PROJECT TITLE :

Stochastic Modeling for the Next Day Domestic Demand Response Applications

ABSTRACT:

Demand response (DR) refers back to the shoppers' activities for changing the load profile with the purpose of lowering value, improving power quality or reliability of power system. Enhancement in participation of the DR is well known as a profit-creating pattern in distribution systems for both residential units (to increase their edges) and distribution firms (DISCO) (to cut back their peak demand and costs). The target of this research is concentrated on proposing a brand new strategy for optimal scheduling of versatile masses for the next day. Then, the day ahead pricing (DAP) is modeled using the inclining block rates (IBR), assumed for retail electricity markets, to research the efficiency of the proposed strategy. At the same time, the appliances stochastic time of use (ASTOU) are taken into consideration in residential units for non-controllable half of the load during every day stochastically. Among five various copulas, the Gaussian copula (GC) function shows the most effective performance in modeling and estimation of non-controllable load consumption. Finally, simulations, performed with the GAMS, illustrate the effectiveness of the instructed approach that is formulated as a stochastic nonlinear programming (NLP) modeled by the GC. Notice that copulas use samples of real data gathered from residential units.


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