network. Earlier, India s wind energy potential was measured to be at around 100 GW with a tower height of 80 metres. NATIONAL INSTITUTE OF WIND ENERGY Formerly Centre for Wind Energy Technology (C-WET) Chennai NIWE is organising 18 th National Training Course on Wind Energy Technology from 26 th to 30 th October 2015 at Chennai. For details please visit the NIWE website or write to pkanagavel.niwe@nic.in. August - September 2015 Indian Wind Power 11

14 Scheduling & Forecasting in Rajasthan - An IWTMA Initiatve Om Taneja, Associate Director, IWTMA, New Delhi IWTMA has taken an initiative of coordinating Scheduling & Forecasting for the state of Rajasthan. The state has the total installed capacity of approx 3300 MW. The major players are Suzlon, Wind World, Inox, Regen Powertech & Gamesa. Most of the projects are SCADA enabled and connected to State Transmission Units (STU) with DISCOM. Presently SLDC is not equipped for analysis of deviation between scheduled power and actual injection. There is no Data integration system in between Pooling substations and SLDC for getting the details of Power injection at any time. SLDC is getting data on phone/ and manually maintain a log book, which is not very reliable as the data is received at different timings, hence not comparable. Availability of actual data of Injected Power is possible only after 30 days from the MRI record. IWTMA is consolidating a forecast of above 2900 MW on day ahead basis and forwarding to SLDC before 10:30 AM daily. This schedule is expected to cover above 3200 MW by end of the year. Presently IWTMA is playing a role as a single co-ordinating agency for compiling all Forecast data as received from various generators and forwarding to SLDC. This exercise is static in nature and IWTMA is working to make the exercise dynamic form of S&F, so that the prevailing Regulations can be adhered to and the exercise is useful for the state. The proposed scheme (tentative) for the exercise is as sketched below. This exercise will be beneficial for all the stakeholders, like developers, generators, SLDC Rajasthan, Power Distribution companies of Rajasthan, Rajasthan discom power procurement centre etc. A study of available systems at Pooling sub stations is under progress and once the study is over, one of the coordinating agencies (aggregator) will be selected to take over, who will be responsible for: Substation 1 Substation 2 Substation 3 Compilation of schedule data included all Revisions, as per regulation for submission to SLDC. Co-ordination with SLDC, RDPPC, Sub Stations, Developers / Investors or any other designated agency. To arrange actual generation report from Developers/ Investors /DISCOM Analysis of Actual & forecasted Data and subsequent effects To prepare Daily, Weekly & Monthly Reports covering Analysis, Shortcomings, issues of curtailment by SLDC, Actual Vs Forecasted Deviation etc. We believe that the State of Rajasthan will be totally connected by accuracy on forecasting and scheduling by the year end. Rajasthan Rajya Vidyut Prasaran Nigam Limited has written to MNRE appreciating the efforts of IWTMA for the initiative taken in collection and consolidation of forecasting data from various generators. GPRS Modem with IEC 104 Protocol GPRS Modem with IEC 104 Protocol GPRS Modem with IEC 104 Protocol GPRS Modem with IEC 104 Protocol Substation N SLDC SCADA in IEC 104 protocol Aggregator s analyzing System 1Mbps OEM Routers 1Mbps 1Mbps Internet Service Provider cloud IWTMA Inox Gamesa Regen Suzlon Windworld 1 12 Indian Wind Power August - September 2015

15 Our groundwork enables our clean energy contribution to touch the sky Our groundwork is what earns us the wings: Robust operations - from concept to commissioning and lifetime care thereafter Comprehensive in-house manufacturing facilities including complete turbines and towers Turbine technology - reliable and proven gearless technology Holistic solutions to all wind energy related financial / regulatory / CDM aspects Proven track record - 18 years of operation; capacities exceeding 4200MW Wind World (India) Ltd. Wind World Towers, Plot No. A-9, Veera Industrial Estate, Veera Desai Rd., Andheri (W), Mumbai , India. Tel: wwil.marketing@windworldindia.com

