Matching Items (8)

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Burkina Faso Hospital Microgrid Case Study

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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

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.

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  • 2019-05

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Model predictive control for resilient operation of hybrid microgrids

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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,

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.

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  • 2019

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On Enhancing Microgrid Control and the Optimal Design of a Modular Solid-State Transformer with Grid-Forming Inverter

Description

This dissertation covers three primary topics and relates them in context. High frequency transformer design, microgrid modeling and control, and converter design as it pertains to the other topics are

This dissertation covers three primary topics and relates them in context. High frequency transformer design, microgrid modeling and control, and converter design as it pertains to the other topics are each investigated, establishing a summary of the state-of-the-art at the intersection of the three as a baseline. The culminating work produced by the confluence of these topics is a novel modular solid-state transformer (SST) design, featuring an array of dual active bridge (DAB) converters, each of which contains an optimized high-frequency transformer, and an array of grid-forming inverters (GFI) suitable for centralized control in a microgrid environment. While no hardware was produced for this design, detailed modeling and simulation has been completed, and results are contextualized by rigorous analysis and comparison with results from published literature. The main contributions to each topic are best presented by topic area. For transformers, contributions include collation and presentation of the best-known methods of minimum loss high-frequency transformer design and analysis, descriptions of the implementation of these methods into a unified design script as well as access to an example of such a script, and the derivation and presentation of novel tools for analysis of multi-winding and multi-frequency transformers. For microgrid modeling and control, contributions include the modeling and simulation validation of the GFI and SST designs via state space modeling in a multi-scale simulation framework, as well as demonstration of stable and effective participation of these models in a centralized control scheme under phase imbalance. For converters, the SST design, analysis, and simulation are the primary contributions, though several novel derivations and analysis tools are also presented for the asymmetric half bridge and DAB.

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  • 2019

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A Qualitative Study of EMaaS Performance in California Schools

Description

In recent years, many school districts, community colleges, and universities in California have implemented energy management-as-a-service (EMaaS). The purpose of this study was to analyzes how EMaaS has been realized

In recent years, many school districts, community colleges, and universities in California have implemented energy management-as-a-service (EMaaS). The purpose of this study was to analyzes how EMaaS has been realized in California schools, including how performance expectations and service guarantees have been met, how value is created and captured, and which trends are emerging in the pay-for-performance models. This study used a qualitative research design to identify patterns in the collected data and allow theories to be drawn from the emergent categories and themes. Ten in-depth interviews were conducted with a diverse pool of facility managers, energy practitioners, superintendents, and associate superintendents working with EMaaS. Four themes emerged (1) peak shaving overperformance, (2) low risk/reward, (3) performance exactly as expected, and (4) hope in future flexibility. This study reveals medium to high levels of performance satisfaction from the customers of cloud-enabled and battery-based EMaaS in California schools. Value has been captured primarily through peak shaving and intelligent bill management. Large campuses with higher peaks are especially good at delivering energy savings, and in some instances without pairing batteries and solar. Where demand response participation is permitted by the utility companies, the quality of demand response performance is mixed, with performance being exactly as expected to slightly less than expected. The EMaaS business model is positioned to help California schools implement and achieve many of their future sustainability goals in a cost-effective way.

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Date Created
  • 2020

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Optimal Scheduling of Home Energy Management System with Plug-in Electric Vehicles Using Model Predictive Control

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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

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.

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  • 2018

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Optimal capacity and location assessment of natural gas fired distributed generation in residential areas

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With ever increasing use of natural gas to generate electricity, installed natural gas fired microturbines are found in residential areas to generate electricity locally. This research work discusses a generalized

With ever increasing use of natural gas to generate electricity, installed natural gas fired microturbines are found in residential areas to generate electricity locally. This research work discusses a generalized methodology for assessing optimal capacity and locations for installing natural gas fired microturbines in a distribution residential network. The overall objective is to place microturbines to minimize the system power loss occurring in the electrical distribution network; in such a way that the electric feeder does not need any up-gradation. The IEEE 123 Node Test Feeder is selected as the test bed for validating the developed methodology. Three-phase unbalanced electric power flow is run in OpenDSS through COM server, and the gas distribution network is analyzed using GASWorkS. The continual sensitivity analysis methodology is developed to select multiple DG locations and annual simulation is run to minimize annual average losses. The proposed placement of microturbines must be feasible in the gas distribution network and should not result into gas pipeline reinforcement. The corresponding gas distribution network is developed in GASWorkS software, and nodal pressures of the gas system are checked for various cases to investigate if the existing gas distribution network can accommodate the penetration of selected microturbines. The results indicate the optimal locations suitable to place microturbines and capacity that can be accommodated by the system, based on the consideration of overall minimum annual average losses as well as the guarantee of nodal pressure provided by the gas distribution network. The proposed method is generalized and can be used for any IEEE test feeder or an actual residential distribution network.

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Date Created
  • 2014

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Managing solar uncertainty in neighboring systems with stochastic unit commitment

Description

As renewable energy becomes more prevalent in transmission and distribution systems, it is vital to understand the uncertainty and variability that accompany these resources. Microgrids have the potential to mitigate

As renewable energy becomes more prevalent in transmission and distribution systems, it is vital to understand the uncertainty and variability that accompany these resources. Microgrids have the potential to mitigate the effects of resource uncertainty. With the ability to exist in either an islanded mode or maintain connections with the main-grid, a microgrid can increase reliability, defer T&D; infrastructure and effectively utilize demand response. This study presents a co-optimization framework for a microgrid with solar photovoltaic generation, emergency generation, and transmission switching. Today unit commitment models ensure reliability with deterministic criteria, which are either insufficient to ensure reliability or can degrade economic efficiency for a microgrid that uses a large penetration of variable renewable resources. A stochastic mixed integer linear program for day-ahead unit commitment is proposed to account for uncertainty inherent in PV generation. The model incorporates the ability to trade energy and ancillary services with the main-grid, including the designation of firm and non-firm imports, which captures the ability to allow for reserve sharing between the two systems. In order to manage the computational complexities, a Benders' decomposition approach is utilized. The commitment schedule was validated with solar scenario analysis, i.e., Monte-Carlo simulations are conducted to test the proposed dispatch solution. For this test case, there were few deviations to power imports, 0.007% of solar was curtailed, no load shedding occurred in the main-grid, and 1.70% load shedding occurred in the microgrid.

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  • 2013

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Modeling and control for microgrids

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

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.

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  • 2013