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Modelling Developments at Power Systems Research

Modelling Developments at Power Systems Research. Tom Halliburton EPOC Meeting 9 th July 2014. PSR – Power Systems Research Inc. Offices in Rio de Janeiro Founded in late 1980s by Mario Pereira Now has 47 staff Work split equally between consulting and software sales

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Modelling Developments at Power Systems Research

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  1. Modelling Developments at Power Systems Research Tom Halliburton EPOC Meeting 9th July 2014

  2. PSR – Power Systems Research Inc • Offices in Rio de Janeiro • Founded in late 1980s by Mario Pereira • Now has 47 staff • Work split equally between consulting and software sales • And equally between local and overseas customers • Customers world wide – most countries with significant hydro generation

  3. SDDP – mid term planning OptGen – Investment planning NCP – short term scheduling

  4. SDDP – faster solves • Parallel processing • Base SDDP licencing allows parallel processing on one PC • Base Xpress solver allows two simultaneous processes on each licence • Enhanced version of SDDP for parallel processing across multiple networked PCs • Two parallel processes reduces CPU by approx 60% • Faster solves with Cut Relaxation • Each iteration, size of LP problem increases, e.g. 18% from 1st to 2nditeration. • Eliminate redundant future cost function cuts from the one stage LP problems automatically, rather than allowing user to select based on a rule

  5. Fuel Supplies • Fuel supply contracts • Take or pay contracts, • General limits of rates and quantities of fuel supplies • Fuel storage • Coal stockpiling, gas storage • Multiple fuel contracts, supplying multiple stations • Take or pay, fuel storage add dimensions to future cost function

  6. SDDP chronological • Chronological modelling within each week • Hourly • Trial version completed • Flow delays down rivers • Hydro plant head pond constraints • Thermal plant ramp rates • Random variations in wind generation • Time of day effects for solar power • Requires massive parallel computing • Conceptually all the one stage optimisations can be carried out simultaneously (e.g. 50 per stage, 360 stages)

  7. Current Issues • Modelling of risk averse management of hydro reservoirs • Apply a more risk averse approach based on a willingness to give up some expected returns to reduce probability of deficit • Approximating head effects at hydro stations without creating non-convex future cost function • Possibly take or pay contracts for hydros

  8. Cloud Computing on Amazon Servers • All three models available on Amazon • PSR the first South American customer for Amazon, over 2 years ago • Costs US$0.50 per processor, per hour • Covers Amazon charges and Xpress LP solver licencing fees • Processor cost has come down as most customers want storage, not CPU power • Opens up new opportunities for parallel processing • OptGen 20 year case, 80 iterations, 5.5 hours elapsed, using 16 processors • SDDP Chronological

  9. OptGen – Optimal Generation System Expansion Planning • Includes all the usual constraints for expansion planning • Find the optimal expansion plan using a MIP solver, minimising investment + operational cost • Investment costs known for each plant • System operation costs must be calculated for each node in the MIP problem • Repeated calculation of operational cost for different expansion plans result in an improving representation of the system operating cost function • Cost function has a similar form to the future cost function calculated by SDDP.

  10. OptGen Algorithm Objective: Minimise C(x) + W(x) where C(x) investment cost W(x) operating cost X(t,j) is a matrix representing new generation commissioning program

  11. OptGen with SDDP • Simple mode - OptGen calculates operational cost for a number of scenarios • Alternatively, use SDDP: • OptGen calculates an optimal expansion plan • SDDP calculates the system operating costs • OptGen re-calculates the expansion plan using this new information • Allows plant operating capabilities and constraints to directly influence expansion planning. • End result is a least cost expansion plan and an SDDP model setup for this plan.

  12. OptGen + SDDP • Distinguishes between run of river hydros and those with storage. • Waitaki North Bank will benefit from storage management, Arnold scheme will not. • Full effects of variability of hydro inflows reflected in planning • Accounts for extra plant that might be needed to cover dry periods • Thermal unit commitment options • Base load or peaking capabilities • Coal stockpiling, gas storage • Take or pay fuel contracts associated with new plant • Variability of wind, solar can be modelled in more detail

  13. OptGen Trials • Trial study of New Zealand system • 20 year study • 80 iterations, 5.5 hours elapsed with 16 processors • Results look reasonable

  14. NCP • Detailed scheduling model hourly, ½ hourly or 15 minute time steps • Used for detailed day ahead planning etc. where ramp rates, start up costs, interaction of hydro plants in a river system need to be modelled • Used in centrally planned and dispatched systems • A model of this type is likely to be needed if the “NZ Power” single buyer scheme were to eventuate.

  15. NCP Chronological • Latest extension enables SDDP model results to be studied in more detail • Solve a full year with NCP, working from an SDDP solution to give a detailed picture of one or more flow scenarios • Options to enforce SDDP’s mid-term strategies: • Use water value for end of period storage • End of period reservoir levels as a target • Total generation each period for each hydro plant

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