FPGA-based Real-time Simulation of Grid-Connected Distributed Solar Systems using Multi-Agent Control

可再生能源在配电系统中的高度渗透给电网的电压调节带来了挑战。电压不稳定会对电网造成严重的破坏。当前电力系统控制的趋势是采用分布式、柔性和鲁棒性结构。应用基于智能体的控制系统是解决复杂并行问题的有效途径。乘法器的交替方向法（ADMM）可以作为设计分布式计算系统的理论框架。基于admm的算法是一种迭代优化方法，能够将复杂问题以完全分布的方式分解成多个子问题来求解复杂问题。实时仿真是一种有效的方法，使研究人员能够在安全的环境中测试复杂设计的控制器。然而，实时仿真器的计算时间随着模型的复杂性而增加。近年来，尽管多智能体控制技术在电力系统中的应用具有明显的优势，但为了充分利用现场可编程门阵列（fpga）的实时并行化硬件结构，对ADMM算法进行修改的工作却很少。基于fpga的平台用于硬件在环（HIL）测试，作为在更短时间内运行更真实模型的解决方案。fpga以更少的时间步长和更高的灵活性提供高性能并行仿真。该程序是一个创新的应用程序，在实时仿真的并网光伏系统集成到一个基于多智能体系统的最优电压控制。不同代理之间的协调将使用FPGA实现。该项目的主要目标是设计一种创新、简单、强大的FPGA应用，用于实时控制与Hydro- qu网络相连的光伏系统，以确保对本地能源的最佳管理以及清洁能源的安全注入。该计划的短期目标是：1。设计并仿真了一种基于ADMM的智能代理控制算法。2.分析了该技术在pv高穿透下的运行情况。3.开发基于分布式优化的电压控制算法，加快算法的收敛速度。4.通过在实际网络上的大规模实现，验证了该方法的有效性。5.设计一种使用实时fpga的并行仿真方法，确保整个系统划分的最小延迟。该项目的长期目标是：1。实现了一种低成本、有效的解决配电网和输电网不确定情况下的电压稳定问题的方法。2.为了减少分布式ADMM算法的运行时间，提出了一种基于神经网络的智能agent训练方法。3.在管理和控制当地微型网络方面发展独特的专门知识。

High penetration of renewable energy sources in distribution power systems is causing challenges to the voltage regulation of grids. Voltage instability may trigger serious damages in power networks. Current trend in control of power systems is moving toward the use of distributed, flexible, and robust structures. Applying an intelligent agent-based control system is an effective way for solving complex problems in parallel. The Alternating Direction Method of Multipliers (ADMM) can be used as a theoretical framework to design distributed computational systems. ADMM-based algorithm is an iterative optimization method able to solve complex problems by decomposing them into multiple sub-problems in a fully distributed way. Real-time simulation is an efficient way that allows researchers to test complex designed controllers in a secure environment. However, the computational time in the real-time (RT) simulators increase with the complexity of the models. In recent years, despite the identified advantages of the application of multi-agent control technique in power systems, only a few works have been done to modify the ADMM algorithm to fully utilize the parallelized hardware structure of the Field Programmable Gate Arrays (FPGAs) in real-time. FPGA-based platforms are used for Hardware-in-the-Loop (HIL) testing as a solution for running more realistic models in less time. FPGAs offer high-performance simulations in parallel with less time step and higher flexibility. This program is an innovative application in real-time simulation of grid-connected PV systems integrated to an optimal voltage control based on multi-agent systems. Coordination between different agents will be implemented using FPGA. The main objective of the program is to design an innovative, simple, and robust application of FPGA in real-time control of PV systems connected to Hydro- Québec's networks to ensure optimal management of local energy as well as the safe injection of clean energy. The short-term objectives of the program are to: 1.Design and simulate an intelligent agent-based control algorithm based on ADMM. 2.Analyze the operation of proposed technique under high penetrations of PVs. 3.Develop the distributed optimization-based voltage control algorithm to accelerate the convergence of the algorithm. 4.Validate the method by implement it on real networks in large-scale. 5.Design a parallel simulation approach using real-time FPGAs ensuring minimum latency in the whole system division. The long-term objectives of the project are to: 1. Implement a low-cost and effective solution for voltage stability of the system under uncertainties during distribution and transmission level.  2.Develop an intelligent method for training the agents using neural networks aims to reduce the running time of distributed ADMM algorithms. 3.Develop a unique expertise in the management and control of local micro-networks.