Forecasting tools for micro-grid applications

通用电气(GE)在加拿大的数字能源Multilin，在这里被称为GE，已经与卡尔加里大学合作开发合作研究和开发(CRD)计划。该项目将专注于GE的电网IQ微电网控制系统平台的价格和负荷预测技术。该平台由加拿大开发，是第一个进入世界市场的工业微电网控制器。CRD项目的研究问题是如何开发微电网优化运行所需的预测模块。更具体地说，这项建议的首要任务是开发和实施一种能够无缝适应不同市场结构的价格预测机制。这是为了确保在不同司法管辖区安装该平台时，只需进行最小程度的调整，即可生成相关的电力市场价格预测。本研究的第二个任务是建立确定性和概率性的微电网负荷预测模型，该模型对微电网负荷的高波动性具有较强的鲁棒性。负荷预测模型的设计将考虑到微电网负荷构成的具体特点。最后，本研究的第三个任务是研究预测误差如何影响微电网的整体经济效益，以及如何调整预测模型以缓解与预测误差相关的任何经济缺陷。该计划将在几个方面使加拿大受益，包括(I)从改进的加拿大技术中创造经济机会；(Ii)通过改进工业微电网控制平台，促进更多可再生资源的整合；以及(Iii)通过改进平台来节省资金和避免排放，该平台是偏远、离网社区微电网优化的重要组成部分。

General Electric (GE) Digital Energy Multilin in Canada, referred to as GE here onward, has partnered with the University of Calgary to develop a Collaborative Research and Development (CRD) program. The program will be focused on price and load forecasting technologies for GE's Grid IQ Micro-grid Control System platform. The platform, developed in Canada, is the first industrial micro-grid controller to enter the world market. The research problem in the CRD program is how to develop forecasting modules required for optimal operation of micro-grids. More specifically, the first task in this proposal is to develop and implement a price forecasting mechanism that is seamlessly adaptable to different market structures. This is to ensure that when installing the platform in different jurisdictions, minimal adjustments are necessary to generate relevant electricity market price forecasts. The second task in this research is to build deterministic and probabilistic micro-grid load forecasting models that are robust against the high volatility of micro-grid loads. The load forecasting models will be designed such that they take into account the specific characteristics of micro-grid load composition. Finally, the third task in this research is to investigate how forecast errors may impact the overall economic efficiency of micro-grids, and how the forecasting models could be adjusted to mitigate any economic deficiency associated with forecast errors. This program will benefit Canada in several ways, including (i) creating economic opportunities from an improved Canadian technology, (ii) facilitating the integration of more renewable resources by improving an industrial micro-grid control platform, and (iii) saving money and avoiding emissions by improving a platform that is an essential part of micro-grid optimization in remote, off-grid communities.