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A review of microgrid development in the United States – A decade of progress on policies, demonstrations, controls, and software tools
Microgrids have become increasingly popular in the United States. Supported by favorable federal and local policies, microgrid projects can provide greater energy stability and resilience within a project site or community. This paper reviews major federal, state, and utility-level policies driving microgrid development in the United States. Representative U.S. demonstration projects are selected and their technical characteristics and non-technical features are introduced. The paper discusses trends in the technology development of microgrid systems as well as microgrid control methods and interactions within the electricity market. Software tools for microgrid design, planning, and performance analysis are illustrated with each tool's core capability. Finally, the paper summarizes the successes and lessons learned during the recent expansion of the U.S. microgrid industry that may serve as a reference for other countries developing their own microgrid industries
Binary Search Algorithm for Mixed Integer Optimization: Application to energy management in a microgrid
This paper presents a binary search algorithm
to deal with binary variables in mixed integer optimization
problems. One example of this kind of problem is the optimal
operation of hydrogen storage and energy sale and purchase
into a microgrids context. In this work was studied a system
composed by a microgrid that has a connection with the
external electrical network and a charging station for electric
cars. The system modeling was carried out by the Energy
Hubs methodology. The proposed algorithm transforms the
MIQP (Mixed Integer Quadratic Program) problem into a QP
(Quadratic Program) that is easier to solve. In this way the
overall control task is carried out the electricity purchase and
sale to the power grid, maximizes the use of renewable energy
sources, manages the use of energy storages and supplies the
charge of the parked vehicles.Ministerio de EconomĂa y Competitividad DPI2013-46912-C2-1-RUniversidad de Sevilla CNPq401126/2014-5Universidad de Sevilla CNPq303702/2011-
The Comparison Study of Short-Term Prediction Methods to Enhance the Model Predictive Controller Applied to Microgrid Energy Management
Electricity load forecasting, optimal power system operation and energy management play key roles that can bring significant operational advantages to microgrids. This paper studies how methods based on time series and neural networks can be used to predict energy demand and production, allowing them to be combined with model predictive control. Comparisons of different prediction methods and different optimum energy distribution scenarios are provided, permitting us to determine when short-term energy prediction models should be used. The proposed prediction models in addition to the model predictive control strategy appear as a promising solution to energy management in microgrids. The controller has the task of performing the management of electricity purchase and sale to the power grid, maximizing the use of renewable energy sources and managing the use of the energy storage system. Simulations were performed with different weather conditions of solar irradiation. The obtained results are encouraging for future practical implementation
Application of Neural-Like P Systems With State Values for Power Coordination of Photovoltaic/Battery Microgrids
The power coordination control of a photovoltaic/battery microgrid is performed with a novel
bio-computing model within the framework of membrane computing. First, a neural-like P system with
state values (SVNPS) is proposed for describing complex logical relationships between different modes
of Photovoltaic (PV) units and energy storage units. After comparing the objects in the neurons with the
thresholds, state values will be obtained to determine the con guration of the SVNPS. Considering the
characteristics of PV/battery microgrids, an operation control strategy based on bus voltages of the point of
common coupling and charging/discharging statuses of batteries is proposed. At rst, the SVNPS is used to
construct the complicated unit working modes; each unit of the microgrid can adjust the operation modes
automatically. After that, the output power of each unit is reasonably coordinated to ensure the operation
stability of the microgrid. Finally, a PV/battery microgrid, including two PV units, one storage unit, and
some loads are taken into consideration, and experimental results show the feasibility and effectiveness of
the proposed control strategy and the SVNPS-based power coordination control models
Smart Microgrids: Overview and Outlook
The idea of changing our energy system from a hierarchical design into a set
of nearly independent microgrids becomes feasible with the availability of
small renewable energy generators. The smart microgrid concept comes with
several challenges in research and engineering targeting load balancing,
pricing, consumer integration and home automation. In this paper we first
provide an overview on these challenges and present approaches that target the
problems identified. While there exist promising algorithms for the particular
field, we see a missing integration which specifically targets smart
microgrids. Therefore, we propose an architecture that integrates the presented
approaches and defines interfaces between the identified components such as
generators, storage, smart and \dq{dumb} devices.Comment: presented at the GI Informatik 2012, Braunschweig Germany, Smart Grid
Worksho
Optimization of the operation of smart rural grids through a novel rnergy management system
The paper proposes an innovative Energy Management System (EMS) that optimizes the grid operation based on economic and technical criteria. The EMS inputs the demand and renewable generation forecasts, electricity prices and the status of the distributed storages through the network, and solves with an optimal quarter-hourly dispatch for controllable resources. The performance of the EMS is quantified through diverse proposed metrics. The analyses were based on a real rural grid from the European FP7 project Smart Rural Grid. The performance of the EMS has been evaluated through some scenarios varying the penetration of distributed generation. The obtained results demonstrate that the inclusion of the EMS from both a technical point of view and an economic perspective for the adopted grid is justified. At the technical level, the inclusion of the EMS permits us to significantly increase the power quality in weak and radial networks. At the economic level and from a certain threshold value in renewables’ penetration, the EMS reduces the energy costs for the grid participants, minimizing imports from the external grid and compensating the toll to be paid in the form of the losses incurred by including additional equipment in the network (i.e., distributed storage).Postprint (published version
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