Matching Items (4)
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- All Subjects: energy
- Genre: Doctoral Dissertation
- Creators: Johnson, Nathan
- Member of: Theses and Dissertations
Description
Thermodynamic development and balance of plant study is completed for a 30 MW solar thermochemical water splitting process that generates hydrogen gas and electric power. The generalized thermodynamic model includes 23 components and 45 states. Quasi-steady state simulations are completed for design point system sizing, annual performance analysis and sensitivity analysis. Detailed consideration is given to water splitting reaction kinetics with governing equations generalized for use with any redox-active metal oxide material. Specific results for Ceria illustrate particle reduction in two solar receivers for target oxygen partial pressure of 10 Pa and particle temperature of 1773 K at a design point DNI of 900 W/m2. Sizes of the recuperator, steam generator and hydrogen separator are calculated at the design point DNI to achieve 100,000 kg of hydrogen production per day from the plant. The total system efficiency of 39.52% is comprised of 50.7% hydrogen fraction and 19.62% electrical fraction. Total plant capital costs and operating costs are estimated to equate a hydrogen production cost of $4.40 per kg for a 25-year plant life. Sensitivity analysis explores the effect of environmental parameters and design parameters on system performance and cost. Improving recuperator effectiveness from 0.7 to 0.8 is a high-value design modification resulting in a 12.1% decrease in hydrogen cost for a modest 2.0% increase in plant $2.85M. At the same time, system efficiency is relatively inelastic to recuperator effectiveness because 81% of excess heat is recovered from the system for electricity production 39 MWh/day and revenue is $0.04 per kWh. Increasing water inlet pressure up to 20 bar reduces the size and cost of super heaters but further pressure rises increasing pump at a rate that outweighs super heater cost savings.
ContributorsBudama, Vishnu Kumar (Author) / Johnson, Nathan (Thesis advisor) / Stechel, Ellen (Committee member) / Rykaczewski, Konrad (Committee member) / Phelan, Patrick (Committee member) / Wang, Robert (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 work introduces self-organizing techniques to reduce the complexity and burden of coordinating distributed energy resources (DERs) and microgrids that are rapidly increasing in scale globally. Technical and financial evaluations completed for power customers and for utilities identify how disruptions are occurring in conventional energy business models. Analyses completed for Chicago, Seattle, and Phoenix demonstrate site-specific and generalizable findings. Results indicate that net metering had a significant effect on the optimal amount of solar photovoltaics (PV) for households to install and how utilities could recover lost revenue through increasing energy rates or monthly fees. System-wide ramp rate requirements also increased as solar PV penetration increased. These issues are resolved using a generalizable, scalable transactive energy framework for microgrids to enable coordination and automation of DERs and microgrids to ensure cost effective use of energy for all stakeholders. This technique is demonstrated on a 3-node and 9-node network of microgrid nodes with various amounts of load, solar, and storage. Results found that enabling trading could achieve cost savings for all individual nodes and for the network up to 5.4%. Trading behaviors are expressed using an exponential valuation curve that quantifies the reputation of trading partners using historical interactions between nodes for compatibility, familiarity, and acceptance of trades. The same 9-node network configuration is used with varying levels of connectivity, resulting in up to 71% cost savings for individual nodes and up to 13% cost savings for the network as a whole. The effect of a trading fee is also explored to understand how electricity utilities may gain revenue from electricity traded directly between customers. If a utility imposed a trading fee to recoup lost revenue then trading is financially infeasible for agents, but could be feasible if only trying to recoup cost of distribution charges. These scientific findings conclude with a brief discussion of physical deployment opportunities.
ContributorsJanko, Samantha Ariel (Author) / Johnson, Nathan (Thesis advisor) / Zhang, Wenlong (Committee member) / Herche, Wesley (Committee member) / Arizona State University (Publisher)
Created2019
Description
Rapid increases in the installed amounts of Distributed Energy Resources are forcing a paradigm shift to guarantee stability, security, and economics of power distribution systems. This dissertation explores these challenges and proposes solutions to enable higher penetrations of grid-edge devices. The thesis shows that integrating Graph Signal Processing with State Estimation formulation allows accurate estimation of voltage phasors for radial feeders under low-observability conditions using traditional measurements. Furthermore, the Optimal Power Flow formulation presented in this work can reduce the solution time of a bus injection-based convex relaxation formulation, as shown through numerical results. The enhanced real-time knowledge of the system state is leveraged to develop new approaches to cyber-security of a transactive energy market by introducing a blockchain-based Electron Volt Exchange framework that includes a distributed protocol for pricing and scheduling prosumers' production/consumption while keeping constraints and bids private. The distributed algorithm prevents power theft and false data injection by comparing prosumers' reported power exchanges to models of expected power exchanges using measurements from grid sensors to estimate system state. Necessary hardware security is described and integrated into underlying grid-edge devices to verify the provenance of messages to and from these devices. These preventive measures for securing energy transactions are accompanied by additional mitigation measures to maintain voltage stability in inverter-dominated networks by expressing local control actions through Lyapunov analysis to mitigate cyber-attack and generation intermittency effects. The proposed formulation is applicable as long as the Volt-Var and Volt-Watt curves of the inverters can be represented as Lipschitz constants. Simulation results demonstrate how smart inverters can mitigate voltage oscillations throughout the distribution network. Approaches are rigorously explored and validated using a combination of real distribution networks and synthetic test cases. Finally, to overcome the scarcity of real data to test distribution systems algorithms a framework is introduced to generate synthetic distribution feeders mapped to real geospatial topologies using available OpenStreetMap data. The methods illustrate how to create synthetic feeders across the entire ZIP Code, with minimal input data for any location. These stackable scientific findings conclude with a brief discussion of physical deployment opportunities to accelerate grid modernization efforts.
ContributorsSaha, Shammya Shananda (Author) / Johnson, Nathan (Thesis advisor) / Scaglione, Anna (Thesis advisor) / Arnold, Daniel (Committee member) / Boscovic, Dragan (Committee member) / Arizona State University (Publisher)
Created2021