Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE): a Complexity Science-Based Investigation into the Smart Grid Concept

人们普遍承认，电力行业面临着一些严重的挑战，包括基础设施、能力限制和减少温室气体的需要等，但许多国家的放松管制产生了更复杂的问题。这导致了一种巴尔干化的形式，往往会对传统电网造成额外的压力，传统电网的结构基于对大型发电厂、远程高压输电和本地低压配电网络的集中指挥和管理。需要解决不同规模和不同层次上的一些相互关联的问题，包括需要昂贵的备用能力来满足高峰负荷，新工厂的资本成本高和筹备时间长，易受各种能源安全威胁的影响，分布式能源的非技术壁垒和更灵活和复杂的能源服务，可能会导致更高的能源效率。有迹象表明，一个新的模式，为现代电力工业正在定义一个分散的模式，根据最近和在DER和电力存储技术方面的预期进步，特别是信息和通信技术的快速发展，将使智能设备的大规模部署成为可能。特别是在美国，这一新概念-即所谓的智能电网-正在吸引大规模投资和政策认可，一些评论家将其发展与互联网的发展相比较，并预测其规模的变化可能代表电力行业及其最终用户的类似范式转变。如果这种情况真的发生了，那么集中主义的理论、法律和技术将在某个时候不再是有效的控制手段。互联网作为一种新的商业模式，被认为是复杂性理论的一个范例，与智能电网概念的相似之处表明了这门新科学作为阐述和应对挑战的手段的适当性。电力工业的现有结构和组织为有意义的研究提供了必要的起点和背景，研究所设想的演变机制，这可能是间断平衡的一个例子。复杂系统的思考和建模都是关于这种重大的结构性变化的发生，以及系统在不同政策和干预下可能演变的可能方式。这些因素联合收割机提供了一个独特的机会，以获得重要的洞察力，自我组织的出现和复杂的适应系统的演变，在场景中具有极高的相关性，一系列重要的政策问题，影响能源安全，碳减排和燃料贫困。复杂性科学为所提出的研究问题提供了一个协同的概念框架，并提供了一套特别适合于解决这些问题的工具和方法。这项研究将主要基于基于代理的建模，它能够模拟许多非线性，动态，历史依赖性，多尺度相互作用所产生的复杂性，反馈效应将击败传统的基于方程和统计建模。技术不典型的以前的建模和模拟的这种将被开发，以反映问题域的特殊功能，特别是社会经济和技术系统的紧密耦合，其中人类和人工智能代理人一起建模和模拟，并需要找到适当的水平和形式的认知表示。这些模型将基于以前对能源使用和供应问题的大量研究中的证据，特别是最近小规模部署技术和机制的例子，这些技术和机制被认为是智能电网作为一个复杂的自适应系统发展的关键。

It is widely acknowledged that the power industry faces a number of serious challenges including infrastructure, capacity constraints and the need to reduce greenhouse gas and other, but more complex issues have arisen from deregulation in many countries. This has resulted in a form of balkanisation that tends to cause additional stress to the legacy electricity grid, which has a structure based on centralised command and management of large scale generating plant, long-range high voltage transmission and local low voltage distribution networks. A number of interrelated problems on varying scales and at different levels need to be addressed, including the need for expensive standby capacity to meet peak loads, high capital cost and long lead-times for new plant, vulnerability to energy security threats of various kinds, and non-technical barriers to distributed energy resources (DERs) and more flexible and sophisticated energy services that might lead to greater energy efficiency.There are signs that a new paradigm for the modern electricity industry is being defined with a decentralised model based on recent and expected advances in DERs and electricity storage technology and, in particular, rapid developments in information and communication technology that will enable the wide scale deployment of smart devices. Particularly in the USA, this new concept - known as the smart grid - is attracting large scale investment and policy recognition, with some commentators comparing its development to that of the Internet and predicting change on a scale that could represent a paradigm shift of a similar kind for the electricity industry and its end-users. If this indeed occurs, then centralist theories, laws and techniques will at some point cease to be valid as the means of control.As well as being a new paradigm for business, the Internet has been considered to be a paradigm case for complexity theory and the parallel with the smart grid concept indicates the appropriateness of this new science as the means of articulating and answering the challenges it sets. The existing structure and organisation of the power industry provides the essential starting point and context for meaningful research into the mechanisms underlying the envisioned evolution, which may represent an example of a punctuated equilibrium. Complex systems thinking and modelling is all about the occurrence of such major, structural changes and the possible ways that the system may evolve under different policies and interventions. These factors combine to offer a unique opportunity to gain important insights into the emergence of self organisation and the evolution of complex adaptive systems in scenarios with extremely high relevance for a range of vital policy issues affecting energy security, carbon reduction and fuel poverty. Complexity science offers both a synergistic conceptual framework for the research questions raised and provides a set of tools and approaches particularly suited to their solution. This research will be based primarily on agent-based modelling, which enables simulation of the complexity arising from many non-linear, dynamic, history-dependent, multi-scale interactions with feedback effects that would defeat traditional equation-based and statistical modelling. Techniques not typical of previous modelling and simulation of this kind will be developed to reflect the special features of the problem domain, in particular the close coupling of socio-economic and technical systems, in which human and artificial intelligent agents are modelled and simulated together, and the need to find appropriate levels and forms of cognitive representation. The models will be based on evidence from the wealth of previous research into energy usage and supply issues and in particular from recent examples of small scale deployment of the technologies and mechanisms identified as key to the evolution of the smart grid as a complex adaptive system.