Matching Items (7)
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- All Subjects: Energy Storage
- Creators: Ayyanar, Raja
- Status: Published
Description
Battery energy storage has shown a lot of potential in the recent past to be effective in various grid services due to its near instantaneous ramp rates and modularity. This thesis aims to determine the commercial viability of customer premises and substation sited battery energy storage systems. Five different types of services have been analyzed considering current market pricing of Lithium-ion batteries and power conditioning equipment. Energy Storage Valuation Tool 3.0 (Beta) has been used to exclusively determine the value of energy storage in the services analyzed. The results indicate that on the residential level, Lithium-ion battery energy storage may not be a cost beneficial option for retail tariff management or demand charge management as only 20-30% of the initial investment is recovered at the end of 15 year plant life. SRP's two retail Time-of-Use price plans E-21 and E-26 were analyzed in respect of their ability to increase returns from storage compared to those with flat pricing. It was observed that without a coupled PV component, E-21 was more suitable for customer premises energy storage, however, its revenue stream reduces with addition to PV. On the grid scale, however, with carefully chosen service hierarchy such as distribution investment deferral, spinning or balancing reserve support, the initial investment can be recovered to an extent of about 50-70%. The study done here is specific to Salt River Project inputs and data. Results for all the services analyzed are highly location specific and are only indicative of the overall viability and returns from them.
ContributorsNadkarni, Aditya (Author) / Karady, George G. (Thesis advisor) / Ayyanar, Raja (Committee member) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2013
Description
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
Description
An increase in the number of inverter-interfaced photovoltaic (PV) generators on existing distribution feeders affects the design, operation, and control of the distri- bution systems. Existing distribution system analysis tools are capable of supporting only snapshot and quasi-static analyses. Capturing the dynamic effects of the PV generators during the variation in the distribution system states is necessary when studying the effects of controller bandwidths, multiple voltage correction devices, and anti-islanding. This work explores the use of dynamic phasors and differential algebraic equations (DAE) for impact analysis of the PV generators on the existing distribution feeders.
The voltage unbalance induced by PV generators can aggravate the existing unbalance due to load mismatch. An increased phase unbalance significantly adds to the neutral currents, excessive neutral to ground voltages and violate the standards for unbalance factor. The objective of this study is to analyze and quantify the impacts of unbalanced PV installations on a distribution feeder. Additionally, a power electronic converter solution is proposed to mitigate the identified impacts and validate the solution's effectiveness through detailed simulations in OpenDSS.
The benefits associated with the use of energy storage systems for electric- utility-related applications are also studied. This research provides a generalized framework for strategic deployment of a lithium-ion based energy storage system to increase their benefits in a distribution feeder. A significant amount of work has been performed for a detailed characterization of the life cycle costs of an energy storage system. The objectives include - reduction of the substation transformer losses, reduction of the life cycle cost for an energy storage system, and accommodate the PV variability.
The distribution feeder laterals in the distribution feeder with relatively high PV generation as compared to the load can be operated as microgrids to achieve reliability, power quality and economic benefits. However, the renewable resources are intermittent and stochastic in nature. A novel approach for sizing and scheduling the energy storage system and microtrubine is proposed for reliable operation of microgrids. The size and schedule of the energy storage system and microturbine are determined using Benders' decomposition, considering the PV generation as a stochastic resource.
The voltage unbalance induced by PV generators can aggravate the existing unbalance due to load mismatch. An increased phase unbalance significantly adds to the neutral currents, excessive neutral to ground voltages and violate the standards for unbalance factor. The objective of this study is to analyze and quantify the impacts of unbalanced PV installations on a distribution feeder. Additionally, a power electronic converter solution is proposed to mitigate the identified impacts and validate the solution's effectiveness through detailed simulations in OpenDSS.
The benefits associated with the use of energy storage systems for electric- utility-related applications are also studied. This research provides a generalized framework for strategic deployment of a lithium-ion based energy storage system to increase their benefits in a distribution feeder. A significant amount of work has been performed for a detailed characterization of the life cycle costs of an energy storage system. The objectives include - reduction of the substation transformer losses, reduction of the life cycle cost for an energy storage system, and accommodate the PV variability.
The distribution feeder laterals in the distribution feeder with relatively high PV generation as compared to the load can be operated as microgrids to achieve reliability, power quality and economic benefits. However, the renewable resources are intermittent and stochastic in nature. A novel approach for sizing and scheduling the energy storage system and microtrubine is proposed for reliable operation of microgrids. The size and schedule of the energy storage system and microturbine are determined using Benders' decomposition, considering the PV generation as a stochastic resource.
