A procedure for distribution system planning of a large-scale agricultural project

Abstract

Different mathematical techniques adapting linear, nonlinear, mixed-integer, and network flow programming have been developed over the past decades to solve the distribution planning optimization problem. The high dimensionality of the problem made it in some of practical cases unmanageable by such classical optimization techniques. This gave rise to the application of knowledge based, heuristics, artificial intelligence, and approximate iterative techniques to search for the optimal solution. The problem also was typically perceived from the distribution companies' perspectives with the objective being to supply sustainable yet cost effective power to multi-objective multi-interest consumers with different damage functions and relatively uncertain data. This paper presents a value-based distribution system planning procedure for large-scale agricultural real life project. This type of distribution planning is characterized not only by high load demand but also with a huge distribution network covering the vast agricultural area. Yet it is a planning for single type of customers who has a consistent developing policy, interest, cost damage function, together with a realistic and less uncertain data. The planning is also perceived from the consumer perspective who may even question the connection to the power utility unless it is proved as cost effective way of power supply. Macro and micro-levels planning is suggested for both overall project and farm modules, respectively. The proposed planning procedure evaluates different feasible alternatives based on life cycle cost while reliability indices and cost of interruption are taken into consideration. The procedure is illustrated on the micro-level for a real life agricultural problem