Extending the AgentSpring/EMLab Tool to Evaluate Additional Agent Behaviour such as Electric Vehicles and Demand Side Response.

开发基于Java的POWER EMLab(AgentSpring)的PYTHON端口允许集成其他基于PYTHON的POWER框架，如PowerGama和SmartNet。这一新框架允许我们通过DSR、聚合、灵活性和电动汽车等短期建模问题来扩展长期投资和政策建模。使用基于智能体的建模(ABM)和多智能体系统(MAS)范例来研究计算经济学和社会影响是一种重要的方法，它能够建立对任何未来电网结构的整体理解，特别是其随时间的演变。随着分布式能源(DER)的普及，这类电力系统将变得越来越复杂，包括风能和太阳能等具有可变发电输出的可再生资源。在电力环境中加入新的参与者，如电动汽车(EV)车主、灵活需求、聚合器和数字平台提供商(例如提供P2P服务)，将使系统进一步复杂化，具有未知的交互和策略，这将影响价格、投资行为和系统运营(电压、线路拥塞等)。在其他事情中。了解这些原因和影响，以及未来的政策制定者和监管机构如何促进这个不断发展和复杂的系统中参与者之间更好、更有效的互动，将是极其有价值的。这项工作的目的是开发一个多层次、多尺度的ABM/MAS框架，以帮助我们更好地识别和评估这些影响，并使我们能够更好地了解规则和政策如何影响能源网络和市场参与者的行为。

Development of a python port of the java based power EMLab(AgentSpring) allows integration of other python based power frameworks such as PowerGama and SmartNet. This new framework allows us to extend long term investment and policy modelling with short term modelling issues such as DSR , Aggregation, flexibility and EV's . Using the Agent based Modelling (ABM) and Multi agent System (MAS) paradigm for computational economics and for investigating societal effects is an important methodology that enables building a holistic understanding of any future power grid structure and, particularly, its evolution through time. Such power systems will become ever more complex with an increased penetration of Distributed Energy Resources (DER), including renewable resources with variable generation output such as wind and solar. The addition of new actors in the power environment such as Electric Vehicle (EV) Owners, flexible demand, aggregators and digital platform providers (e.g. providing P2P services) will further complicate the system with unknown interactions and strategies which will impact prices, investment behaviour and system operation (voltages, line congestion etc.) amongst other things. Understanding these causes and effects, and how future policy makers and regulators could facilitate better and more efficient interaction among the players in this ever evolving and complex system, would be extremely valuable.The aim of the work is to develop a multi-level multi-scale ABM/MAS framework to help us better identify and evaluate these effects and to enable better understanding of how rules and polices can affect energy networks and market participant behaviour.