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Hydrothermal Generation Scheduling Research

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "J: Thermal Management".

Deadline for manuscript submissions: closed (31 May 2022) | Viewed by 1425

Special Issue Editor


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Guest Editor
Department of Electrical and Electronic Engineering, Federal University of Santa Catarina/LabPlan, Florianópolis 88040-900, Brazil
Interests: power system planning and economics; real-time hydro dispatch; applied optimization

Special Issue Information

Dear Colleagues,

Hydrothermal power generation scheduling is a crucial problem that assesses the system operation in the future to pursue the trade-off between economical and reliable power generation resources. Consequently, the scheduling model results in a mathematical representation of the system components (reservoirs, plants, transmission lines) and a forecast of the operational conditions (weather, equipment failures, water inflow, demand, prices).

Different optimization models (long-term, medium-term, and unit commitment) usually solve the hydrothermal generation scheduling problem since power systems have different configurations, complexities, and sizes. Furthermore, systems are operated in different market contexts: in a decentralized market, different stakeholders possess distinct objectives, leading to different modeling approaches; in a cost-based market, a single entity is responsible for centrally scheduling and dispatching generating units. Technological changes, constant insertion of interminable power generation, and climate change are a small sample of the challenges demanded by generation scheduling models. In contrast, with robust developments in data analysis and optimization models, the high computational capacity has allowed innovative modeling and solution strategies and approaches.

To summarize, in this Special Issue, we invite authors to submit papers from the full value chain of hydrothermal power generation scheduling, including, but not limited to, modeling issues and solution strategies related to long- and medium-term generation scheduling problems, unit commitment, economic dispatch, market models, financial products in hydro-dominated markets, integration of intermittent resources, real-time scheduling and dispatch, and planning and maintenance of generation resources. Tutorial and survey papers are also welcome.

We are looking forward to receiving your outstanding research.

Prof. Dr. Erlon Cristian Finardi
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • long-term generation scheduling problem
  • medium-term generation scheduling problem
  • hydrothermal unit commitment
  • economic dispatch
  • market models
  • financial products in hydro-dominated markets
  • integration of intermittent resources
  • real-time scheduling and dispatch
  • planning and maintenance of generation resources.

Published Papers (1 paper)

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Research

23 pages, 2729 KiB  
Article
Continuous Piecewise Linear Approximation of Plant-Based Hydro Production Function for Generation Scheduling Problems
by David Lucas dos Santos Abreu and Erlon Cristian Finardi
Energies 2022, 15(5), 1699; https://doi.org/10.3390/en15051699 - 24 Feb 2022
Cited by 4 | Viewed by 1205
Abstract
An essential challenge in generation scheduling (GS) problems of hydrothermal power systems is the inclusion of adequate modeling of the hydroelectric production function (HPF). The HPF is a nonlinear and nonconvex function that depends on the head and turbined outflow. Although the hydropower [...] Read more.
An essential challenge in generation scheduling (GS) problems of hydrothermal power systems is the inclusion of adequate modeling of the hydroelectric production function (HPF). The HPF is a nonlinear and nonconvex function that depends on the head and turbined outflow. Although the hydropower plants have multiple generating units (GUs), due to a series of complexities, the most attractive modeling practice is to represent one HPF per plant, i.e., a single function is built for representing the plant generation instead of the generation of each GU. Furthermore, due to the computation time constraints and representation of nonlinearities, the HPF must be given by a piecewise linear (PWL) model. This paper presented some continuous PWL models to include the HPF per plant in GS problems of hydrothermal systems. Depending on the type of application, the framework allows a choice between the concave PWL for HPF modeled with one or two variables and the nonconvex (more accurate) PWL for HPF dependent only on the turbined outflow. Basically, in both PWL models, offline, mixed-integer linear (or quadratic) programming techniques are used with an optimized pre-selection of the original HPF dataset obtained through the Ramer-Douglas-Peucker algorithm. As a highlight, the framework allows the control of the number of hyperplanes and, consequently, the number of variables and constraints of the PWL model. To this end, we offer two possibilities: (i) minimizing the error for a fixed number of hyperplanes, or (ii) minimizing the number of hyperplanes for a given error. We assessed the performance of the proposed framework using data from two large hydropower plants of the Brazilian system. The first has 3568 MW distributed in 50 Bulb-type GUs and operates as a run-of-river hydro plant. In turn, the second, which can vary the reservoir volume by up to 1000 hm3, possesses 1140 MW distributed in three Francis-type units. The results showed a variation from 0.040% to 1.583% in terms of mean absolute error and 0.306% to 6.356% regarding the maximum absolute error even with few approximations. Full article
(This article belongs to the Special Issue Hydrothermal Generation Scheduling Research)
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