A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Decomposed Modeling of Controllable and Uncontrollable Components in Power Systems with High Penetration of Renewable Energies
The high penetration of variable renewable energies requires the flexibility from both the generation and demand sides. This raises the necessity of modeling stochastic and flexible energy resources in power system operation. However, some distributed energy resources have both stochasticity and flexibility, e.g., prosumers with distributed photovoltaics and energy storage, and plug-in electric vehicles with stochastic charging behavior and demand response capability. Such partly controllable participants pose challenges to modeling the aggregate behavior of large numbers of entities in power system operation. This paper proposes a new perspective on the aggregate modeling of such energy resources in power system operation. Specifically, a unified controllability-uncontrollability-decomposed model for various energy resources is established by modeling the controllable and uncontrollable parts of energy resources separately. Such decomposition enables the straightforward aggregate modeling of massive energy resources with different controllabilities by integrating their controllable components with linking constraints and uncontrollable components with dependent discrete convolution. Furthermore, a two-stage stochastic unit commitment model based on the proposed model for power system operation is established. The proposed model is tested using a three-bus system and real Qinghai provincial power grid of China. The result shows that this model is able to characterize at high accuracy the aggregate behavior of massive energy resources with different levels of controllability so that their flexibility can be fully explored.
Decomposed Modeling of Controllable and Uncontrollable Components in Power Systems with High Penetration of Renewable Energies
The high penetration of variable renewable energies requires the flexibility from both the generation and demand sides. This raises the necessity of modeling stochastic and flexible energy resources in power system operation. However, some distributed energy resources have both stochasticity and flexibility, e.g., prosumers with distributed photovoltaics and energy storage, and plug-in electric vehicles with stochastic charging behavior and demand response capability. Such partly controllable participants pose challenges to modeling the aggregate behavior of large numbers of entities in power system operation. This paper proposes a new perspective on the aggregate modeling of such energy resources in power system operation. Specifically, a unified controllability-uncontrollability-decomposed model for various energy resources is established by modeling the controllable and uncontrollable parts of energy resources separately. Such decomposition enables the straightforward aggregate modeling of massive energy resources with different controllabilities by integrating their controllable components with linking constraints and uncontrollable components with dependent discrete convolution. Furthermore, a two-stage stochastic unit commitment model based on the proposed model for power system operation is established. The proposed model is tested using a three-bus system and real Qinghai provincial power grid of China. The result shows that this model is able to characterize at high accuracy the aggregate behavior of massive energy resources with different levels of controllability so that their flexibility can be fully explored.
Decomposed Modeling of Controllable and Uncontrollable Components in Power Systems with High Penetration of Renewable Energies
Hai Li (author) / Ning Zhang (author) / Yue Fan (author) / Ling Dong (author) / Pengcheng Cai (author)
2022
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Perception of repeated pain relief with controllable and uncontrollable pain
| BASE | 2021
| British Library Conference Proceedings | 1992