Unit commitment problem: Difference between revisions
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==Applications== | ==Applications== | ||
Unit commitment problems can be further adjusted for components that reflect the real-world problem. A simple categorization can be divided into two major groups. One is related to the commitment of power generation/production/manufacturing process, and the other group involves output allocation to the problem, often known as unit commitment and economic dispatch <ref>A.J. Conejo, L. Baringo, “Power System Operations,” Power Electronics and Power | Unit commitment problems can be further adjusted for components that reflect the real-world problem. A simple categorization can be divided into two major groups. One is related to the commitment of power generation/production/manufacturing process, and the other group involves output allocation to the problem, often known as unit commitment and economic dispatch <ref>A.J. Conejo, L. Baringo, “Power System Operations,” Power Electronics and Power | ||
Systems, p. 197-232, 2018, doi: 10.1007 | Systems, p. 197-232, 2018, doi:https://link.springer.com/chapter/10.1007%2F978-3-319-69407-8_7 </ref>. | ||
===Unit commitment: Single period=== | ===Unit commitment: Single period=== | ||
Revision as of 20:32, 27 November 2021
Authors: Fah Kumdokrub, Malcolm Hegeman, Kapil Khanal (SYSEN 6800 Fall 2021)
Introduction
Theory, methodology, and/or algorithmic discussions
Numerical example
Applications
Unit commitment problems can be further adjusted for components that reflect the real-world problem. A simple categorization can be divided into two major groups. One is related to the commitment of power generation/production/manufacturing process, and the other group involves output allocation to the problem, often known as unit commitment and economic dispatch [1].
Unit commitment: Single period
This type of problem usually optimizes the number of power generators for each facility/plant to meet the demand in a specific period. Although this might not be the case study in real-world scenarios, starting off with this type of unit commitment optimization problem might help check the correctness of other constraints before adding the complexity of time and other power generating units’ components.
Unit commitment: Multi-period
Many times, the production of power should be planned in advance. This planned period could be for months, weeks, or even overnight to avoid under or overly-generating power and minimize the total number of generators needed. And these problems would require a multi-period unit commitment optimization.
Unit commitment: Additional constraints
There are many more criteria that can be added to the unit commitment problem to truly reflect the system. Some scenarios may be required reserve constraints to ensure sufficient supply in response to a spike in demand [2]. Ramping constraints can also be added since the generators take time to start and stop the process which both affect the cost and amount of power output [2]. Types of power affect the optimization whether they come from a single source or multiple sources [2] [3].
Unit commitment and Economic dispatch
With any attributes to the unit commitment problem, the economic aspects are always involved meaning that the allocation of power generation (energy output) for each committing unit must be economical with all the costs and revenues. Power generator plants not only need to meet the demand, but they also need to operate in the most economical ways, at the lowest possible cost or the highest possible profit. There are many costs involved in generating power, for example, the cost per unit of power generations, the cost of shutting down or starting up the generator, the cost of over generating power since it may cause damage to the plant, and there are many other costs and benefits that could be considered to the problem.
Commercialized unit commitment software is also available for use. For example, Power Optimisation company developed a software named POWEROP which is more generalized to wide ranges of users or power companies, customized software for Northern Ireland Electricity (NIE), and software developed specifically for the British Electricity Trading and Transmission Arrangements (BETTA) [3]. Software for NIE considers power from multiple sources, including gas, coal, and oil-fired steam [2]. Additionally, software for BETTA can generate electricity prices for both the general market and individuals by contract [3]. The software was developed from a multi-stage mixed-integer linear programming (MILP) and adapted the constraints to serve customers’ specific requirements [3].
Conclusion
References
- ↑ A.J. Conejo, L. Baringo, “Power System Operations,” Power Electronics and Power Systems, p. 197-232, 2018, doi:https://link.springer.com/chapter/10.1007%2F978-3-319-69407-8_7
- ↑ 2.0 2.1 2.2 2.3 L.A. Wolsey, Integer Programming. Wiley, 1998.
- ↑ 3.0 3.1 3.2 3.3 “Unit Commitment and Economic Dispatch Software to Optimise the Short-Term Scheduling of Electrical Power Generation” https://msi-jp.com/xpress/learning/square/unit_en.pdf (accessed Nov. 13, 2021).