Resource Allocation Using Branch and Bound

Abstract

The chapter describes a resource-allocation problem in a smart-grid application that is formulated and solved as a binary integer-programming model. To handle power outages from the main distribution circuit, the Smart grid’s intelligent agents have to utilize and negotiate with distributed-energy resource agents that act on behalf of the grid’s local generators in order to negotiate power-supply purchases to satisfy shortages. We develop a model that can optimally assign these DERs to the available multiple regional utility areas (RUAs) or units that are experiencing power shortages. This type of allocation is a resource-assignment problem. The DERs in our model depict the behavior of power created with a wind turbine, solar generation, or other renewable generation units, and the region or area refers to a centralized distribution unit. The integer-programming approach is called Capacity-Based Iterative Binary Integer Linear Programming (C-IBILP). All simulation results are computed using the optimization tool box in MATLAB. Computation results exhibit very good performance for the problem instances tested and validate the assumptions made.

The material in this chapter was co-authored by Prakash Ranganathan and Kendall E. Nygard. Prakash Ranganathan had primary responsibility for developing the linear-programming formulation of a resource-allocation problem using the branch-and-bound method. Prakash Ranganathan was the primary developer for modeling, implementing, and testing the conclusions that are advanced here. Prakash Ranganathan also drafted and revised all versions of this chapter. Kendall E. Nygard served as a proofreader and checked the LP formulation that was run by Prakash Ranganathan.