Contingency Constrained Unit Commitment with Demand Response programs

Author(s):  
Jamshid Aghaei ◽  
Kashem M. Muttaqi ◽  
Mohammad-Iman Alizadeh
2021 ◽  
Author(s):  
Caio Costa de Barros Pimentel Luke ◽  
Danielle de Freitas ◽  
Felipe Atenas Maldonado ◽  
Luigi Viola ◽  
Tiago Lino Bello ◽  
...  

Demand response is currently being tested by the Brazilian independent system operator, ONS, and by the trading chamber, CCEE. The program considers the reduction of consumption of some registered clients, as an alternative to dispatching thermal power plants according to merit order. The DESSEM computational tool, developed by CEPEL, is currently run by the ONS to define the next-day dispatch for the whole country. The results obtained using an academic version of DESSEM are used to benchmark and compare DESSEM's performance to relocate the load of demand offered by the operator to different clients under different configurations of the power system. Pros and cons are analyzed for different mathematical formulations, particularly regarding their impact on prices, operating costs, and computational times. Special attention is paid to determining the robustness of the considered models for a variety of optimality requirements for solving the unit-commitment problem.


Author(s):  
Hassan Jalili ◽  
Pierluigi Siano

Abstract Demand response programs are useful options in reducing electricity price, congestion relief, load shifting, peak clipping, valley filling and resource adequacy from the system operator’s viewpoint. For this purpose, many models of these programs have been developed. However, the availability of these resources has not been properly modeled in demand response models making them not practical for long-term studies such as in the resource adequacy problem where considering the providers’ responding uncertainties is necessary for long-term studies. In this paper, a model considering providers’ unavailability for unforced demand response programs has been developed. Temperature changes, equipment failures, simultaneous implementation of demand side management resources, popular TV programs and family visits are the main reasons that may affect the availability of the demand response providers to fulfill their commitments. The effectiveness of the proposed model has been demonstrated by numerical simulation.


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