16 Wind Energy Forecasting and Scheduling in India Balawant Joshi, Managing Director, Idam Infrastructure Advisory Pvt. Ltd., Mumbai Introduction India has the fourth highest wind installed capacity in the world. As on , the total installed capacity for wind energy in India was 23,763 MW. With such large scale wind power deployment, and with even more aggressive target for harnessing the wind energy in the near future, wind industry is going to play a significant role in the operation of electricity markets and power systems. In the past, on several occasions, System Operators in India have been forced to curtail wind energy generation though wind enjoys Must Run status owing to its intermittent nature. This has resulted in loss of generation and revenue for wind projects impacting the project viability. The practice of forecasting wind power generation and scheduling the same is envisaged as a potential solution to tackle the issues posed by the intermittency. This is also expected to increase the acceptability of intermittent generating source like wind among the system operators and allow better management of the Grid. Basics of Forecasting and Scheduling Need for forecasting and scheduling: Given the ambitious target set by Government of India, of adding 60 GW wind power by 2022, there is an urgent need for streamlining the mechanism of forecasting and scheduling wind energy for proper grid integration. Forecasting: The prediction of wind energy available for generation in the future is called forecasting. Forecasting is done with the help of forecasting tools which combines meteorological data (wind speed, temperature, etc.) and turbine level data (type of turbine, installed capacity, swept area, hub height, etc.) into an algorithm and a forecast is generated. Scheduling: The process of generating schedules (in MW or MWh) based on the forecast created on day ahead or intra-day basis for a certain time block (fifteen minutes) for the proper dispatch of energy. Apart from wind energy forecasts, schedules also take into consideration issues such as grid availability, machine maintenance etc. Different approaches to forecasting: Wind forecasting is generally based on the required forecasting horizon; which is broadly categorised based on duration-long term (day ahead/ seasonal) and short term (hour ahead) forecast. The basic approaches for forecasting are enlisted below: Physical Method (Numerical Based): A Numerical Weather Prediction (NWP) model is the commonly used method for forecasting of weather elements represented by equations of physics through the use of numerical methods. Statistical Method: In this method, relationship between wind speed prediction and measured power output from the wind farm is derived to predict the wind power. Hybrid Method: It is a combination of above mentioned forecasting methods with the proper tools. Different approaches to scheduling: The key approaches to scheduling adopted globally are mentioned below: Decentralized Scheduling: In this method each wind farm needs to forecast and schedule its generation. This type of mechanism is preferred for wind generators who wish to participate in open access or day ahead or intraday markets. Centralized Scheduling: In case of centralized scheduling, the forecasting is done by a single entity (the grid operator in most cases) for all wind projects in the control area. Generally, the wind energy generation forecasts prepared for larger control area are consistent and have higher accuracy levels. Integrated Scheduling: It is a combination of the above mentioned scheduling techniques wherein centralized schedules are created for all wind farms in a cluster and decentralized schedule are created for captive and open access wind farms. 14 Indian Wind Power August - September 2015

