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All Subjects: Alternative Energy
Creators: Johnson, Nathan

Dispatch strategy development for grid-tied household energy systems

Description

The prevalence of renewable generation will increase in the next several decades and offset conventional generation more and more. Yet this increase is not coming without challenges. Solar, wind, and even some water resources are intermittent and unpredictable, and thereby create scheduling challenges due to their inherent “uncontrolled” nature. To effectively manage these distributed renewable assets, new control algorithms must be developed for applications including energy management, bridge power, and system stability. This can be completed through a centralized control center though efforts are being made to parallel the control architecture with the organization of the renewable assets themselves—namely, distributed controls. Building energy management systems are being employed to control localized energy generation, storage, and use to reduce disruption on the net utility load. One such example is VOLTTRONTM, an agent-based platform for building energy control in real time. In this thesis, algorithms developed in VOLTTRON simulate a home energy management system that consists of a solar PV array, a lithium-ion battery bank, and the grid. Dispatch strategies are implemented to reduce energy charges from overall consumption ($/kWh) and demand charges ($/kW). Dispatch strategies for implementing storage devices are tuned on a month-to-month basis to provide a meaningful economic advantage under simulated scenarios to explore algorithm sensitivity to changing external factors. VOLTTRON agents provide automated real-time optimization of dispatch strategies to efficiently manage energy supply and demand, lower consumer costs associated with energy usage, and reduce load on the utility grid.

ContributorsCardwell, Joseph (Author) / Johnson, Nathan (Thesis advisor) / Rogers, Bradley (Committee member) / Macia, Narciso (Committee member) / Arizona State University (Publisher)

Created2015

Model predictive control for resilient operation of hybrid microgrids

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

Diffuse radiation calculation methods

Description

Measuring and estimating solar resource availability is critical for assessing new sites for solar energy generation. This includes beam radiation, diffuse radiation, and total incident radiation. Total incident radiation is pertinent to solar photovoltaic (PV) output and low-temperature solar thermal applications whereas beam radiation is used for concentrating solar power (CSP). Global horizontal insolation (GHI) data are most commonly available of any solar radiation measurement, yet these data cannot be directly applied to solar power generator estimation because solar PV panels and solar CSP collectors are not parallel to the earth’s surface. In absence of additional measured data, GHI data may be broken down into its constituent parts—diffuse radiation and beam radiation—using statistical techniques that incorporate explanatory variables such as the clearness index. This study provides a suite of methods and regression models to estimate diffuse radiation as a function of various explanatory variables using both piecewise and continuous fits. Regression analyses using the clearness index are completed for seven locations in the United States and four locations in other regions of the world. The multi-site analysis indicates that models developed using training data for a single location perform best in that location, yet general models can be created that perform reasonably well across any locality and then applied to estimate solar resource availability in new locations around the world. Results from the global and site-specific models perform better than the existing models in literature and indicate that models perform different in different sky conditions e.g. clear or cloudy sky. Results also show that continuous models perform equivalent or better than the piecewise models. Newly generated piecewise models showed improvement over some intervals in the clearness index. A combination of fits from this study and existing literature was used to improve overall performance of modeling techniques used in diffuse radiation estimation. Germany was selected for more detailed studies of a single case study using the clearness index, ambient temperature, relative humidity, and absolute humidity as explanatory variables. Clearness index is the most important variable for diffuse radiation calculation whereas the relative humidity and the temperature are the secondary variable for improving calculation. Absolute humidity plays similar role as temperature in improving the calculation on the other hand relative humidity improves it very slightly over the absolute humidity and temperature.

ContributorsSingh, Uday P (Author) / Johnson, Nathan (Thesis advisor) / Rogers, Bradley (Committee member) / Tamizhmani, Govindasamy (Committee member) / Arizona State University (Publisher)

Created2016

ASU Electronic Theses and Dissertations

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Dispatch strategy development for grid-tied household energy systems

Model predictive control for resilient operation of hybrid microgrids

Diffuse radiation calculation methods