Optimal scheduling and dispatch for hydroelectric generation

The optimal operation of a power system has been investigated since early days of power systems. Special attention has been given to the optimal generation schedule, because significant savings can be achieved in this area. As predominantly hydro systems are not common, treatment of hydro in many cases has been connected with thermal operation and thermal fuel cost. Today with the open electricity market becoming reality in many countries, and decentralisation of the power industry representing the main trend, an independent hydro generator will become a reality and the necessity for optimisation of the predominantly or solely hydro system will increase. The major factors which affect optimal operation of the hydro system are: - Operation at maximum efficient point - Target level achievement(connected with mid and long term optimal operation) - Inflow (and load) uncertainty - Operation at the best head - Start up cost The new algorithm has been developed to take into account all those factors and produce optimal operation for a predominantly hydro system. The new algorithm presents real time hydro scheduling which is performed through regular rescheduling and look ahead dynamic economic dispatch. The full model is implemented including head variation and start-up costs. Mixed Integer Linear Programming (MILP) is chosen as the solution algorithm, because the linear programming part models the hydro network very effectively and the integer variables can be used to control the unit start-up and shut-down behaviour. The new techniques are developed to accommodate implementation of the MILP algorithm, such as power balance constraint relaxation, specific search techniques for integer solution and more detailed connection with mid-term optimisation. The algorithm is implemented on the Tasmanian Hydro Electric Commission's hydro system. It is tested off-line using historical operating plans. A conservative estimate is that the savings will be up to six hours daily of an operator's time plus 0.5% in annual stored energy savings. There is the possibility for savings in the mid term optimisation by decreasing the risk of spill through better control of short term storage levels