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MAS-based whole-sale and retail power market design for smart grid A « less.Application of DR in enhancing the performance of load-frequency controller.Real-time MG power management using DR and storage (partially supported by NEC Labs-America).Application of DR in dealing with the variability of wind power.
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Through analytic and simulation studies, we evaluated the suitability of several heuristic and artificial-intelligence (AI)-based optimization techniques that had potential for real-time MG power management, including genetic algorithms (GA), ant colony optimization (ACO), particle swarm optimization (PSO), and multi-agent systems (MAS), which is based on the negotiation of smart software-based agents. The objective of the project was to investigate real-time power management strategies for MGs using intelligent control, considering maximum feasible energy sustainability, reliability and efficiency while, minimizing cost and undesired environmental impact (emissions). We compared the findings from WebOpt and HOMER and designed appropriately sized hybrid systems for our case studies.
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We also used the software “HOMER,” originally developed at the National Renewable Energy Laboratory (NREL) and the most recent version made available to us by HOMER Energy, Inc., for MG (hybrid energy system) unit sizing. NEC-Labs America, a private industry, also supported our project, providing expert support and modest financial support. Chris Marney more » of LBL provided actual load data, and the software WEBOPT developed at LBL for microgrid (MG) design for our project. The graduate student is now supported be the Electrical and Computer Engineering (ECE) Department at Montana State University (MSU). He is also a committee member of a current graduate student of the PI who was supported by this project in the last two years (August 2014-July 2016). students (graduated in 2014) who was supported by this project. Hammerstrom of PNNL initially supported our project and was on the graduate committee of one of the Ph.D. In this Project we collaborated with two DOE National Laboratories, Pacific Northwest National Lab (PNNL) and Lawrence Berkeley National Lab (LBL). The results established that (1) the GMC is successful in seamlessly transitioning the microgrids to and from an islanded mode, (2) a load/generation mismatch at the time of separation depends on the microgrid configuration and must be lower than a specific value determined by simulation testing, and (3) the GMC Dispatch Function response is acceptable in maintaining, in the islanded mode, 60Hz for a range of load changes. For each microgrid, the GMC was tested in hardware-in-the-loop (HIL) using an OPAL-RT real-time digital simulator, and the two core functions were assessed. The GMC specifications were demonstrated and evaluated using a commercial simulation platform for two different microgrids, a 20MW-Class community microgrid and a 10MW-Class medical center microgrid. A GMC must address two core functions, Transition and Dispatch, as well as several optional higher level functions such as economic dispatch, and renewable and load forecasting. To reduce this cost and address standardization, specifications for a Generic Microgrid Controller (GMC) were developed with the goal to facilitate the design and ease of adaptation of microgrid more » controllers to various microgrids of different sizes and with different resources. One barrier to microgrids is the historic cost and lack of standardization associated with microgrid controllers. Microgrids have garnered attention in recent years as a way to increase the reliability of the grid, increase the reliability of electricity service to customers, adapt to an increasing percentage of intermittent renewable generation, and serve both customer critical loads and the needs of adjacent communities in the case of emergencies such as natural disasters.