Matching Items (5)
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- All Subjects: Microgrid
- All Subjects: MIMO
- Creators: Johnson, Nathan
- Resource Type: Text
- Status: Published
Description
Traditional approaches to modeling microgrids include the behavior of each inverter operating in a particular network configuration and at a particular operating point. Such models quickly become computationally intensive for large systems. Similarly, traditional approaches to control do not use advanced methodologies and suffer from poor performance and limited operating range. In this document a linear model is derived for an inverter connected to the Thevenin equivalent of a microgrid. This model is then compared to a nonlinear simulation model and analyzed using the open and closed loop systems in both the time and frequency domains. The modeling error is quantified with emphasis on its use for controller design purposes. Control design examples are given using a Glover McFarlane controller, gain sched- uled Glover McFarlane controller, and bumpless transfer controller which are compared to the standard droop control approach. These examples serve as a guide to illustrate the use of multi-variable modeling techniques in the context of robust controller design and show that gain scheduled MIMO control techniques can extend the operating range of a microgrid. A hardware implementation is used to compare constant gain droop controllers with Glover McFarlane controllers and shows a clear advantage of the Glover McFarlane approach.
ContributorsSteenis, Joel (Author) / Ayyanar, Raja (Thesis advisor) / Mittelmann, Hans (Committee member) / Tsakalis, Konstantinos (Committee member) / Tylavsky, Daniel (Committee member) / Arizona State University (Publisher)
Created2013
Description
As the number of devices with wireless capabilities and the proximity of these devices to each other increases, better ways to handle the interference they cause need to be explored. Also important is for these devices to keep up with the demand for data rates while not compromising on industry established expectations of power consumption and mobility. Current methods of distributing the spectrum among all participants are expected to not cope with the demand in a very near future. In this thesis, the effect of employing sophisticated multiple-input, multiple-output (MIMO) systems in this regard is explored. The efficacy of systems which can make intelligent decisions on the transmission mode usage and power allocation to these modes becomes relevant in the current scenario, where the need for performance far exceeds the cost expendable on hardware. The effect of adding multiple antennas at either ends will be examined, the capacity of such systems and of networks comprised of many such participants will be evaluated. Methods of simulating said networks, and ways to achieve better performance by making intelligent transmission decisions will be proposed. Finally, a way of access control closer to the physical layer (a 'statistical MAC') and a possible metric to be used for such a MAC is suggested.
ContributorsThontadarya, Niranjan (Author) / Bliss, Daniel W (Thesis advisor) / Berisha, Visar (Committee member) / Ying, Lei (Committee member) / Arizona State University (Publisher)
Created2014
Description
With the growing penetration of plug-in electric vehicles (PEVs), the impact of the PEV charging brought to the utility grid draws more and more attention. This thesis focused on the optimization of a home energy management system (HEMS) with the presence of PEVs. For a household microgrid with photovoltaic (PV) panels and PEVs, a HEMS using model predictive control (MPC) is designed to achieve the optimal PEV charging. Soft electric loads and an energy storage system (ESS) are also considered in the optimization of PEV charging in the MPC framework. The MPC is solved through mixed-integer linear programming (MILP) by considering the relationship of energy flows in the optimization problem. Through the simulation results, the performance of optimization results under various electricity price plans is evaluated. The influences of PV capacities on the optimization results of electricity cost are also discussed. Furthermore, the hardware development of a microgrid prototype is also described in this thesis.
ContributorsZhao, Yue (Author) / Chen, Yan (Thesis advisor) / Johnson, Nathan (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2018
Description
This dissertation develops advanced controls for distributed energy systems and evaluates performance on technical and economic benefits. Microgrids and thermal systems are of primary focus with applications shown for residential, commercial, and military applications that have differing equipment, rate structures, and objectives. Controls development for residential energy heating and cooling systems implement adaptive precooling strategies and thermal energy storage, with comparisons made of each approach separately and then together with precooling and thermal energy storage. Case studies show on-peak demand and annual energy related expenses can be reduced by up to 75.6% and 23.5%, respectively, for a Building America B10 Benchmark home in Phoenix Arizona, Los Angeles California, and Kona Hawaii. Microgrids for commercial applications follow after with increased complexity. Three control methods are developed and compared including a baseline logic-based control, model predictive control, and model predictive control with ancillary service control algorithms. Case studies show that a microgrid consisting of 326 kW solar PV, 634 kW/ 634 kWh battery, and a 350 kW diesel generator can reduce on-peak demand and annual energy related expenses by 82.2% and 44.1%, respectively. Findings also show that employing a model predictive control algorithm with ancillary services can reduce operating expenses by 23.5% when compared to a logic-based algorithm. Microgrid evaluation continues with an investigation of off-grid operation and resilience for military applications. A statistical model is developed to evaluate the survivability (i.e. probability to meet critical load during an islanding event) to serve critical load out to 7 days of grid outage. Case studies compare the resilience of a generator-only microgrid consisting of 5,250 kW in generators and hybrid microgrid consisting of 2,250 kW generators, 3,450 kW / 13,800 kWh storage, and 16,479 kW solar photovoltaics. Findings show that the hybrid microgrid improves survivability by 10.0% and decreases fuel consumption by 47.8% over a 168-hour islanding event when compared to a generator-only microgrid under nominal conditions. Findings in this dissertation can increase the adoption of reliable, low cost, and low carbon distributed energy systems by improving the operational capabilities and economic benefits to a variety of customers and utilities.