ContributorsNagarajan, Adarsh (Author) / Ayyanar, Raja (Thesis advisor) / Vittal, Vijay (Committee member) / Heydt, Gerald (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2015
Description
Scarcity of potable water is one of the major problems faced in the world today. Majority of this problem can be solved if technology is developed to obtain potable water from brackish or saline water. The present desalination methods face challenges such as high costs in terms of energy consumption and infrastructure, physical size of the system, requirement of membrane and high pressure systems and hence have been facing various issues in implementation of the same.
This research provides a new low pressure, low energy, portable method to desalinate water without the need for separation membranes, heat or chemical reactions. This method is energy efficient, cost effective, compact, environment friendly and suitable for portable desalination units. This technology, named as Polyphase Alternating current Bi-Ionic Propulsion System (PACBIPS) makes use of polyphase alternating current source to create a gradient in salt concentration. The gradient in salt concentration is achieved due to the creation of a traveling wave which attracts anions on its positive peak (crests) and cations on its negative peak (troughs) and travels along a central pipe thereby flushing the ions down.
Another method of PACBIPS is based on Helmholtz capacitor which involves the formation of an electric double layer between the electrode and electrolyte consisting of equal and opposite ions which can be approximated as a capacitor. Charging and discharging this capacitor helps adsorb the ions onto a carbon electrode which has high surface area and electrical conductivity. This desalinates seawater and provides pure water. Mathematical modeling, analysis and implementation of the two methods have
been presented in this work. The effects of zeta potential, electric field screening, electric mobility on desalination have been discussed.
This research provides a new low pressure, low energy, portable method to desalinate water without the need for separation membranes, heat or chemical reactions. This method is energy efficient, cost effective, compact, environment friendly and suitable for portable desalination units. This technology, named as Polyphase Alternating current Bi-Ionic Propulsion System (PACBIPS) makes use of polyphase alternating current source to create a gradient in salt concentration. The gradient in salt concentration is achieved due to the creation of a traveling wave which attracts anions on its positive peak (crests) and cations on its negative peak (troughs) and travels along a central pipe thereby flushing the ions down.
Another method of PACBIPS is based on Helmholtz capacitor which involves the formation of an electric double layer between the electrode and electrolyte consisting of equal and opposite ions which can be approximated as a capacitor. Charging and discharging this capacitor helps adsorb the ions onto a carbon electrode which has high surface area and electrical conductivity. This desalinates seawater and provides pure water. Mathematical modeling, analysis and implementation of the two methods have
been presented in this work. The effects of zeta potential, electric field screening, electric mobility on desalination have been discussed.
ContributorsKrishna Kashyap, Suhas (Author) / Hui, Joseph (Thesis advisor) / Ayyanar, Raja (Committee member) / Rodriguez, Armando A (Committee member) / Arizona State University (Publisher)
Created2014
Description
This thesis concerns the impact of energy storage on the power system. The rapidly increasing integration of renewable energy source into the grid is driving greater attention towards electrical energy storage systems which can serve many applications like economically meeting peak loads, providing spinning reserve. Economic dispatch is performed with bulk energy storage with wind energy penetration in power systems allocating the generation levels to the units in the mix, so that the system load is served and most economically. The results obtained in previous research to solve for economic dispatch uses a linear cost function for a Direct Current Optimal Power Flow (DCOPF). This thesis uses quadratic cost function for a DCOPF implementing quadratic programming (QP) to minimize the function. A Matlab program was created to simulate different test systems including an equivalent section of the WECC system, namely for Arizo-na, summer peak 2009. A mathematical formulation of a strategy of when to charge or discharge the storage is incorporated in the algorithm. In this thesis various test cases are shown in a small three bus test bed and also for the state of Arizona test bed. The main conclusions drawn from the two test beds is that the use of energy storage minimizes the generation dispatch cost of the system and benefits the power sys-tem by serving the peak partially from stored energy. It is also found that use of energy storage systems may alleviate the loading on transmission lines which can defer the upgrade and expansion of the transmission system.
