IEA Wind Recommended Practice for the Implementation of Renewable Energy Forecasting Solutions

Front Cover
IEA Wind Recommended Practice for the Implementation of Renewable Energy Forecasting Solutions
Copyright
Contents
List of figures
List of tables
Biography
	Dr. Corinna Möhrlen
	Dr. John W. Zack
	Dr. Gregor Giebel
Preface
About the IEA Wind TCP and Task 36 and 51
Part 1 Forecast solution selection process
	1 Forecast solution selection process
		1.1 Before you start reading
		1.2 Background and introduction
		1.3 Objectives
		1.4 Definitions
	2 Initial considerations
		2.1 Tackling the task of engaging a forecaster for the first time
		2.2 Purpose and requirements of a forecasting solution
		2.3 Adding uncertainty forecasts to forecasting solutions
		2.4 Information table for specific topic targets
	3 Decision support tool
		3.1 Initial forecast system planning
		3.2 IT infrastructure considerations
			3.2.1 IT requirements for single versus multiple forecast vendors
			3.2.2 IT requirements for deterministic versus probabilistic forecasts
		3.3 Establishment of a requirement list
			3.3.1 Requirement list
		3.4 Short-term solution
		3.5 Long-term solution
		3.6 Going forward with an established IT system
		3.7 Complexity level of the existing IT solution
		3.8 Selection of a new vendor versus benchmarking existing vendor
		3.9 RFP evaluation criteria for a forecast solution
			3.9.1 Forecast solution type
				3.9.1.1 Single versus multiple forecast providers
				3.9.1.2 Deterministic versus probabilistic
				3.9.1.3 Forecast horizons
			3.9.2 Vendor capabilities
				3.9.2.1 Experience and reliability
				3.9.2.2 Ability to maintain state-of-the-art performance
				3.9.2.3 Performance incentive schemes
			3.9.3 Evaluation of services
				3.9.3.1 Price versus value and quality
				3.9.3.2 Forecast performance
				3.9.3.3 Solution characteristics
				3.9.3.4 Support structure
				3.9.3.5 Redundancy structure
				3.9.3.6 Escalation structure
		3.10 Forecast methodology selection for use of probabilistic forecasts
			3.10.1 Definitions of uncertainty
			3.10.2 Uncertainty forecasting methods
			3.10.3 Training tools for ensemble forecasting
			3.10.4 Applications of uncertainty forecasts in the energy industry
			3.10.5 Visualization of forecast uncertainty
	4 Data communication
		4.1 Terminology
		4.2 Data description
			4.2.1 LEVEL 1 – data description
		4.3 Data format and exchange
			4.3.1 LEVEL 1 data format and exchange
			4.3.2 LEVEL 2 – data format and exchange
		4.4 Sample formatted template files and schemas
	5 Concluding remarks
Part 2 Designing and executing forecasting benchmarks and trials
	6 Designing and executing benchmarks and trials
		6.1 Before you start reading
		6.2 Background and introduction
		6.3 Definitions
			6.3.1 Renewable energy forecast benchmark
			6.3.2 Renewable energy forecast trial
		6.4 Objectives
	7 Initial considerations
		7.1 Deciding whether to conduct a trial or benchmark
		7.2 Benefits of trials and benchmarks
		7.3 Limitations with trials and benchmarks
		7.4 Time lines and forecast periods in a trial or benchmark
		7.5 1-Page ``cheat sheet'' checklist
	8 Conducting a benchmark or trial
		8.1 Phase 1: preparation
			8.1.1 Key considerations in the preparation phase
			8.1.2 Metadata gathering in the preparation phase
			8.1.3 Historical data gathering in the preparation phase
			8.1.4 IT/data considerations in the preparation phase
			8.1.5 Communication in the preparation phase
			8.1.6 Test run in the preparation phase
		8.2 Phase 2: During benchmark/trial
			8.2.1 Communication during the b/t
			8.2.2 Forecast validation and reporting during the b/t
		8.3 Phase 3: Post trial or benchmark
			8.3.1 Communication at the end of the b/t
			8.3.2 Forecast validation & reporting after the b/t
	9 Considerations for probabilistic benchmarks and trials
		9.1 Preparation phase challenges for probabilistic b/t
		9.2 Evaluation challenges for probabilistic b/t
	10 Best practice recommendations for benchmarks/trials
		10.1 Best practice for b/t
		10.2 Pitfalls to avoid
Part 3 Forecast solution evaluation
	11 Forecast solution evaluation
		11.1 Before you start reading
		11.2 Background and introduction
	12 Overview of evaluation uncertainty
		12.1 Representativeness
			12.1.1 Size and composition of the evaluation sample
			12.1.2 Data quality
			12.1.3 Forecast submission control
			12.1.4 Process information dissemination
		12.2 Significance
			12.2.1 Quantification of uncertainty
				12.2.1.1 Method 1: repeating the evaluation task
				12.2.1.2 Method 2: bootstrap resampling
		12.3 Relevance
	13 Measurement data processing and control
		13.1 Uncertainty of instrumentation signals and measurements
		13.2 Measurement data reporting and collection
