1. Kevin Tomsovic* and Mengstab Gebremicael School or Electrical Engineering and Computer Science Washington State University * Currently on leave at National Science Foundation Modeling the Interaction between the Technical, Social, Economic and Environmental Components of Large Scale Electric Power Systems

2. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 2 Outline of Presentation Some Observations and Questions When should we expect power plant construction Expansion of WSU’s Work in Several Areas Collaboration in Research System Dynamics Overall Study Approach Study Bench Marks Actual Model in Simulink Conclusions and future works

3. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 3 Some Observations and Questions Deregulation has been met in every case by unintended consequences, some reaching the level of a crisis Deregulation has been met in every case by unintended consequences, some reaching the level of a crisis The electric power industry has historically gone through periods of boom and bust cycles. The electric power industry has historically gone through periods of boom and bust cycles. Is it the fundamental nature of generation investment and technology that leads to these cycles and crises? Is it the fundamental nature of generation investment and technology that leads to these cycles and crises? Do transmission system limits and reliability considerations exacerbate the difficulty of predicting policy outcomes? Do transmission system limits and reliability considerations exacerbate the difficulty of predicting policy outcomes? How are the cycles influenced by the new market policies? How are the cycles influenced by the new market policies? How do various incentives programs (e.g. capacity payment, tradable green certificates) impact the planning process?  Can regulatory policies and new engineering approaches relieve these cycles and resulting societal costs?

4. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 4 Disparate System Views System dynamics research shows the tendency towards boom/bust cycles from generation investment and construction permit policies. Engineers understand the operating limits of the transmission system. Economists know market structures that generally lead to more efficient economic behavior from suppliers. Policy makers may set goals based on limited understanding of operations, e.g., 20% renewables in 20 years.  But how do these areas interact?

5. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 5 When should we expect power plant construction to appear? Just in time to cause the market to clear at an average annual price that matches the total cost of a new power plant? In waves of boom and bust? Textbook answer: –Construction will appear just in time to keep market prices at the cost of a new entrant. The answer from other industries (agriculture, mining, real estate)?

6. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 6 Construction will be in waves of boom and bust Ref: Land Values and Real Estat Construction in Chicago traced from Hoyt (1933)

7. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 7 Lessons from Other Industries Pay attention to physical factors, such as long lead times for permitting and construction Include the behavioral factors, such as the tendency to discount the construction in progress Expect psychological factors to shape investor behavior and our discussion of boom & bust :

8. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 8 26 $ per MWH Long Lead Times Behavioral Factor

9. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 9 Price Implications of “Base Case” Simulation from Nov 2001 Price spikes reappear in 2007 Boom and Bust in Power Systems

10. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 10 Expansion of WSU’s Work in Several Areas Long term investment dynamics System security Existing models do not show impact of transmission systems System security in operations Transmission planning processes Market models and investment behavior Bidding behavior Impact of congestion on bidding behavior More sophisticated market rules New generation technologies (e.g., dispersed generation units) Environmental impacts

11. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 11 Research Plan Development of models to provide improved inputs to the system dynamics simulation Transmission systems –Simplified network models appropriate for studying longer term trends with the inclusion of all important effects (regional bottlenecks, etc.). More detailed than simple reserves. –Transmission planning processes under various economic structures. Markets –Consider impact of market rules and supplier gaming Environmental Impact –Role of renewable targets and other related policies

12. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 12 Collaboration in Research Cooperation with West African Researchers –Development of models appropriate for West African Power Pool –Study impact of weakly meshed transmission systems –Modifications for behavioral, regulatory and environmental differences Emphasis on Matlab models rather than Vensim

13. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 13 System Dynamics Originated by applying the concepts of feedback theory to the study of industrial systems Models are one of many tools to help in the study of chaos and complexity Models are constructed to help understand why patterns (growth, decay, and oscillations) occur Designed for general understanding, not point prediction –Emphasizes high level intuitive construction of models. –No explicit representation of dynamic equations. –Awkward implementation of numerical algorithms (e.g., market clearing processes)

14. 14 System Dynamics Modeling Issues for Generation Investment Investors expected prices several years ahead Time lags in construction of facilities Investor behavior (bounded rationality) External economic factors and other unknowns Reserve margin base decision More information at WSU Website: http://www.wsu.edu/~forda click research on boom and bust in the competitive electric industry http://www.wsu.edu/~forda

15. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 15 Software Issues and Model Development System dynamics –Emphasizes high level intuitive construction of models. –No explicit representation of dynamic equations. –Awkward implementation of numerical algorithms (e.g., market clearing processes) –Software tools (Stella, Vensim) Powerful tools for scenario studies Fast methods to build models Not open to sophisticated numerical calculations Engineering –Emphasizes physical and precision of models at potentially the expense of higher level insights. –Explicit representation of dynamics. –Sophisticated computational methods. –Variety of analytical methods –Software tools (Matlab) Extensive libraries of computational tools Model building labor intensive calculations.

16. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 16 System Dynamics - For Engineering Simulink –Is an interactive tool for modeling, simulating, and analyzing dynamic systems. Extensive libraries of computational tools Model building labor intensive –Is an extension to MATLAB which uses an icon-driven interface for the construction of a block diagram representation of a process. –The tool choice for control system design, signal processing, communication, and other simulation applications –Explicit representation of dynamics. –Sophisticated computational methods. –Variety of analytical methods –The block diagram represent the actual math (Different blocks for different math expressions) –Emphasizes physical and precision of models at potentially the expense of higher level insights.

17. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 17 Simulink Model for Construction of New Combined Cycle Plants

18. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 18 Overall Study Approach Follow some suggested steps of modeling –Get acquainted with the system –Be specific about the dynamic problem –Draw the causal loop diagram –Run the model to get the reference model –Conduct sensitivity analysis –Test the impact of policies Scenario analysis – various assumptions –Price forecasts –Economic growth –Weather variables Investor behavior variations –Reserve margins Verification from historical data

19. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 19 Benchmark Systems - WECC Five regions –North West Power Pool –Rocky Mountain Power Area –Arizona - New Mexico - Southern Nevada Power –Northern California –Southern California. Resources, load growth, and so on, vary by area No transmission constraints within regions Network parameters derived from DC network load flow model

20. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 20 Benchmark Systems – WAPP (cont) 14 Countries of West Africa – proposed West African Power Pool

21. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 21 Simulink Model for WAPP (RM base investment)

22. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 22 Simulink Model for WAPP (Price based investment)

23. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 23 Simulink Model S function: Price and generation computation Cost Function - linear marginal cost function (incremental cost) : - Average full costs for will be an integral over the marginal cost function:

24. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 24 S function: (cont) The total cost is given by Matlab formulation of quadratic function, as expected by the “quadprog” function The linear terms (vector b) can also be expressed as:

25. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 25 S function: (cont) Network Constraints : - DC load flow which relates injected nodal real powers, voltage phase angles and real power flows in network elements (branches). assumes that voltage magnitudes are all equal to 1 p.u. assumes that the network is lossless (branch is represented only by its equivalent reactance ) - The first set of equations relates injected nodal real powers and nodal voltage phase angles - The B' matrix is derived from the bus-admittance (inverse of bus- impedance) quadratic, symmetric, for a network with n nodes has dimension [n-1 x n-1]. b ii – sum of all inversed reactances of the branches connected to node i b ij – negative sum of all inversed reactances of the branches connected between nodes i and j;

26. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 26 S function: (cont) Network Constraints (cont) - The second set of equations relates real power flows in network branches Pflow and nodal voltage phase angles - To solve for power flows first find phase angles: - The power flow equations can be written as: - The inequality constraints imposed by the network elements’ capacities are:

27. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 27 Simulation Results (price, generation)

28. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 28 Simulation Results (construction on display) Construction (30 month simulation

29. Third US-Africa Research and Education Collaboration Workshop Abuja, Nigeria, December 13-15, 2004 29 Conclusions and Future work Engineering model: Detailed studies – Computationally intense –Power flow model for transmission constraints –Full market model with possibility of strategic bidding for energy and reserves –Use of analytical models for investor behavior that lose some of their intuitive feel –Investigation of stability analysis methods for developed models (initially using linearization As pointed out the model is for learning, and improved understanding of the interaction between technical, social, economical, and environmental factors in power plant investment So far the reference mode (boom and bust cycle) of construction is not attained Different test scenarios are going to be conducted Validation of the model using historical data is expected