UNIT COMMITMENT : To commit a generating unit is to turn it on ,i.e., to bring the unit upto speed, synchronize it to the system,and connect it so it can deliver power to the network. The problem with commit enough units and leave them online is one of the economics. Its quite expensive to run too many generating units.A great deal of money can be saved by decommitting them when not needed.

UNIT COMMITMENT SOLUTION METHODS : The most talked about techniques fpr the solution of unit-commitment problem are : Priority-list schemes Dynamic Programming (DP) Lagrange relation(LR)

PRIORITY LIST METHOD : Priority-List Methods consist of a simple shut-down rule obtained by an exhaustive enumeration of all unit combinations at each load level or obtained by noting the full-load average production cost of each unit . The full-load average production cost is the net heat rate at full load multiplied by the fuel cost . Typical shut-down rules at each hour when load is dropping, determine whether dropping the next unit on the list leaves sufficient generation to supply the load plus the spinning-reserve requirements if the supply is not sufficient, keep the unit committed determine the number of hours before the unit is needed again if the time is less than the minimum shut-down time for the unit, keep it committed perform a cost comparison the sum of the hourly production costs for the next number of hours with the next unit to be dropped being committed and the sum of the restart costs for the next unit based on the minimum cost of cooling the unit or banking the unit

Advantages: are flexible and allow for the consideration of practical operating constraints feasible solutions if there are any are usually obtained computational requirements in terms of memory and running time are modest.

Disadvantages : This method cannot guarantee the optimal solutions or even furnish an estimate of the magnitude of their sub-optimality. DYNAMIC PROGRAMMING METHODS : The following assumptions are made in this implementation of the DP approach a state consists of an array of units with specified units operating and the rest decommitted (off-line). A feasible state is one in which the committed units can supply the required load and meets the minimum capacity for each period start-up costs are independent of the off-line or down-time i.e., it is a fixed amount w.r.t. time no unit shutting-down costs a strict priority order will be used within each interval a specified minimum amount of capacity must be operating within each interval There are two methods of DP. They are 1. Forward dynamic programming 2. Reverse dynamic programming

The forward DP approach : The forward DP approach runs forward in time from the initial hour to the final hour Recursive algorithm to compute the minimum cost in Kth hour with Ith Combination is, F cost (J,K) = min[ P Where, F cost (J,K) = Least total cost to arrive at state (J, K) ; Pcost cost

(J,K) + Scost (J-1,L; J,K) + Fcost(J-1, L) ]

(J,K) = Production cost for state (J, K) ;

Scost (J-1,L; J,K)= Transition cost from state (J-1,L) to State (J, K) ; Fcost = Kth Combination in Jth hour

Disadvantages : The dynamic -programming method of solution of the unit commitment problem has many disadvantages for large power systems with many generating units . This is because of the necessity of forcing the dynamic-programming solution to search over a small number of commitment states to reduce the number of combinations that must be tested in each time period . Lagrange Relaxation solution : In Lagrangian relaxation approaches, unit commitment problem is formulated in terms of 1) a cost function, that is the sum of terms each involving a single unit, 2) a set of constraints involving a single unit, and 3) a set of coupling constraints (the generation and reserve requirements), one for each hour in the study period, involving all units. Economic Dispatch Formulation The primary concern of an ED problem is the minimization of its objective function. The total cost generated that meets the demand and satisfies all other constraints associated is selected as the objective function. In general, the ED problem can be formulated mathematically as a constrained optimization problem with an objective function of the form: FT = Fi (Pi) where FT is the total generation cost; N is the total number of generating units; Fiis the power generation cost function of the i th unit.