Multistage Robust Look-Ahead Unit Commitment with Probabilistic Forecasting in Multi-Carrier Energy Systems

2021 ◽  
Vol 12 (1) ◽  
pp. 70-82 ◽  
Author(s):  
Yizhou Zhou ◽  
Mohammad Shahidehpour ◽  
Zhinong Wei ◽  
Guoqiang Sun ◽  
Sheng Chen
2017 ◽  
Author(s):  
Miguel F. Anjos ◽  
Antionio J. Conejo

Author(s):  
Ahmad Abdallah Mohammad Aljabery ◽  
Hasan Mehrjerdi ◽  
Sajad Mahdavi ◽  
Reza Hemmati

Author(s):  
Juan Gea Bermúdez ◽  
Kaushik Das ◽  
Hardi Koduvere ◽  
Matti Juhani Koivisto

This paper proposes a mathematical model to simulate Day-ahead markets of large-scale multi-energy systems with high share of renewable energy. Furthermore, it analyses the importance of including unit commitment when performing such analysis. The results of the case study, which is performed for the North Sea region, show the influence of massive renewable penetration in the energy sector and increasing electrification of the district heating sector towards 2050, and how this impacts the role of other energy sources such as thermal and hydro. The penetration of wind and solar is likely to challenge the need for balancing in the system as well as the profitability of thermal units. The degree of influence of the unit commitment approach is found to be dependent on the configuration of the energy system. Overall, including unit commitment constraints with integer variables leads to more realistic behaviour of the units, at the cost of increasing considerably the computational time. Relaxing integer variables reduces significantly the computational time, without highly compromising the accuracy of the results. The proposed model, together with the insights from the study case, can be specially useful for system operators for optimal operational planning.


Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3388 ◽  
Author(s):  
Niina Helistö ◽  
Juha Kiviluoma ◽  
Jussi Ikäheimo ◽  
Topi Rasku ◽  
Erkka Rinne ◽  
...  

Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS). An application of the framework is demonstrated using a power system example, and Backbone is shown to produce results comparable to a commercial tool. However, the adaptability of Backbone further enables the creation and solution of energy systems models relatively easily for many different purposes and thus it improves on the available methodologies.


Author(s):  
Qianfan Wang ◽  
Xing Wang ◽  
Kwok Cheung ◽  
Yongpei Guan ◽  
Frederick S. Stu Bresler

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