Investigating the Effect of Load Uncertainty on Prioritizing Demand Response Programs

In smart grids paradigm, versatile demand response programs have been devised to accommodate the load flexibilities in optimal scheduling of distribution networks and increasing the techno-economic efficiency of electrification process. The initial models for prioritizing the demand response programs are mainly valid for the case of constant and deterministic load profiles. These models are tackled based on multi-criteria decision making approaches and make use of load’s economic model. This is while, the load demand of end-side consumers are accompanied with uncertainties in their nature. An improper modeling of these uncertainties or excluding of from the developed analytics methods ends in corrupted and unreliable results. To ameliorate the precision of the proposed approach, this study effectively incorporates the load demand uncertainties in prioritizing the demand response programs. The load demand uncertainties are effectively modeled based on normal probability distribution function and represented in the form of adequate number of scenarios. The obtained results are then evaluated based on technique for order preference by similarity to ideal solution (TOPSIS) known as a multi-criteria decision making approach. By this way, the priority of each demand response program is determined. Results demonstrate substantial changes in final ranking of the investigated programs compared to the deterministic load profile in preliminary approaches. This remark approves the significant importance of deploying accurate load demand profiles within prioritizing demand response programs.