			13.2.1 Non-weather related production reductions
			13.2.2 Aggregation of measurement data in time and space
		13.3 Measurement data processing and archiving
		13.4 Quality assurance and quality control
	14 Assessment of forecast performance
		14.1 Forecast attributes at metric selection
			14.1.1 ``Typical'' error metrics
			14.1.2 Outlier/extreme error
			14.1.3 Empirical error distribution
			14.1.4 Binary or multi-criteria events
		14.2 Prediction intervals and predictive distributions
		14.3 Probabilistic forecast assessment methods
			14.3.1 Brier scores
			14.3.2 Ranked probability (skill) score (RP(S)s)
				14.3.2.1 The continuous ranked probability skill and energy score
				14.3.2.2 Logarithmic and variogram scoring rules
			14.3.3 Reliability measures
				14.3.3.1 Rank histogram
				14.3.3.2 Reliability (calibration) diagram
			14.3.4 Event discrimination ability: relative operating characteristic (ROC)
			14.3.5 Uncertainty in forecasts: Rény entropy
		14.4 Metric-based forecast optimization
		14.5 Post-processing of ensemble forecasts
	15 Best practice recommendations for forecast evaluation
		15.1 Developing an evaluation framework
			15.1.1 Scoring rules for comparison of forecast types
			15.1.2 Forecast and forecast error analysis
			15.1.3 Choice of deterministic verification methods
				15.1.3.1 Dichotomous event evaluation
				15.1.3.2 Analyzing forecast error spread with box and wiskers plots
				15.1.3.3 Visualizing the error frequency distribution with histograms
			15.1.4 Specific probabilistic forecast verification
				15.1.4.1 Choice of application for benchmarking probabilistic forecasts
			15.1.5 Establishing a cost function or evaluation matrix
				15.1.5.1 Evaluation matrix
		15.2 Operational forecast value maximization
			15.2.1 Performance monitoring
				15.2.1.1 Importance of performance monitoring for different time periods
			15.2.2 Forecast diagnostics and continuous improvement
			15.2.3 Maximization of forecast value
			15.2.4 Maintaining state-of-the-art performance
				15.2.4.1 Significance test for new developments
			15.2.5 Incentivization
		15.3 Evaluation of benchmarks and trials
			15.3.1 Applying the principles of representativeness, significance, and relevance
			15.3.2 Evaluation preparation in the execution phase
			15.3.3 Performance analysis in the evaluation phase
			15.3.4 Evaluation examples from a benchmark
		15.4 Use cases
			15.4.1 Energy trading and balancing
				15.4.1.1 Forecast error cost functions
			15.4.2 General ramping forecasts
				15.4.2.1 Amplitude versus phase
				15.4.2.2 Costs of false alarms
			15.4.3 Evaluation of probabilistic ramp forecasts for reserve allocation
				15.4.3.1 Definition of error conditions for the forecast
Part 4 Meteorological and power data requirements for real-time forecasting applications
	16 Meteorological and power data requirements for real-time forecasting applications
		16.1 Before you start reading
		16.2 Background and introduction
		16.3 Structure and recommended use
	17 Use and application of real-time meteorological measurements
		17.1 Application-specific requirements
			17.1.1 Application-specific requirements for meteorological data
			17.1.2 Applications in system operation, balancing and trading
			17.1.3 Applications in wind turbine and wind farm operation
			17.1.4 Solar/PV plant operation
		17.2 Available and applicable standards for real-time meteorological and power measurements
			17.2.1 Standards and guidelines for wind measurements
			17.2.2 Standards and guidelines for solar measurements
		17.3 Standards and guidelines for general meteorological measurements
		17.4 Data communication
	18 Meteorological instrumentation for real-time operation
		18.1 Instrumentation for wind projects
			18.1.1 Cup anemometers
			18.1.2 Sonic and ultra-sonic anemometers
			18.1.3 Remote sensing devices
			18.1.4 Met mast sensor deployment
			18.1.5 Nacelle sensor deployment
		18.2 Instrumentation for solar projects
			18.2.1 Point measurements
			18.2.2 All sky imagers
			18.2.3 Satellite data
	19 Power measurements for real-time operation
		19.1 Live power and related measurements
		19.2 Measurement systems
			19.2.1 Connection-point meters
			19.2.2 Wind power SCADA systems
			19.2.3 Solar power SCADA systems
		19.3 Power available signals
			19.3.1 Embedded wind and solar ``behind the meter''
		19.4 Live power data in forecasting
			19.4.1 Specifics for producers of forecasts
			19.4.2 Specifics for consumers/users of forecasts
		19.5 Summary of best practices
	20 Measurement setup and calibration
		20.1 Selection of instrumentation
			20.1.1 Selection of instrumentation for wind projects
			20.1.2 Selection of instrumentation for solar power plants
			20.1.3 Measurement characteristics of different technologies
