A model for demand side management using locational salary data
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Congestion in electrical transmission lines causes the use of higher cost generators and creates a surge in the Locational Marginal Prices (LMP). A cost-effective way to relieve the impact of congestion is to control demand for electricity. This project proposes a demand-side management model derived from readily available locational salary data on the internet. The income statistics are converted into willingness-to-pay curves. This willingness to pay curve is divided into blocks of power that are bid at different prices based on the curve. These bids and offers are converted into generator and cost inputs to the DC Optimal Power Flow (OPF) problem.Due to high demand in certain areas over others, some lines might be congested. This congestion pattern can be modified by manipulating the loads. A comparison is shown between solutions of the OPF problem with and without demand-side management. The proposed model is tested on IEEE 3-bus and 30-bus systems. Contour plots are reported to visually illustrate the change in system cost as a function of change in loads. The loads that present the highest decrease in system cost is picked as adjustable loads for future use.