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Wind Hydro Power Optimization based on Stochastic Forecasting of Wind1By: Muhammad Sharjeel Javaid (201404920) Numan Saeed (201404640)Course Instructor: Dr. Ali Taleb Al-Awami

Electrical Engineering Department, College of Engineering Sciences and Applied Engineering. KING FAHD UNIVERSITY OF PETROLEUM & MINERALS1-First progress report summary2

31-First progress report summary

Formulation

Operation StrategyProfitsW-H10555 OW8741.8 Difference1813.2 Output Power to Grid (MATLAB)HoursPrice/Unit00:00-08:0054 /MWh08:00-22:00103.84 /MWhEnergy Price TariffProfit Comparison42-Goals for final progress reportPrimary GoalsUnderstand AIMMSDeterministic Model in AIMMSUncertain Model in AIMMSScenario Analysis (Monte Carlo Simulations)Robust OptimizationComparison

Secondary GoalsEffect of PenaltyThermal Generator Incorporation in our SystemComparison

53-Understanding aimmsAIMMS Literature ReviewAIMMS The Language ReferenceAIMMS Optimization Modeling AIMMS Function ReferenceGoogle Groups4-Deterministic Model in AIMMS (Input data)6

4-Deterministic Model in AIMMS (RESULTS)

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Output Power ContributionsEnergy Stored in Reservoir with Pump OperationOff-Peak HoursPeak HoursUncertain model analysisScenario Generation (Monte carlo simulation)Robust optimization8To be uncertain is to be uncomfortable, but to be certain is to be ridiculous Chinese proveb

5-uncertain model analysis (Input data)9All input parameters and bounds remains same, except available windFor each hour standard deviation is introduced

5-uncertain model analysis (Scenario generation results)10Also known as Monte Carlo SimulationsTotal 150 scenarios are solved in AIMMSProfitsMaximum22427.02 Minimum24323.74 Average23346.88

5-uncertain model analysis (Robust Optimization results)11Available Wind parameter was declared uncertain in AIMMSSolved the Robust Optimization by generating RO_Model in AIMMS

6-Comparison of ROBUST Optimization and scenario analysis12

Optimization TechniqueProfitsRO19530.29 Monte Carlo23346.88 Difference3816.59 Effect of Penalty functionand how to overcome the loss137-Penalty function effectLuckily, for the given wind scenario, we never ran out of energy resources.However, if at any instant, our whole system is unable to produce the required 3 MW (preset lower limit), we are penalized.To verify penalty we reduce the available wind in the beginning when we have 0 MWh stored in reservoir. 147-Penalty function effectWind Scenario is changed by changing available wind to 1 MW for first 3 hours, as shown

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ProfitsRevenue22309.99 Penalty7920 Net Profit14389.99 8-How to overcome the loss16

8-How to overcome the lossNow after adding Generator total supplied power remained within the limits (i.e. 3