The optimal operation of wind turbine, ces, and conventional generation units, considering the stochastic models for price, demand, and wind speed, was formulated as a. This study includes recommendations that the fleet needs to have a flexible component, load shifting, and storage technology to mitigate potential overgeneration. In addition to demand response, the project team analyzed to what extent more flexible operations and battery energy storage might increase the economic carrying capacity.
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β’ the dr models go from curtailment and ideal shifting to shifting with saturation. In this context, the flexible operation of cryogenic air separation units (asus) has attracted interest due to their high energy consumption. The representation of load shifting in a power system model is more complex than that of, for example, contingency due to the necessity of balancing any response from the flexible load.
Highlights β’ we present a collection of linear formulations for demand response (dr) models.
Some asu plants allow storing energy. An energy storage dispatch optimization model was developed to simulate peak clipping and load shifting control strategies of the energy storage system to maximize cost savings for industrial. We demonstrate the value of the proposed scheduling framework by comparing the demand response operation of the industrial asu against a constant operation base case,. Demand response and energy storage are sources of power system flexibility that increase the alignment between renewable energy generation and demand.
