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Influence of demand response on electric power distribution systems optimization problems

Grant number: 18/25872-4
Support Opportunities:Scholarships abroad - Research
Effective date (Start): February 01, 2019
Effective date (End): June 30, 2019
Field of knowledge:Engineering - Electrical Engineering - Power Systems
Principal Investigator:Marina Lavorato de Oliveira
Grantee:Marina Lavorato de Oliveira
Host Investigator: Bala Venkatesh
Host Institution: Centro de Ciências Exatas, Ambientais e de Tecnologias. Pontifícia Universidade Católica de Campinas (PUC-CAMP). Campinas , SP, Brazil
Research place: Ryerson University, Canada  
Associated research grant:15/21972-6 - Optimization of the operation and planning in transmission and distribution systems, AP.TEM


In the last years, with the advancement of new technologies, electrical energy distribution systems have undergone major changes. These new technologies make it possible to use renewable and alternative energies. At the global level issues involving the preservation of the environment and the reduction of the emission of carbon dioxide in the Earth's atmosphere have been widely discussed and in some countries targets have already been established for these issues to be put into practice. Thus, new technologies that aid in environmental preservation are being widely used around the world and in Brazil, such as the installation of residential photovoltaic panels in addition to photovoltaic plants, wind power generation, electric vehicles and energy storage devices. In this context, new planning and operation mathematical models have been used to optimize investments in system expansion, distributed generation, and volt/VAR control of electrical energy distribution systems. However, these models have not been fully adapted to address price-dependent resources as a response to demand, which can be broadly defined as the adjustment of consumer energy consumption in response to some financial gain offered by the energy distribution company. The importance of considering the demand response in optimization models is that it is based on the collective response of a large number of participants, which has a considerable impact on the variable demand curve over time. The role of demand response has recently attracted increasing interest in world-class energy systems. In this context, an assessment of the influence of demand response on the optimization problems of electrical energy distribution systems becomes necessary since the future of the electric energy market is moving in this direction. Thus, the objective of this project is to emphasize the importance of integrating the response on demand to the models of planning and operation of electricity distribution systems considering the variable prices in time in the investment models. (AU)

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