17 Regulatory Framework for Scheduling in India The concept of forecasting and scheduling of wind generators and commercial settlement thereof was first introduced in Indian context by CERC through Indian Electricity Grid Code (IEGC), The RRF or the Renewable Regulatory Fund mechanism was envisaged to be implemented from January 1, However, owing to several implementation issues, the mechanism was never made operational. In order to formulate an implementable framework, CERC on , issued draft Amendments to (i) the Central Electricity Regulatory Commission (IEGC) Regulations, (ii) the Central Electricity Regulatory Commission (Deviation Settlement Mechanism and Related Matters) Regulations and (iii) the Central Electricity Regulatory Commission (Terms and Conditions for recognition and issuance of Renewable Energy Certificate for RE Generation) Regulations. Based on the comments and suggestions received from various stakeholders, CERC has published the 3 rd amendment to IEGC. It is called Central Electricity Regulatory Commission (IEGC) (Third Amendment) Regulations, 2015 issued on On the same date, CERC also issued 2 nd amendment to regulation for Deviation settlement mechanism and related matters. Brief Snapshot of the Recent Amended Regulations The CERC has amended the IEGC to accommodate mechanism for Forecasting, Scheduling and Imbalance Handling for Renewable Energy (RE) generating stations based on wind and solar energy. The salient features of the framework are mentioned below: Applicability: Wind and Solar generators which are regional entities. Forecasting responsibility: Forecasting shall be done by wind and solar generators which are regional entities as well as by RLDC. The forecast by the concerned RLDC shall be responsible for ensuring secure grid operation while the forecast by wind/solar generators shall be generator centric. Scheduling Responsibility: The responsibility of providing generation schedule lies with wind and solar generators. They have the option of accepting the concerned RLDC s forecast for preparing its schedule or they can prepare schedule based on their own forecast. Revision of schedules: There may be a maximum of 16 revisions for each fixed one and half hour time slot starting from 00:00 hours during the day. Error Calculation: The formula for error calculation is : Error (%) = 100 * (Actual Generation - Scheduled Generation) / (Available Capacity) Where, Available Capacity (AvC) is the cumulative capacity rating of the wind turbines and solar inverters that are capable of generating power in a given time-block. AvC will be equal to the installed capacity unless one or more turbines are under maintenance or shutdown. Imbalance Handling: The tolerance band being proposed is +/-15% for wind and solar generators. The settlement in case of over or under injection would be as follows: Absolute Error in Deviation charges S the 15 minute time payable to Regional No. block DSM pool 1. Within +/- 15% No commercial implication 2. >15% but <= 25% 10% of PPA rate 3. >25% but <=35% 20% of PPA rate 4. > 35% 30% of PPA rate In case of multiple PPAs, the weighted average of the PPA rates shall be taken as the PPA Rate. International Experience In German power sector, currently more than 75 GW of RE capacities are subject to forecasting. The German power transmission system is subdivided into four areas, each run by an independent TSO. Forecasting is done for wind generators located in the control area by the respective TSO. The forecast horizon is typically up to three days and temporal resolution of the forecast is of fifteen minutes to one hour. The Wind Power Management System (WPMS) which is developed by ISET is used by the four TSOs for forecasting of wind power. The accuracy of the predictions has significantly improved over the last year and is roughly above 95%. In order to improve wind power forecasts intense research and development efforts are already on track. In Spain, Red Eléctrica de España, S.A. (REE), the Spanish TSO, is dedicated to the transmission of electricity and the operation of electricity systems of Spain. REE, started a Control Centre of Renewable Energies (CECRE) in 2006, to monitor and control renewable energy generation in Spain and to cope up with the issue of intermittency of these sources. REE was one of the first TSOs in the world to have a power forecasting system integrated with other tools in real-time operations. Hourly forecasts for August - September 2015 Indian Wind Power 15

18 the next 48 hours are computed by region or the node at the transmission system. REE uses forecasts which are computed using single or combination of forecast models provided by multiple forecast providers. REE constantly performs comparison of forecasting errors to track the forecasts with the least error and better performance. It is observed that combined forecast is better since the mean absolute error is the lowest for all time horizons. TSO in Spain was able to reduce the errors with the help of forecasts from multiple forecast providers. Developments in India: Gujarat Owing to high wind energy potential, significant wind power projects have been commissioned in the state of Gujarat. Hence, in order to contain wind generation variability, several initiatives have been undertaken in the state to improve wind energy forecasts and thereby assist System Operators in maintaining the stability of the grid. Analysis of the existing conditions reveals that significant variations exist not only in physical infrastructure but also in institutional mechanisms within the state. A few wind farm developers in Gujarat have initiated forecasting wind generation and providing day-ahead schedules to SLDC. The state has also installed RTUs at all 220 kv and above substations for remote data transfer to SLDCs. Real time renewable energy (Solar & wind) generation data is integrated with existing system and posted on the website of Gujarat SLDC. It is important that the detailed assessment of Gujarat experience of wind forecasting & scheduling is undertaken and gaps in processes, systems and institutional structure are identified for successful implementation of the forecasting and scheduling framework in across India. Key Issues The key issues which need to be addressed for successful implementation of a forecasting and scheduling mechanism would include: ² ² The roles of implementing institutions such as SLDC, RLDC, NLDC and RPC should be clearly defined. ² ² It is important to analyse the preparedness of all wind rich states viz. Gujarat, Rajasthan, Karnataka, Tamil Nadu, Maharashtra, etc., for implementation of such mechanisms at the State level. ² ² Improvement of infrastructure facilities and formulation of suitable procedures, protocols and capacity building/ training of staff at the implementing institutions (SLDC, RLDC, NLDC, RPC, SNA) should be undertaken. Conclusion The level of RE penetration (in terms of energy generated) in India is presently around 5 to 6 percent. While the capability of generators to forecast generation and to provide timely schedules are key requirements, it is equally important that other institutions involved, whether central level or state level are adequately prepared. Apart from wind/solar generators, the implementing institutions such as SLDC, RLDC, NLDC and RPC need to be geared up with adequate infrastructure and trained manpower. We need your Feedback Dear Reader, It is our endeavour to make IWTMA magazine Indian Wind Power, THE MAGAZINE for the Indian Wind Industry. Your feedback on the general impression of the magazine, quality of articles, topics to be covered in future, etc. will be of immense value to us. We are thankful to your response. Kindly address your mail to "associatedirector@indianwindpower.com". Thank You, The Editor - Indian Wind Power Indian Wind Turbine Manufacturers Association 4 th Floor, Samson Tower, 403 L, Pantheon Road, Egmore, Chennai Tel : Fax : associatedirector@indianwindpower.com Advertisements National Institute of Wind Energy 2 nd Wrapper Regen Powertech Private Limited 3 rd Wrapper RRB Energy Limited 4 th Wrapper SKF 7 Wind World India Limited 13 Bonfiglioli Transmissions (Pvt.) Ltd. 17 Gamesa Renewable Pvt. Limited Pioneer Wincon Private Limited 25 LM Wind Power 29 Suzlon 33 NGC Transmission Asia Pacific Pvt Ltd Indian Wind Power August - September 2015

