A Mixed Integer Linear Programming Model for Factory Load Scheduling in Tim-of-Use Schemes

Abstract

In this paper, we propose a model for load scheduling of industrial loads under time-of-use pricing schemes using linear programming. While industrial loads consume more electrical energy than residential or commercial loads, their characteristics and correlations are not as simple, leading to complex conditions that need to be considered compared to other types of loads. On the other hand, linear programming is a validated optimization method that guarantees global optimal solutions. However, applying it to load scheduling requires expressing all constraints of industrial loads as linear equations, which presents a challenge. In the proposed model, loads are categorized into fixed loads and demand response loads, allowing for the differentiation of interruptible loads among shiftable loads to account for load diversity. Control variables are set to enable the modeling of these loads, considering the potential sequential conditions and duplicate prohibition conditions among shiftable loads. By representing these conditions as linear equations of control variables, they can be incorporated into load scheduling using linear programming. Additionally, the model considers potential scenarios that may exist at the consumer site, such as the presence of solar power generation facilities or energy storage systems, the ability to sell excess power, and limitations on the available workforce for simultaneous operations. These factors are taken into account to provide a comprehensive reflection of possible situations. In this paper, the proposed model is implemented in MATLAB and applied to a sample problem consisting of 8 flexible loads and 2 interruptible loads. A case study is conducted, considering various situations, and the results are analyzed to confirm the effectiveness of the proposed model.