EAGER: Renewables: Market Mechanism for Managing Uncertainties Caused by High Levels of Renewable Generation
EAGER:可再生能源:管理高水平可再生能源发电引起的不确定性的市场机制
基本信息
- 批准号:1549937
- 负责人:
- 金额:$ 30万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-09-15 至 2018-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Renewable energy resources in electric power grids are inherently variable, and the ability to predict the variation in generated power is quite limited. This variability raises issues regarding proper pricing mechanisms for electric power in systems with high levels of renewable generation. The research objective of this project is to explore a new fundamental market-based mechanism for managing the uncertainty caused by high levels of renewable generation or renewable energy sources (RES). The key concept of the proposed mechanism is to charge uncertain sources and credit flexible sources based on Uncertainty Marginal Price (UMP), which represents the marginal cost of immunizing the next increment of uncertainty at a specific location. Management of uncertainty is one of the key issues that must be dealt with to have seamless high-level penetration of RES. The clear price signals and incentives developed in this project have the potential to remove a critical barrier to distributed RES, which in turn will promote energy independence and reduce environmental impact, contributing to the goal of a low-carbon economy. The proposed UMP concept enriches the fundamentals of electricity market theory and opens a new door for future research.This research project will, for the first time, provide explicit price signals and utilize a market mechanism to manage any level of uncertainty using a robust optimization framework. In comparison, the traditional reserve approach is based on experience and heuristics that cannot work under the high renewables scenario. The research project aims to manage uncertainty both at the source side (uncertainty reduction) and the resource side (uncertainty accommodation). UMP provides important price signals for both themarket operation and investment related to uncertainty and flexibility. In the short term, the proposed market-based mechanism provides incentives for RES operators to improve forecasting accuracy (i.e., to reduce uncertainties). It also provides incentives for existing flexible resources (e.g., gas-fired generating units) to contribute reserves for uncertainty accommodation. In the long term, the proposed mechanism provides price signals for siting new flexible resources (e.g., energy storage) to accommodate uncertainties from increasing RES penetration.
电网中的可再生能源资源具有固有的可变性,预测发电量变化的能力非常有限。这种可变性提出了在可再生能源发电量高的系统中建立适当的电力定价机制的问题。 该项目的研究目标是探索一种新的基本市场机制,以管理高水平的可再生发电或可再生能源(RES)所造成的不确定性。该机制的核心概念是根据不确定性边际价格(UMP)对不确定性来源和信贷灵活来源进行收费,UMP代表了在特定位置免疫下一个不确定性增量的边际成本。管理不确定性是必须处理的关键问题之一,以实现可再生能源的无缝高水平渗透。该项目中开发的明确价格信号和激励措施有可能消除分布式可再生能源的关键障碍,这反过来将促进能源独立并减少对环境的影响,有助于实现低碳经济的目标。UMP概念的提出丰富了电力市场理论的基础,并为未来的研究打开了一扇新的大门。该研究项目将首次提供明确的价格信号,并利用市场机制来管理任何程度的不确定性,使用一个强大的优化框架。相比之下,传统的储备方法是基于经验和经验,不能在高可再生能源情景下工作。该研究项目的目的是管理不确定性的来源方(减少不确定性)和资源方(不确定性调节)。UMP为市场运作和投资提供了重要的价格信号,这与不确定性和灵活性有关。在短期内,拟议的市场机制为RES运营商提供了提高预测准确性的激励措施(即,减少不确定性)。它还为现有的灵活资源提供激励措施(例如,燃气发电机组)为不确定性应对提供储备。从长远来看,拟议的机制为新的灵活资源的选址提供了价格信号(例如,能源储存),以适应日益增加的可再生能源渗透的不确定性。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Zuyi Li其他文献
A compensation scheme for CVT transient effects using artificial neural network
- DOI:
10.1016/j.epsr.2006.12.006 - 发表时间:
2008-01-01 - 期刊:
- 影响因子:
- 作者:
Hassan Khorashadi Zadeh;Zuyi Li - 通讯作者:
Zuyi Li
State identification of home appliance with transient features in residential buildings
- DOI:
10.1007/s11708-022-0822-z - 发表时间:
2022-03-10 - 期刊:
- 影响因子:6.200
- 作者:
Lei Yan;Runnan Xu;Mehrdad Sheikholeslami;Yang Li;Zuyi Li - 通讯作者:
Zuyi Li
Transient Characteristics of Synchronverters Subjected to Asymmetric Faults
同步逆变器遭受不对称故障时的暂态特性
- DOI:
10.1109/tpwrd.2019.2906766 - 发表时间:
2019 - 期刊:
- 影响因子:4.4
- 作者:
Lili He;Zhikang Shuai;Xin Zhang;Xuan Liu;Zuyi Li;Z. Shen - 通讯作者:
Z. Shen
Integrated planning of BEV public fast-charging stations
- DOI:
10.1016/j.tej.2016.11.010 - 发表时间:
2016-12-01 - 期刊:
- 影响因子:
- 作者:
Lin Gong;Yong Fu;Zuyi Li - 通讯作者:
Zuyi Li
Challenges for real-world applications of nonintrusive load monitoring and opportunities for machine learning approaches
非侵入式负载监控的实际应用面临的挑战和机器学习方法的机遇
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Lei Yan;Mehrdad Sheikholeslami;Wenlong Gong;Wei Tian;Zuyi Li - 通讯作者:
Zuyi Li
Zuyi Li的其他文献
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{{ truncateString('Zuyi Li', 18)}}的其他基金
Collaborative Research: Stochastic Optimization and Coordination Control of Demand Response for Enhancing the Secure and Economic Operation of Power Systems
协作研究:需求响应随机优化与协调控制,增强电力系统安全经济运行
- 批准号:
1102136 - 财政年份:2011
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
Coordination of Renewable Hydro-Wind Units for Enhancing the Hydrothermal Power System Operation
协调可再生水力风电机组以增强水热发电系统的运行
- 批准号:
0801853 - 财政年份:2008
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
GOALI: Security-Constrained Optimal Coordination of Generation and Transmission Maintenance Outage Scheduling
GOALI:发电和输电维护停电调度的安全约束最优协调
- 批准号:
0725666 - 财政年份:2007
- 资助金额:
$ 30万 - 项目类别:
Standard Grant
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