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

复杂自适应系统、认知代理和分布式能源 (CASCADE)：对智能电网概念的复杂性科学调查

基本信息

批准号：
EP/G059969/1
负责人：
Richard Mark Rylatt
金额：
$ 132.81万
依托单位：
De Montfort University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2009
资助国家：
英国
起止时间：
2009 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FG059969%2F1
关键词：
Complex Adaptive Systems Cognitive Agents

项目摘要

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.

人们普遍承认，电力行业面临许多严重的挑战，包括基础设施，容量限制以及减少温室气体和其他人的需求，但许多国家的放松管制引起了更复杂的问题。这导致了一种形式的巴尔干化形式，该形式倾向于给传统电网造成额外的压力，该结构基于大规模生成工厂的集中式命令和管理，远程高压传输和局部低压分布网络。需要解决各种规模和不同级别上的许多相互关联的问题，包括需要昂贵的待机能力来满足峰值负载，高资本成本和长时间的新工厂的长时间，对各种能源安全威胁的脆弱性以及非技术安全障碍，以及对分布式能源（ders）和更高的能源服务的范围，以实现更大的能源服务。根据DESCHALIZED模型定义，基于DERS和电力存储技术的最新和预期进步，尤其是信息和通信技术方面的快速发展，这将使智能设备的广泛部署能够进行。尤其是在美国，这个新概念（称为智能电网）吸引了大规模的投资和政策认可，一些评论员将其发展与互联网的发展进行了比较，并以可能代表电力行业及其最终用户的类似种类范式转移的规模进行预测。如果确实发生了这一点，那么中央主义理论，法律和技术将在某个时候就不再有效作为控制手段。以及作为业务的新范式，互联网被认为是复杂性理论的范式，并且与智能电网概念相似，这表明了这种新科学的合适性，表明了这种新科学的合适性，以使其充满清醒和回应挑战。电力行业的现有结构和组织为对所设想进化的基础机制的有意义的研究提供了重要的起点和背景，这可能代表了标点平衡的示例。复杂的系统思维和建模是关于这种重大，结构性变化的发生以及系统在不同的政策和干预措施下可能进化的可能方式。这些因素结合在一起，提供了一个独特的机会，可以在自我组织的出现和复杂自适应系统的演变中获得重要的见解，这对于影响能源安全，减少碳和燃料贫困的一系列重要政策问题的相关性极高。复杂性科学既为提出的研究问题提供了协同的概念框架，并提供了一组特别适合其解决方案的工具和方法。这项研究将主要基于基于代理的建模，该建模能够模拟由许多非线性，动态，依赖历史的，多尺度相互作用与反馈效应的复杂性，这些效果将击败传统的基于方程式的和统计的建模。将开发不典型的建模和模拟的技术，以反映问题领域的特殊特征，尤其是社会经济和技术系统的紧密耦合，其中人类和人工智能的代理被建模和模拟在一起，以及需要找到适当水平和形式的认知表达的水平和形式。这些模型将基于先前对能源使用和供应问题的研究的证据，尤其是从最近的小规模部署技术和机制的示例中，被确定为智能电网作为复杂自适应系统演变的关键。