ContributorsGupta, Samir (Author) / Heydt, Gerald T (Thesis advisor) / Vittal, Vijay (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2012
Description
The inherent intermittency in solar energy resources poses challenges to scheduling generation, transmission, and distribution systems. Energy storage devices are often used to mitigate variability in renewable asset generation and provide a mechanism to shift renewable power between periods of the day. In the absence of storage, however, time series forecasting techniques can be used to estimate future solar resource availability to improve the accuracy of solar generator scheduling. The knowledge of future solar availability helps scheduling solar generation at high-penetration levels, and assists with the selection and scheduling of spinning reserves. This study employs statistical techniques to improve the accuracy of solar resource forecasts that are in turn used to estimate solar photovoltaic (PV) power generation. The first part of the study involves time series forecasting of the global horizontal irradiation (GHI) in Phoenix, Arizona using Seasonal Autoregressive Integrated Moving Average (SARIMA) models. A comparative study is completed for time series forecasting models developed with different time step resolutions, forecasting start time, forecasting time horizons, training data, and transformations for data measured at Phoenix, Arizona. Approximately 3,000 models were generated and evaluated across the entire study. One major finding is that forecasted values one day ahead are near repeats of the preceding day—due to the 24-hour seasonal differencing—indicating that use of statistical forecasting over multiple days creates a repeating pattern. Logarithmic transform data were found to perform poorly in nearly all cases relative to untransformed or square-root transform data when forecasting out to four days. Forecasts using a logarithmic transform followed a similar profile as the immediate day prior whereas forecasts using untransformed and square-root transform data had smoother daily solar profiles that better represented the average intraday profile. Error values were generally lower during mornings and evenings and higher during midday. Regarding one-day forecasting and shorter forecasting horizons, the logarithmic transformation performed better than untransformed data and square-root transformed data irrespective of forecast horizon for data resolutions of 1-hour, 30-minutes, and 15-minutes.
ContributorsSoundiah Regunathan Rajasekaran, Dhiwaakar Purusothaman (Author) / Johnson, Nathan G (Thesis advisor) / Karady, George G. (Thesis advisor) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2016
Description
This research mainly focuses on improving the utilization of photovoltaic (PV) re-sources in distribution systems by reducing their variability and uncertainty through the integration of distributed energy storage (DES) devices, like batteries, and smart PV in-verters. The adopted theoretical tools include statistical analysis and convex optimization. Operational issues have been widely reported in distribution systems as the penetration of PV resources has increased. Decision-making processes for determining the optimal allo-cation and scheduling of DES, and the optimal placement of smart PV inverters are con-sidered. The alternating current (AC) power flow constraints are used in these optimiza-tion models. The first two optimization problems are formulated as quadratically-constrained quadratic programming (QCQP) problems while the third problem is formu-lated as a mixed-integer QCQP (MIQCQP) problem. In order to obtain a globally opti-mum solution to these non-convex optimization problems, convex relaxation techniques are introduced. Considering that the costs of the DES are still very high, a procedure for DES sizing based on OpenDSS is proposed in this research to avoid over-sizing.
Some existing convex relaxations, e.g. the second order cone programming (SOCP) relaxation and semidefinite programming (SDP) relaxation, which have been well studied for the optimal power flow (OPF) problem work unsatisfactorily for the DES and smart inverter optimization problems. Several convex constraints that can approximate the rank-1 constraint X = xxT are introduced to construct a tighter SDP relaxation which is referred to as the enhanced SDP (ESDP) relaxation using a non-iterative computing framework. Obtaining the convex hull of the AC power flow equations is beneficial for mitigating the non-convexity of the decision-making processes in power systems, since the AC power flow constraints exist in many of these problems. The quasi-convex hull of the quadratic equalities in the AC power bus injection model (BIM) and the exact convex hull of the quadratic equality in the AC power branch flow model (BFM) are proposed respectively in this thesis. Based on the convex hull of BFM, a novel convex relaxation of the DES optimizations is proposed. The proposed approaches are tested on a real world feeder in Arizona and several benchmark IEEE radial feeders.
Some existing convex relaxations, e.g. the second order cone programming (SOCP) relaxation and semidefinite programming (SDP) relaxation, which have been well studied for the optimal power flow (OPF) problem work unsatisfactorily for the DES and smart inverter optimization problems. Several convex constraints that can approximate the rank-1 constraint X = xxT are introduced to construct a tighter SDP relaxation which is referred to as the enhanced SDP (ESDP) relaxation using a non-iterative computing framework. Obtaining the convex hull of the AC power flow equations is beneficial for mitigating the non-convexity of the decision-making processes in power systems, since the AC power flow constraints exist in many of these problems. The quasi-convex hull of the quadratic equalities in the AC power bus injection model (BIM) and the exact convex hull of the quadratic equality in the AC power branch flow model (BFM) are proposed respectively in this thesis. Based on the convex hull of BFM, a novel convex relaxation of the DES optimizations is proposed. The proposed approaches are tested on a real world feeder in Arizona and several benchmark IEEE radial feeders.
ContributorsLi, Qifeng (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald T (Committee member) / Mittelmann, Hans D (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2016