| Grant number: | 16/04164-6 |
| Support Opportunities: | Scholarships abroad - Research Internship - Doctorate |
| Start date: | September 01, 2016 |
| End date: | August 31, 2017 |
| Field of knowledge: | Engineering - Electrical Engineering - Power Systems |
| Principal Investigator: | Luiz Carlos Pereira da Silva |
| Grantee: | Pedro Pablo Vergara Barrios |
| Supervisor: | Bo Norregaard Jorgensen |
| Host Institution: | Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil |
| Institution abroad: | University of Southern Denmark (SDU), Denmark |
| Associated to the scholarship: | 15/09136-8 - Fault tolerant portfolio optimization in Smart Grid, BP.DR |
Abstract The term Smart Grid refers to the use of communication, sensing and control technology to operate in parallel with an electric power grid for the purpose of enhancing the reliability of electric power delivery, minimizing the cost of electric energy to consumers, and facilitating the interconnection of new generating sources, specially renewable generation sources. However, the extensive growth of installed wind and solar power plants creates challenges to maintain grid balance. The reason is that the output power from the renewable energy sources such as wind and solar highly depends on weather conditions that are out of human control. Different approaches have been proposed to overcome these problems, including moving consumption to when wind and solar power generation is high, using energy storage system or developing a demand response framework. All these solutions strengthen the resilience and robustness of the grid, but also increase control complexity of the grid. Therefore, new control and planning algorithms are required to operate this new so-called Smart Grid. Considering this, the main concern of this PhD research project is to develop a distributed optimization strategy considering a dynamic unit portfolio, where some units can shut down due to faults or scheduled maintenance. Although portfolio optimization is not a new optimization problem in power systems, this research project considers a new and a future Smart Grid scenario. In this Smart Grid scenario, we consider that a large amount of power comes from renewable units, characterized by an unpredictable generation, and a large part of the energy consumption is flexible. Therefore, it is possible to shift such consumption temporarily without posing a significant discomfort in the consumer side. Furthermore, an uncertainty assessment study will be carried out, using the optimization strategy. For this, a Monte-Carlo Simulation framework will be developed, aiming to assess the impact of uncertainty in renewable generation and energy demand in the operational cost of the portfolio. (AU) | |
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