ContributorsNelson, James Robert (Author) / Johnson, Nathan (Thesis advisor) / Stadler, Michael (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2019
Description
This paper analyzes Burkina Faso’s Souro Sanou University Hospital Center’s energy needs and discusses whether or not solar panels are a good investment. This paper also discusses a way to limit the damage caused by power outages. The hospital has a history of problems with power outages; in the summer they have power outages every other day lasting between one to four hours, and in the rainy season they have outages once every other week lasting the same amount of time.
The first step in this analysis was collecting relevant data which includes: location, electricity rates, energy consumption, and existing assets. The data was entered into a program called HOMER. HOMER is a program which analyzes an electrical system and determines the best configuration and usage of assets to get the lowest levelized cost of energy (LCOE). In HOMER, five different analyses were performed. They reviewed the hospital’s energy usage over 25 years: the current situation, one of the current situation with added solar panels, and another where the solar panels have single axis tracking. The other two analyses created incentives to have more solar panels, one situation with net metering, and one with a sellback rate of 0.03 $/kWh. The result of the analysis concluded that the ideal situation would have solar panels with a capacity of 300 kW, and the LCOE in this situation will be 0.153 $/kWh. The analysis shows that investing in solar panels will save the hospital approximately $65,500 per year, but the initial investment of $910,000 only allows for a total savings of $61,253 over the life of the project. The analysis also shows that if the electricity company, Sonabel, eventually buys back electricity then net metering would be more profitable than reselling electricity for the hospital.
Solar panels will help the hospital save money over time, but they will not stop power outages from happening at the hospital. For the outages to stop affecting the hospital’s operations they will have to invest in an uninterrupted power supply (UPS). The UPS will power the hospital for the time between when the power goes out and when their generators are turning on which makes it an essential investment. This will stop outages from affecting the hospital, and if the power goes out during the day then the solar panels can help supplement the energy production which will take some of the strain from their generators.
The results of this study will be sent to officials at the hospital and they can decide if the large initial investment justifies the savings. If the solar panels and UPS can save one life, then maybe the large initial investment is worth it.
The first step in this analysis was collecting relevant data which includes: location, electricity rates, energy consumption, and existing assets. The data was entered into a program called HOMER. HOMER is a program which analyzes an electrical system and determines the best configuration and usage of assets to get the lowest levelized cost of energy (LCOE). In HOMER, five different analyses were performed. They reviewed the hospital’s energy usage over 25 years: the current situation, one of the current situation with added solar panels, and another where the solar panels have single axis tracking. The other two analyses created incentives to have more solar panels, one situation with net metering, and one with a sellback rate of 0.03 $/kWh. The result of the analysis concluded that the ideal situation would have solar panels with a capacity of 300 kW, and the LCOE in this situation will be 0.153 $/kWh. The analysis shows that investing in solar panels will save the hospital approximately $65,500 per year, but the initial investment of $910,000 only allows for a total savings of $61,253 over the life of the project. The analysis also shows that if the electricity company, Sonabel, eventually buys back electricity then net metering would be more profitable than reselling electricity for the hospital.
Solar panels will help the hospital save money over time, but they will not stop power outages from happening at the hospital. For the outages to stop affecting the hospital’s operations they will have to invest in an uninterrupted power supply (UPS). The UPS will power the hospital for the time between when the power goes out and when their generators are turning on which makes it an essential investment. This will stop outages from affecting the hospital, and if the power goes out during the day then the solar panels can help supplement the energy production which will take some of the strain from their generators.
The results of this study will be sent to officials at the hospital and they can decide if the large initial investment justifies the savings. If the solar panels and UPS can save one life, then maybe the large initial investment is worth it.
ContributorsSchmidt, Evin Khalil (Author) / Johnson, Nathan (Thesis director) / Miner, Mark (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05