Optimal Grid Management for Large-Scale Sustainable Coordination

大规模可持续协调的优化网格管理

• 批准号: RGPIN-2018-05650
• 负责人: Srikantha, Pirathayini
• 金额: $ 2.04万
• 依托单位: York University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=713762
• 关键词: Optimal; Grid; Management; Large; Scale

Recent changes in climate patterns are causes for great consternation as the ensuing environmental consequences are devastating and costly. Climate change related costs are projected to increase up to $43 billion every year in Canada by 2050. In light of these repercussions, many nations (including Canada) have pledged to actively limit the impact of climate change while increasing resilience to related adverse risks in the Paris Climate Accord established in 2016. One vital component of this initiative is the promotion of clean energy production and consumption. Mechanisms actively engaged today for reducing greenhouse emissions and carbon footprint are predominantly based on monetary incentives. For example, carbon pricing penalizes generation sources with high carbon emissions and time-of-use pricing assigns fixed prices for electricity consumption over specific blocks of time periods over a day via smart meters. As these do not reflect actual costs and congestions incurred for generation, transmission and distribution; inefficiencies are inevitable. Active mechanisms that optimally coordinate actuating power components in real-time to promote grid sustainability are still not yet a reality due to the intractability caused by the presence of large number of control variables, highly fluctuating non-linear constraints and complex dynamics modelling underlying physical interdependencies. The proposed research program aims to tap onto the ubiquitous cyber-physical capability present in the modern smart grid to construct a more adaptive and unified grid management framework consisting of three specific objectives: 1) contextual grid monitoring; 2) large-scale coordination of actuating power components residing at the transmission, distribution and microgrid levels; and 3) active planning for increasing system resilience to constantly occurring changes. To achieve these goals, the inherent separability and decomposable structure of optimization and control formulations in the grid will be capitalized to construct adaptive monitoring, control and planning algorithms at various degrees of granularity. Recent advances in large-scale optimization, distributed game theory and social learning analysis will be leveraged to design information exchanges and strategic local decision-making for large populations of power entities to enhance the efficiency and sustainability in power grid operations. This proposal is in line with the climate change initiative taken at the federal level by the government of Canada via the Pan-Canadian Framework on Clean Growth and Climate Change. Core goals of this initiative include supporting sustainable technology and incorporating resilience to adverse effects of climate change. These are also key elements of the proposed research program contributing to the efforts of securing a safe and sustainable planet for future generations.

最近气候模式的变化是引起巨大恐慌的原因，因为随之而来的环境后果是毁灭性的和代价高昂的。预计到2050年，加拿大与气候变化相关的成本每年将增加高达430亿美元。鉴于这些影响，许多国家(包括加拿大)承诺在2016年制定的《巴黎气候协议》中积极限制气候变化的影响，同时提高对相关不利风险的抵御能力。这一倡议的一个重要组成部分是促进清洁能源的生产和消费。 当今积极参与的减少温室气体排放和碳足迹的机制主要是基于货币激励。例如，碳定价惩罚碳排放高的发电源，分时电价通过智能电表在特定时段内为一天的电力消耗指定固定价格。由于这些指标没有反映发电、输电和配电的实际成本和拥堵情况，因此效率低下在所难免。由于大量控制变量的存在、高度波动的非线性约束以及物理上相互依赖的复杂动力学建模造成的困难，实时以最佳方式协调驱动功率组件以促进电网可持续发展的主动机制仍未成为现实。 该研究计划旨在利用现代智能电网中普遍存在的网络物理能力来构建一个更适应和统一的电网管理框架，该框架由三个具体目标组成：1)上下文电网监控；2)大规模协调位于输电、配电和微电网级别的执行功率组件；以及3)主动规划以提高系统对不断发生的变化的弹性。为了实现这些目标，网格中优化和控制公式固有的可分离性和可分解结构将被利用，以构建不同粒度的自适应监测、控制和规划算法。将利用大规模优化、分布式博弈论和社会学习分析的最新进展，为大量电力实体设计信息交换和战略性地方决策，以提高电网运营的效率和可持续性。 这一提议与加拿大政府通过《泛加拿大清洁增长和气候变化框架》在联邦一级采取的气候变化倡议是一致的。该倡议的核心目标包括支持可持续技术和纳入应对气候变化不利影响的复原力。这些也是拟议的研究计划的关键要素，有助于为子孙后代确保一个安全和可持续的地球。