1. 1 Seema Thakur (st107641) Advisor: Dr. Weerakorn Ongsakul Optimal Generation Scheduling of Cascaded Hydro-thermal and Wind Power Generation By Particle Swarm Optimization Master’s Thesis Energy

2. 2  Introduction  Contribution to Research  Benefits of the Proposed Innovative Approach  Methodology  Problem Formulation  Results & Discussion  Conclusion  Recommendation Outlines

3. 3 Introduction  Bulk amount of electrical energy cannot be stored. So, in real time, the generation from different power plants should match with the power demand.  Electricity generating companies and power systems have the problem of deciding how best to meet the varying demand for electricity, which has a daily and/or weekly cycle.  Generation scheduling is the process of allocating the required load demand between the available generation units such that the cost of operation is minimized, while honoring the operational constraints of the available generation resources. There have been many algorithms proposed for the scheduling.  A typical system is composed of hydro and thermal generating units. The generation scheduling done for such a system is called hydrothermal scheduling.  It helps to minimize the total fuel cost and also for the optimal utilization of the available natural renewable resources.  Considering the aspect of near future, integrating wind energy in an existing hydrothermal system seems to be an attractive option.

4. 4 Contribution to Research  Generation scheduling is a challenging task due to its complex mathematical behavior. Thus, various optimization techniques have been used in the past but they have various drawbacks.  So far the research has been done for generation scheduling of hydro-thermal system or wind-thermal system. But no works has been done for a system having all the three generations.  In this research work, an innovative approach called Particle Swarm Optimization (PSO) is introduced for the generation scheduling of different systems incorporating all three different types of generation to optimize the generation cost.  In addition, the effectiveness of different versions of PSO is evaluated in this work.  The proposed simulation model has been tested in test systems as well as in the real power system of Nepal.

5. 5  Cost reduction  Maximization of renewable energy use (hydro and wind)  Reduction of thermal generation : Reduction of GHG emission. (Without any extra monitory investment ) Benefits of the Proposed Innovative Approach

6. 6 Methodology  The approach is inspired by the social behavior of animals such as fish schooling and bird flocking.  A set of unknown variables are randomly initialized in a feasible region and the best solution is selected.  The solution tries to converge depending upon its distance from the best solution.  In each iteration within the runtime of the program, the solution converses and gives the best solution. PSO Figure 1: Fish schooling and Bird flocking

7. 7 Problem Formulation Fig: Schematic diagram of a typical power system The objective is to minimize the total operating cost Minimize, Subjected to various physical limitations,

8. 8 Problem Formulation II. Constraints a.Power Balance Constraints b.Hydro power generation limits c.Hydro plant water discharge limits d.Reservoir water storage limits e.Initial and final reservoir water storage volume f.Hydro power generation constraints g.Hydraulic continuity constraints h.Thermal power generation limits i.Ramp response rate limit on thermal generation units j.Spinning reserve limits k.Power output limits on wind energy system

9. 9 Results & Discussion

10. 10 Generation level of plants with time interval Test 1: A Simple System with a Hydro and a Thermal Generating Unit

11. 11 Test 2: A system with Four Cascaded Hydro and Three Thermal Generating Units

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13. 13 Convergence characteristics of the proposed approached of all PSO schemes without considering wind generation in the system. Convergence characteristics of the proposed approached of all PSO schemes considering wind generation in the system.

14. 14 Optimal generation scheduling by SPSO-TVAC for each time interval

15. 15 Generation Scheduling for Nepali Power System

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17. 17 Hydrothermal generation (MW) schedule by SPSO-TVAC without considering wind generation in the Nepali system

18. 18 Figure: Hydrothermal generation (MW) schedule by SPSO-TVAC with the consideration of wind generation in the Nepali system

19. 19 Conclusion  This research work helps to reduce the GHG emission by reducing the thermal generation in the system. (Social benefit)  Helps to optimize the generation cost.(Economical benefit)  Maximizes the utilization of renewable resources. (Environmental benefit)  The comparison with the results from the already existing techniques clearly demonstrates that the proposed method gives the best result.  The simulation results for both test model and real system model (Nepali system) illustrate that the proposed SPSO_TVAC is the most efficient approach to find the optimal solution for generation scheduling of hydrothermal system with/without penetration of wind power to the system, considering all the associated constraints.  In this proposed concept, there is no physical system modification necessary in the existing system Results, no additional constructional cost.

20. 20 Thank You Q & A