Load demand management with high renewable energy penetration in distribution systems
Load demand management with high renewable energy penetration in distribution systems
批准号:
RGPIN-2016-04580
负责人:
Chandra, Ambrish
金额:
$2.99万
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
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31
中文摘要
分布式可再生资源(DRR)在根本上不同于传统和化石燃料资源。它们的来源(特别是风速和太阳辐射)无法控制或储存。此外,由于其高不稳定性,可再生发电通常不与真实的消费者负载需求相关。它可能导致电力系统不稳定的主要原因之一。考虑到这些DRR(50-60%)在未来电网中的渗透率增加,即使是传统发电厂也难以有效地参与维持网络稳定性。在这种具有高DRR渗透率的改造后的电网结构中,瞬时预测和控制整个电网的总发电量将成为一项真实的具有挑战性的任务。电网的运行将更有意识地根据DRR的产生而不是消费者的负荷需求来管理。可能出现的主要问题是增加电压畸变方面的闪变,凹陷,膨胀和谐波含量,频率控制等,为了解决这些问题,在文献中提出的解决方案,如增加额定值的备用DG单元和采用存储系统,以保持赤字真实的时间负载需求。
需求侧管理是缓解电力系统中DRR不稳定性的替代解决方案。控制负载电力消耗,使得负载需求跟随发电。负荷需求管理方法分为负荷调度,使用储能系统(ESS),非关键负荷的直接开关控制等,但这些方法中的大多数是适合于在小时的时间范围内的负荷管理。他们不工作在真实的时间,除非与ESS的使用。最近,电弹簧(ES)的概念已被提出作为一个智能负载的需求管理在真实的时间。然而,它的设计,有效的控制和它的价值下的风能和太阳能光伏发电与配电系统的高渗透方面的分析还不是很多。此外,在不久的将来,预计运输部门的能源需求将迅速增加,以供应插电式电动汽车(PEV)。这些PEV的充电站可以用作灵活的负载以稳定电网。
鉴于这些挑战,迫切需要对配电系统技术进行详细调查,以减轻DRR的不确定性。拟议研究项目的主要目标如下,
设计、建模、控制、实施和性能评估智能负载的选定拓扑结构,以实现损耗最小化、技术简化、在DRR渗透率增加的情况下减小尺寸。
设计、建模和控制用于在DRR渗透增加的情况下调度PEV停车站,以提高电网稳定性和客户满意度。
英文摘要
Distributed Renewable Resources (DRRs) differ from conventional and fossil-fired resources in a fundamental way. Their sources (wind velocity and solar radiation in particular) cannot be controlled or stored. Further, renewable power generation often does not correlate with consumer load demand in real time due to its high intermittency. It may lead to one of the main causes of destabilizing the power system. In light of increased penetrations of these DRRs (50-60%) with the future grid, it will be difficult even for conventional power plants to participate effectively with great impact in maintaining stability of the network. In such reformed grid structure with high DRRs penetration, it will become a real challenging task to instantaneously predict and control total power generation in the entire grid. The operation of power grid will be more deliberately governed on the basis of DRRs generation rather than consumer loads demand. The main problems which may arise are increased voltage distortions in terms of flicker, sag, swell and its harmonic contents, frequency control etc. To solve such problems, solutions are presented in literature, such as, increased rating of a stand-by DG unit and employing storage system for maintaining deficit real time load demands.
The demand side management is alternative solution for mitigating intermittency of the DRRs in the power system. The load power consumption is controlled such that load demand follow power generation. Load demand management methods are classified as load scheduling, use of energy storage systems (ESS), direct on-off control of non-critical loads etc. However most of these methods are suitable for load management in time frame of hours. They do not work in real time, except with the use of ESS. Recently, electric spring (ES) concept has been proposed as a smart load for demand management in real time. However, it has not been analyzed very much in terms of its design, efficient control and its worthiness under high penetration of wind and solar PV generation with distribution systems. Moreover, in near future, energy demand is expected to increase rapidly in the sector of transportation to supply plug-in electrical vehicles (PEVs). These charging stations of PEVs may be used as flexible loads to stabilize the grid.
In view of these challenges, there is an immediate requirement for detailed investigation for technologies with distribution system to mitigate intermittency of DRRs. The main objectives of the proposed research project are as follows,
Design, modeling, control, implementation and performance evaluation of selected topologies of smart loads to achieve loss minimization, technical upgradation, size reduction under increased penetrations of DRRs.
Design, modeling and control for scheduling the dispatch of parking stations for PEVs under increased penetrations of DRRs to improve grid stability and customer satisfaction.
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