				20.1.3.1 Measurement characteristics of LIDARs
				20.1.3.2 Lightning effects on instrumentation
				20.1.3.3 Measurement characteristics of SODARs
		20.2 Location of measurements
			20.2.1 Location of representative measurements for wind projects
			20.2.2 Location of representative measurements for solar projects
		20.3 Maintenance and inspection schedules
			20.3.1 Maintenance of radiometers
	21 Assessment of instrumentation performance
		21.1 Measurement data processing
		21.2 Uncertainty expression in measurements
		21.3 Known issues of uncertainty in specific instrumentation
			21.3.1 Effects of uncertainty in nacelle wind speed measurements and mitigation methods
				21.3.1.1 Wind speed reduction in the induction zone
				21.3.1.2 Wake effects from rotating blades
				21.3.1.3 Yaw misalignment of wind turbine for scanning LIDARs
			21.3.2 Application of nacelle wind speeds in real-time NWP data assimilation
			21.3.3 Known uncertainty in radiation measurements
		21.4 General data quality control and quality assurance (QCQA)
		21.5 Historic quality control (QC)
			21.5.1 QC for wind forecasting applications
				21.5.1.1 Specific control procedures
				21.5.1.2 Practical methodology for quality control of measurement for wind applications
				21.5.1.3 Statistical tests and metrics for the QC process
			21.5.2 QC for solar applications
		21.6 Real-time quality control (QC)
			21.6.1 Data screening in real-time wind and solar forecast applications
			21.6.2 Data sampling thresholds in real-time wind and solar forecast applications
			21.6.3 Real-time QC for wind and solar applications
				21.6.3.1 Data screening
			21.6.4 Solar forecasting specific real-time QC
	22 Best practice recommendations
		22.1 Definitions
		22.2 Instrumentation
		22.3 Recommendations for real-time measurements by application type
		22.4 Recommendations for real-time measurements for power grid and utility-scale operation
			22.4.1 Recommendations on quality requirements
				22.4.1.1 Requirements for wind forecasting applications according to environment
				22.4.1.2 Wind measurement alternatives to met masts
				22.4.1.3 Recommendations for solar forecasting applications
				22.4.1.4 Recommendations for power measurements for real-time wind and solar forecasting
			22.4.2 Accuracy and resolution recommendations
			22.4.3 Validation and verification recommendations
				22.4.3.1 Practical methodology for historic quality control of meteorological measurements
				22.4.3.2 Data screening in real-time environments
		22.5 Recommendations for real-time measurements for power plant operation and monitoring
			22.5.1 Data quality recommendations
				22.5.1.1 Requirement recommendations for wind farms
				22.5.1.2 Requirement recommendations for wind farms using remote sensing
				22.5.1.3 Requirement recommendations for solar plants
			22.5.2 Validation and verification recommendations
				22.5.2.1 Statistical test and metric recommendations for the QC process
				22.5.2.2 Solar specific validation recommendations
				22.5.2.3 Performance control recommendations for hardware and manufacturer production guarantees
		22.6 Recommendations for real-time measurements for power trading in electricity markets
			22.6.1 Trading strategies with real-time measurements
			22.6.2 Quality recommendations
			22.6.3 Accuracy and resolution requirement recommendations
	23 End note
A Clarification questions for forecast solutions
	Ask questions to the vendors
		Typical questions for Part 1
		Typical questions for Part 2
B Typical RFI questions prior to or in an RFP
C Application examples for use of probabilistic uncertainty forecasts
	C.1 Example of the graphical visualization of an operational dynamic reserve prediction system at a system operator
	C.2 High-speed shut down warning system
D Metadata checklist
E Sample forecast file structures
	E.1 XSD template example for forecasts and SCADA
	E.2 XSD SCADA template for exchange of real-time measurements
F Standard statistical metrics
	F.1 BIAS
	F.2 MAE – mean absolute error
	F.3 RMSE – root mean squared error
	F.4 Correlation
	F.5 Standard deviation
	F.6 What makes a forecast ``good''?
G Validation and verification code examples
	G.1 IEA wind task 36 and task 51 specific V&V code examples
	G.2 Code examples from related projects with relevance to recommendations
H Examples of system operator met measurement requirements
	H.1 Examples of requirements in different jurisdictions
	H.2 Met measurement requirement example from California independent system operator in USA
	H.3 Met measurement requirement example from Irish system operator EIRGRID group
	H.4 Met measurement requirement example from Alberta electric system operator in Canada
Bibliography
Nomenclature
Index
Back Cover