Hierarchical energy management system for microgrids

A two-layered hierarchical energy management system for a microgrid is built in this project, which is composed of a photovoltaic system, a battery energy storage system (BESS), a microturbine generator, and a heating, ventilation, and air-conditioning (HVAC) system in a local commercial building. T...

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Bibliographic Details
Main Author: Qin, Jinjiao
Other Authors: Gooi Hoay Beng
Format: Final Year Project (FYP)
Language:English
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10356/68356
Description
Summary:A two-layered hierarchical energy management system for a microgrid is built in this project, which is composed of a photovoltaic system, a battery energy storage system (BESS), a microturbine generator, and a heating, ventilation, and air-conditioning (HVAC) system in a local commercial building. The microgrid is in the grid connected operation mode, as power exchange between the microgrid and the power grid is allowed. The primary level controller aims to carry out Load Frequency Control, while the secondary level controller is based on Economic Dispatch. Both of the two level controls are designed using Model Predictive Control (MPC) strategy. In the project, software Matrix Laboratory (MATLAB) and General Algebraic Modeling System (GAMS) are utilized for simulation. The system modeling is based on characteristics of individual components inside the microgrid system, whole system balance and limits on the microgrid communicating with the outside utility. Both the simplified HVAC model and the realistic HVAC and building thermal model were developed on the basis of the fan power consumption model and aggregate building thermal model. The microgrid was implemented in three stages. At the first stage, a simplified HVAC system was incorporated in the primary controller and the incomplete MPC strategy is applied. When it comes to the second stage, the simplified HVAC model was replaced by a realistic HVAC and building thermal model. Besides, MPC strategy was fully implemented. At the third stage, on the basis of the second stage, the mechanism of optimal regulation power allocation was developed. The higher the stage is, the more mature the microgrid system is and better simulation performances can be obtained. Until the third stage, reliable and acceptable results can be obtained.