19 Complete Solutions for Yaw & Pitch Control Bonfiglioli is a leading provider of complete packages for the wind industry that seamlessly control energy generation, from rotor blade positioning with a pitch drive to nacelle orientation with a yaw drive. Working closely with customers, Bonfiglioli designs and manufactures a series of specialized wind turbine gearboxes and inverters that deliver reliable, superior performance. Bonfiglioli Transmissions (Pvt.) Ltd. PLOT AC7-AC11, SIDCO Industrial Estate Thirumudivakkam, Chennai , INDIA Ph: +91(044) salesindia.mws@bonfiglioli.com

20 Framework for Scheduling and Forecasting of Renewable Energy Dr. Balaraman K Chandra Shekhar Reddy Atla M/s Power Research & Development Consultants Pvt Ltd., Bangalore 1. Introduction Renewable energy capacity (in particular wind and solar) in India has increased exponentially in the past few years. This increase in variable generation has led to issues in integrating it to the power system in particular in system operation. The system operator has to ensure reliability & security of the system and hence there is a need to forecast and schedule these variable renewable energy generations. Scheduling and forecasting of the wind generation is presently being discussed and debated in India citing its importance and role in system operation and security. Considering the relevance of the subject, a roadmap suggesting possible forecasting and scheduling strategies for India and implementation frameworks for the same are evolved. The roadmap covers: Scheduling process Forecasting services Error computation Data management 2. Scheduling Process As per present regulations in India, decentralized scheduling is adopted which mean that each of the wind farm with the connected capacity of 10 MW and above at interface point to the grid submits its schedule to the system operator. It is observed that most countries prefer centralized or cluster-based scheduling with the concept of virtual power plants. The practices followed are: Centralized scheduling for committed wind farms through PPA: An independent body or system operator carries out the scheduling and forecasting on behalf of all the wind farms. Individual wind farms who participate in the market: The wind farms participate in the open electricity markets through bidding process and settlement takes place according to the market rules. Here, scheduling & forecasting is the responsibility of the wind farm owners. There are advantages and disadvantages of both the approaches. For power system operation and security, the centralized mechanism is preferred. The summary of various methods is described below. 2.1 Decentralized Scheduling Mechanism In this mechanism, each wind farm forecasts and schedules its generation. The mechanism is preferred for wind farms who wish to participate in open access or day ahead or intraday markets. As the schedule is available from individual wind farms, the transmission line congestion would be known in advance and appropriate actions can be initiated. However, each wind farm follows its own forecast mechanism and there is no consistent approach. With many wind farms, the huge number of schedules received by the system operator may create difficulties in managing the schedules. As each wind farm has to maintain the scheduling and forecasting system, there is no optimization of costs as well as forecasting system. The accuracy of the forecasting is also less as compared with cluster or system level due to less geographic area of wind farm considered for forecasting. 2.2 Centralized Scheduling Mechanism The centralized scheduling mechanism would result in reduction in forecast error due to aggregation taking advantage of geographic diversity and smoothing of forecasting errors. This mechanism can provide consistent wind power forecasting and methodology for all wind projects in the region, which will likely lead to more consistent results. With its sheer magnitude and resources, it would promote technological advances and research for better forecasting system. 18 Indian Wind Power August - September 2015

