Mathematical model capacity constraints

The optimisation procedure presented in this chapter entails two stages as summarized in Fig. 5.3. In the first stage, a mathematical model for minimisation of freshwater requirement is solved based on maximum potential reusable water storage, gf. For clarity, this model will be referred to as model Ml in this chapter. In the second stage, the minimum freshwater requirement obtained from model Ml is used as an input parameter in another mathematical model for which the objective function is the minimisation of reusable water storage. This model will be referred to as model M2 in this chapter. Since different amounts of reusable water will be stored at various intervals within the time horizon of interest, the minimum reusable water storage capacity will correspond to the maximum amount of reusable water stored at any point within the time horizon of interest as obtained from model M2 (Constraints (5.40)). 

The combined methods Various variants 1. Process mathematical models with distributed inputs 2. Capacity to be associated with a Kalman filter 3. Without inequality type constraints The maximum likelihood method... 

The mathematical models incorporate mass balance equations, capacity constraints, the cost functions, and the special constraints mentioned in the previous section. The mass balance equations, the capacity constraints, and the variable cost functions, are all linear and need not be explained here. How the special constraints are formulated is explained below. 

Sanghvi, A.P. Shavel, I.H. (1984). Incorporating explicit loss-of-load probability constraints in mathematical programming models for power system capacity planning. International Journal of Electrical Power Energy Systems, 6(4) 239-247. 

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