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A microgrid is defined as an integrated energy system consisting of interconnected distributed generation (DG) sources, along with energy storage devices and controllable loads located at or near the end-use customers at the distribution level. The portfolio of these small-scale generation and storage technologies, which are generally known as distributed energy resources (DER), includes renewable energy technologies, internal combustion engines, microturbines, fuel cells, battery storage, and flywheel energy storage. Such systems can operate in parallel with the grid during normal conditions or in a controlled islanded mode during emergency conditions. The deployment of a microgrid is expected to increase system robustness, resilience and security, deliver higher power security to critical loads, allow renewable integration and enable inclusion of emerging technologies.
The main objective of this work was to explore the feasibility of and provide guidelines for the development of microgrids in campus-type facilities. The work was divided into two phases:
The objective of the first phase was to develop a microgrid simulation test bench at Virginia Tech. The developed simulation tool included both DER and load models, as well as demand response algorithms. The simulation tool can be used for planning and evaluation of microgrid deployment and is capable of estimating benefits of deploying a microgrid in campus-type facilities. The objective of the second phase was to identify a set of technical and operational criteria for developing a microgrid on a military base, including the introduction of renewable energy sources. These criteria were applied to quantify reliability benefits of a microgrid hosting energy efficient equipment along with renewable energy sources.
The technical approach consisted of: (1) development of the microgrid simulation test bench including various DG and storage options; (2) expansion of the test bench to include load models; (3) development of microgrid management strategies to perform demand response; (4) development of case studies to analyze benefits of microgrid operations; (5) gathering necessary information from Ft. Bragg; (6) identification of microgrid development criteria, including its boundary parameters; (7) development of a microgrid case study using a part of an electric power distribution system at the base; (8) analysis of operational (reliability) benefits of the microgrid; and (9) preparation of the general guidelines for microgrid deployment in a campus-type facility.
The key outcome of this project was a set of design criteria and general guidelines that can be used as a reference for deploying a microgrid in a campus-type facility, and establishing their cost-benefit impacts. There are seven design criteria and guidelines dealing with various phases of microgrid deployment, e.g. planning, design, operation, risk and benefit assessment. They include: (1) A microgrid definition and its boundary selection criteria; (2) Recommended microgrid design criteria to achieve three microgrid properties – robustness, resilience and security; (3) Recommended microgrid design criteria for selecting type and size of DERs for microgrid deployment; (4) Recommended microgrid design criteria for load classification and prioritization; (5) Recommended microgrid operation strategies; (6) Recommended system studies and necessary standards; (7) Potential risks on microgrid deployment and operation; and (8) Guideline to estimate microgrid benefits.
The simulation tool/methodology – that comprises various DER and load models as well as demand response algorithms – was the other significant outcome of this work. The project team used the developed simulation models to estimate potential benefits of deploying a microgrid.
The set of guidelines developed through this project will provide the Department of Defense (DoD) with general recommendations when deploying a microgrid. Additionally, the simulation tool/methodology and simulation results will provide an insight into the estimation of microgrid benefits, including reliability improvement, as well as peak shaving and energy reduction potentials due to management of supply-side and demand-side resources.