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The smart grid initiative is the impetus behind changes that are expected to culminate into an enhanced distribution system with the communication and control infrastructure to support advanced distribution system applications and resources such as distributed generation, energy storage systems, and price responsive loads. This research proposes a distribution-class analog

The smart grid initiative is the impetus behind changes that are expected to culminate into an enhanced distribution system with the communication and control infrastructure to support advanced distribution system applications and resources such as distributed generation, energy storage systems, and price responsive loads. This research proposes a distribution-class analog of the transmission LMP (DLMP) as an enabler of the advanced applications of the enhanced distribution system. The DLMP is envisioned as a control signal that can incentivize distribution system resources to behave optimally in a manner that benefits economic efficiency and system reliability and that can optimally couple the transmission and the distribution systems. The DLMP is calculated from a two-stage optimization problem; a transmission system OPF and a distribution system OPF. An iterative framework that ensures accurate representation of the distribution system's price sensitive resources for the transmission system problem and vice versa is developed and its convergence problem is discussed. As part of the DLMP calculation framework, a DCOPF formulation that endogenously captures the effect of real power losses is discussed. The formulation uses piecewise linear functions to approximate losses. This thesis explores, with theoretical proofs, the breakdown of the loss approximation technique when non-positive DLMPs/LMPs occur and discusses a mixed integer linear programming formulation that corrects the breakdown. The DLMP is numerically illustrated in traditional and enhanced distribution systems and its superiority to contemporary pricing mechanisms is demonstrated using price responsive loads. Results show that the impact of the inaccuracy of contemporary pricing schemes becomes significant as flexible resources increase. At high elasticity, aggregate load consumption deviated from the optimal consumption by up to about 45 percent when using a flat or time-of-use rate. Individual load consumption deviated by up to 25 percent when using a real-time price. The superiority of the DLMP is more pronounced when important distribution network conditions are not reflected by contemporary prices. The individual load consumption incentivized by the real-time price deviated by up to 90 percent from the optimal consumption in a congested distribution network. While the DLMP internalizes congestion management, the consumption incentivized by the real-time price caused overloads.
ContributorsAkinbode, Oluwaseyi Wemimo (Author) / Hedman, Kory W (Thesis advisor) / Heydt, Gerald T (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2013
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As global energy demand has dramatically increased and traditional fossil fuels will be depleted in the foreseeable future, clean and unlimited renewable energies are recognized as the future global energy challenge solution. Today, the power grid in U.S. is building more and more renewable energies like wind and solar, while

As global energy demand has dramatically increased and traditional fossil fuels will be depleted in the foreseeable future, clean and unlimited renewable energies are recognized as the future global energy challenge solution. Today, the power grid in U.S. is building more and more renewable energies like wind and solar, while the electric power system faces new challenges from rapid growing percentage of wind and solar. Unlike combustion generators, intermittency and uncertainty are the inherent features of wind and solar. These features bring a big challenge to the stability of modern electric power grid, especially for a small scale power grid with wind and solar. In order to deal with the intermittency and uncertainty of wind and solar, energy storage systems are considered as one solution to mitigate the fluctuation of wind and solar by smoothing their power outputs. For many different types of energy storage systems, this thesis studied the operation of battery energy storage systems (BESS) in power systems and analyzed the benefits of the BESS. Unlike many researchers assuming fixed utilization patterns for BESS and calculating the benefits, this thesis found the BESS utilization patterns and benefits through an investment planning model. Furthermore, a cost is given for utilizing BESS and to find the best way of operating BESS rather than set an upper bound and a lower bound for BESS energy levels. Two planning models are proposed in this thesis and preliminary conclusions are derived from simulation results. This work is organized as below: chapter 1 briefly introduces the background of this research; chapter 2 gives an overview of previous related work in this area; the main work of this thesis is put in chapter 3 and chapter 4 contains the generic BESS model and the investment planning model; the following chapter 5 includes the simulation and results analysis of this research and chapter 6 provides the conclusions from chapter 5.
ContributorsDai, Daihong (Author) / Hedman, Kory W (Thesis advisor) / Zhang, Muhong (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2014