Dextromethorphan In the heuristics methodology of Kulkarni
In the heuristics methodology of Kulkarni and Mittal , the given square layout is divided into a fine grid and the points where the grid lines cross each other can be considered as possible turbine locations. Subsequently, turbines are placed in these possible locations one by one starting with the point where the gross AEP is maximum. The subsequent turbines are placed at locations where AEP will be the best and none of the constraints such as ITD, OCF will most likely be violated. The algorithm is implemented as follows. In the first step, a point is selected based on the gross AEP and added to the accepted turbine location matrix (M). In the next step, other locations surrounding the accepted location and violating other constraints are discarded and are added up to the rejected turbine location matrix (V). The left over locations are next updated as available locations. Now, the next turbine can again be added at the location that shows highest gross AEP value in the map and no constraint violation among all available locations. This way of adding turbines is continued till the search on all possible candidate locations is exhausted. Fig. 3 shows the schematic view of this Dextromethorphan methodology. It can be seen that the matrices M and V are updated at each iteration. In this fashion, the total number of turbines and their respective locations can be found out in one shot. As explained earlier, the above mentioned heuristic approach of determining the optimal number as well as location of turbines in a farm layout has a drawback of lack of continuity i.e. the turbines can only have certain available locations for the optimal placement. This is because the heuristic algorithm discretizes the given geographical boundary into finite number of grid-points, and the grid-cross sites act as the only possible locations for candidate turbines. Therefore, the turbines can be placed only in those available locations leaving the scope of any other nearby points to be one of the optimal points. Also, the heuristic methodology lacks the stability, since outcomes can be different depending on the selection of the starting point. Due to lack of stability, tropic hormone might be difficult for wind farm developers to decide on which starting point to start the search process of locating the turbines using the heuristic approach and this shows that the practical application of this approach could be limited. However, the results generated by the heuristic approach can be used as an intelligent initial guess to other methodologies.