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Hybrid Energy Cooperative Control Modeling and Simulation Analysis in Smart Home

Author: ShenJiaJian
Tutor: YangGenKe
School: Shanghai Jiaotong University
Course: Control Theory and Control Engineering
Keywords: Energy Management Control Model Particle Swarm Optimization Demand Side Management Smart grid
CLC: TP273
Type: Master's thesis
Year: 2012
Downloads: 87
Quote: 0
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Abstract


With the growing concern with greenhouse gas emissions and fossil fuel prices, the renewable energy, distributed power generation and energy storage have received unprecedented attentions. Encouraging families to invest in micro-generation is one of the important directions in Smart Grid development, so as to partially satisfy the local electricity needs. Currently, as an effective mean of demand-side management, Time Of Use (TOU) Power Price guides the consumer to voluntarily take action to save electricity, changing the way of using electricity and transforming the curve shape in order to achieve the purpose of peak load shifting. Therefore, the TOU Power Price strategy can reduce construction and operation costs of power system.The existing new energy devices which are mainly installated in families are photovoltaic panels, solar collectors, etc. Wind, solar and other green energy are featured by random, intermittent characteristics, which are often influenced by the weather and related with their loations. In the meantime, their energy output can hardly meet the immediate energy needs of the user. Therefore, imbalance between the energy supply and consumption will appear in the smart home nodes. In order to reduce the families’dependence on public power and encourage them as much as possible to use of their new energy equipment installed for energy supply, battery energy storage devices have been introduced into the home.In this paper, we propose the optimization control model for power management at smart homes, which is equipped with photovoltaic panel, grid and solar collector. We choose indoor heating power, solar heating system switch, and battery charge-discharge power as control variables, and maximize the user’s satisfaction for dynamic temperature and hot water supply while minimizing the power consumption cost. Also, this optimization control problem is constricted by battery’s physical conditions and the fact that the communication between family node and grid is one-way. To solve this optimization problem, we propose particle swarm based solution, fulfilling the user’s transformation from static power consumer to dynamic participants.The effectiveness of the optimal control model and intelligent algorithm are demonstrated by simulating a virtual smart family. The optimization management of household mixed energy has significant economic benefits,and lays a solid foundation for the development of Family-side controller in smart grid.

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