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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=682665
• 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引起了极大的恐慌，因为随之而来的环境后果是毁灭性的，代价高昂。预计到2050年，加拿大每年与气候变化相关的成本将增加到430亿美元。鉴于这些影响，许多国家（包括加拿大）在2016年签署的《巴黎气候协定》中承诺积极限制气候变化的影响，同时提高应对相关不利风险的能力。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。******目前积极参与的减少温室气体排放和碳足迹的机制主要基于货币激励。例如，碳定价对高碳排放的发电源进行惩罚，而分时电价通过智能电表为一天中特定时间段的电力消耗分配固定价格。由于这些没有反映发电、输电和配电的实际成本和拥堵；效率低下是不可避免的。由于存在大量控制变量、高度波动的非线性约束和物理相互依赖的复杂动力学建模，因此，实时优化协调驱动电源组件以促进电网可持续性的主动机制仍未成为现实。******提出的研究计划旨在利用现代智能电网中无处不在的网络物理能力，构建一个更具适应性和统一的电网管理框架，包括三个具体目标：1)上下文网格监测；2)输配电及微网级作动功率元件的大规模协同；3)积极规划增加系统对不断发生的变化的弹性。为了实现这些目标，将利用网格中优化和控制公式固有的可分离性和可分解结构，构建不同粒度度的自适应监测、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方面的最新进展，为大量电力实体设计信息交换和战略性本地决策，以提高电网运行的效率和可持续性。******该提案符合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。该倡议的核心目标包括支持可持续技术，并纳入应对气候变化不利影响的能力。这些也是拟议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。