I-Corps: Approximate Dynamic Programming and Artificial Neural Network Control for Microgrids

I-Corps：微电网的近似动态规划和人工神经网络控制

• 批准号: 1744159
• 负责人: Shuhui Li
• 金额: $ 5万
• 依托单位: University of Alabama Tuscaloosa
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1744159&HistoricalAwards=false
• 关键词: Corps; Approximate; Dynamic; Programming; Artificial

The broader impact/commercial potential of this I-Corps project is to act as a catalyst in the growth of distributed generation and microgrid industries. This artificial intelligence based control system will potentially provide an electrical network that is reliable by reducing outages and restoration costs with incredibly fast bidirectional power flow, secured with real time diagnostics, self-healing and adaptive capabilities, and more economical by reducing equipment failures and minimizing power losses. The product potentially three broad markets, including utilities, distributed generation and consumer. The solution will enhance energy generation from renewables, improve microgrid efficiency, reliability, stability and power quality, and add intelligent control to conventional power systems. Inverter capabilities are presently a significant challenge for integrating distributed generation sources. The proposed innovation would potentially provide an appropriate solution to address this challenge.This I-Corps project develops a neural network control technology for microgrid control and management. Microgrids are one path for integrating renewable and distributed generation sources into the grid and can generally support a future smart electricity grid. A key challenge in microgrid adoption is adequate control of power inverters. Problems include high oscillations when connecting or disconnecting an energy source, fluctuating voltage and frequency, malfunctions and reliability, competing control between inverters, and high harmonic distortions. The proposed innovation uses adaptive dynamic programming and artificial neural networks to implement microgrid control. It integrates into one controller the advantages of conventional control methods, including optimal control, proportional integral control, predictive control, and sliding mode control. The proposed innovation has the potential to overcome the limitations of the conventional control technologies and better meet customer demands and requirements.

该I-Corps项目的更广泛的影响/商业潜力是充当分布式生成和微电网行业增长的催化剂。这种基于人工智能的控制系统将有可能提供一个可靠的电网，该电网通过降低停战和恢复成本的可靠性，并具有令人难以置信的快速双向电源流量，并具有实时诊断，自我修复和适应性功能，并通过减少设备故障和最小化功率损失来确保更经济。该产品可能是包括公用事业在内的三个广泛市场，分布式生成和消费者。该解决方案将增强可再生能源的能源，提高微电网效率，可靠性，稳定性和功率质量，并为传统的电力系统增加智能控制。逆变器功能目前是整合分布式发电源的重大挑战。提出的创新可能会提供适当的解决方案来应对这一挑战。该I-Corps项目开发了用于微电网控制和管理的神经网络控制技术。微电网是将可再生和分布式发电源集成到网格中的一条途径，通常可以支持未来的智能电网。 微电网采用率的关键挑战是对逆变器的充分控制。问题包括连接或断开能源时高振荡，电压和频率的波动，故障和可靠性，逆变器之间的竞争控制以及高谐波扭曲。提出的创新使用自适应动态编程和人工神经网络来实施微电网控制。它将传统控制方法的优势集成到一个控制器中，包括最佳控制，比例积分控制，预测控制和滑动模式控制。拟议的创新有可能克服常规控制技术的局限性并更好地满足客户需求和要求。