21 The grid operator shall have access to wind generation data (and perhaps on-site weather data from all the wind plants) that can be used to improve the performance of centralized scheduling & forecasting system. Whereas in decentralized forecast method by wind farms, the system operator may not have access to wind generation data because of proprietary or confidentiality reasons. A centralized scheduling system may be able to utilize economies of scale, reducing the cost of forecasting as compared to decentralized forecasting systems. However, the centralized forecasting system may have inconsistency as it can be based on single forecasting methodology and provider. This can be overcome by creating structure with the competitive model and the fees paid to the forecast provider dependent on the accuracy of the forecast. The system operator receives the wind power forecast for entire state or area as one entity and hence the system operator can see one overall wind power forecast value. Under this mechanism system operator does not perform the wind power forecast for individual wind farms. Further, it would be difficult to anticipate transmission line congestion if only the aggregate forecast is available for entire region. It is observed that both the mechanisms have their own merits and would be useful for different purposes. Considering the Indian context where the future wind farms can trade power through any route, adopting any one particular mechanism may not serve the purpose of system operation and security. Hence it is proposed to have an integrated scheduling mechanism where the wind farms entering into PPAs with the utilities would be covered under centralized forecasting system whereas the wind farms that are into captive use or participate in the bilateral market (either through power exchange or third party sales) could follow the decentralized mechanism. 2.3 Integrated Scheduling Mechanism In this approach, it is proposed for centralized wind power forecast for each of the identified clusters and individual, wind farm/solar farm forecast for the investors who wish to participate in the energy market. This provides high accuracy as compared with decentralized forecast due to diversity of wind farms over the area/cluster. These clusters can be described as virtual power plant for all practical purposes. Under this mechanism, system operator can see the wind power forecast values for each cluster. These schedules can be integrated with the EMS (Energy Management System) and would enable the system operator to handle transmission line congestion. With economics of scale, it would be possible to reduce the cost of forecasting and at the same time promote forecast by ensemble methods (i.e., systems that make use of a variety of methodologies or forecast providers) that use five or more forecasting services to improve the forecast accuracy. In this mechanism, all the wind farms in the clusters would be considered (irrespective of date of commissioning) for the forecasting. In view of range of wind turbines commissioned in the last decade, wind farms would be categorized into three levels. First, there are plants that had no turbine and nodal-level generation or meteorological data; these can be labeled as Level 1 wind plants. These include plants that were not included in the data gathering effort and are not metered. Second are the ones in which only total power output is known at the interconnection point (Level 2). These tend to be plants that were not included in the data gathering effort but are metered. These are plants that are technically incapable of providing real-time data and/or are small in installed power. For example, turbines built prior to 2005 tend to be technically incapable of providing real time data via the architected data collection system and plants less than 10 MW were not pursued unless bundled together with other larger plants. Lastly, there are plants which are SCADA connected, that can provide turbine-level and nodal-level details (Level 3). Most of the wind farms commissioned post 2006 have the capability to provide the real time SCADA data (with minor modification in the wind farms wherever it is needed) and would constitute around 70% of the wind generation in country. The level 3 wind farms would form the base for the forecasting and for the remaining wind farms, upscaling methods would be used to arrive at their generation. Thus in the proposed approach, the system operator would have complete information of the wind generation in the cluster and can plan their activity by considering them as virtual power plant for their operation. Individual wind farm who are contracted by captive use and third party sales, would forecast their generation and submit their schedule to the System Operator (SO). The gaming by these wind farms would also be prevented in this approach as the intended generation in the cluster would be known through the centralized forecasting system, and if the schedule deviates beyond certain percentage, then the system operator can initiate appropriate action to correct their schedule. August - September 2015 Indian Wind Power 19

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