scholarly journals Hydrothermal Unit-Commitment Problem of a Large-Scale System with Representation of Forbidden Zones

Energies ◽  
2021 ◽  
Vol 15 (1) ◽  
pp. 39
Author(s):  
Bruno Colonetti ◽  
Erlon Finardi ◽  
Lucas Borges Picarelli
Keyword(s):  
Power Systems ◽  
Large Scale ◽  
Unit Commitment ◽  
Electrical Networks ◽  
Unit Commitment Problem ◽  
Large Scale System ◽  
Marginal Costs ◽  
Commitment Problem ◽  
Electrical Components ◽  
The Impact

As we move towards electrical networks with a growing presence of renewable generation, the representation of the electrical components becomes more important. In hydro-dominated power systems, modelling the forbidden zones of hydro plants becomes increasingly challenging as the number of plants increases. Such zones are ranges of generation that either should be avoided or are altogether unreachable. However, because representing the forbidden zones introduces a substantial computational burden, hydrothermal unit-commitment problems (HTUC) for large systems are usually formulated ignoring the forbidden zones. Nonetheless, this simplification may demand adjustments to the solution of the HTUC, because the generation of the hydro stations may fall in forbidden zones. In practice, the adjustments are usually performed based on the experience of system operators and, then, can be far from an optimal correction. In this paper, we study the impact of explicitly representing the hydro-generation forbidden zones in a large-scale system with more than 7000 buses, 10,000 lines, and 700 hydro units. Our findings show that the simplified model that is current used can deviate significantly from the model with forbidden zones, both in terms of the generation of hydro plants, as well as the generation of thermal plants and the system marginal costs.

A MIQCP formulation to solve the unit commitment problem for large-scale power systems

2012 ◽  
Vol 36 (1) ◽  
pp. 68-75 ◽  
Author(s):  
Juan Álvarez López ◽  
José L. Ceciliano-Meza ◽  
Isaías Guillén Moya ◽  
Rolando Nieva Gómez
Keyword(s):  
Power Systems ◽  
Large Scale ◽  
Unit Commitment ◽  
Unit Commitment Problem ◽  
Commitment Problem

scholarly journals Fat Tail Model for Simulating Test Systems in Multiperiod Unit Commitment

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
J. A. Marmolejo ◽  
R. Rodriguez
Keyword(s):  
Power Systems ◽  
Unit Commitment ◽  
Electrical Power ◽  
Random Variables ◽  
Production Costs ◽  
Unit Commitment Problem ◽  
Test Systems ◽  
Fat Tail ◽  
Commitment Problem ◽  
Stable Random Variables

This paper describes the use of Chambers-Mallows-Stuck method for simulating stable random variables in the generation of test systems for economic analysis in power systems. A study that focused on generating test electrical systems through fat tail model for unit commitment problem in electrical power systems is presented. Usually, the instances of test systems in Unit Commitment are generated using normal distribution, but in this work, simulations data are based on a new method. For simulating, we used three original systems to obtain the demand behavior and thermal production costs. The estimation of stable parameters for the simulation of stable random variables was based on three generally accepted methods: (a) regression, (b) quantiles, and (c) maximum likelihood, choosing one that has the best fit of the tails of the distribution. Numerical results illustrate the applicability of the proposed method by solving several unit commitment problems.

Absolutely Stochastic Simulated Annealing Approach to Large Scale Unit Commitment Problem

2006 ◽  
Vol 34 (6) ◽  
pp. 619-637 ◽  
Author(s):  
Tomonobu Senjyu ◽  
Ahmed Yousuf Saber ◽  
Tsukasa Miyagi ◽  
Naomitsu Urasaki ◽  
Toshihisa Funabashi
Keyword(s):  
Simulated Annealing ◽  
Large Scale ◽  
Unit Commitment ◽  
Unit Commitment Problem ◽  
Scale Unit ◽  
Commitment Problem

scholarly journals A New Solution to Profit Based Unit Commitment Problem Considering PEVs/BEVs and Renewable Energy Sources

2020 ◽  
Vol 184 ◽  
pp. 01070
Author(s):  
Ayani Nandi ◽  
Vikram Kumar Kamboj
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Production Cost ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Energy Sources ◽  
Unit Commitment Problem ◽  
Load Demand ◽  
Commitment Problem ◽  
The Impact

Daily load demand for industrial, residential and commercial sectors are changing day by day. Also, inclusion of e-mobility has totally effected the operations of realistic power sector. Hence, to meet this time varying load demand with minimum production cost is very challenging. The proposed research work focuses on the mathematical formulation of profit based unit commitment problem of realistic power system considering the impact of battery electric vehicles, hybrid electric vehicles and plug in electric vehicles and its solution using Intensify Harris Hawks Optimizer (IHHO). The coordination of plants with each other is named as Unit commitment of plants in which the most economical patterns of the generating station is taken so as to gain low production cost with higher reliability. But with the increase in industrialization has affected the environment badly so to maintain the balance between the generation and environment a new thinking of generating low cost power with high reliability by causing less harm to environment i.e. less emission of flue gases is adopted by considering renewable energy sources.

scholarly journals A Novel Strategy to Reduce Computational Burden of the Stochastic Security Constrained Unit Commitment Problem

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3777
Author(s):  
Cristian Camilo Marín-Cano ◽  
Juan Esteban Sierra-Aguilar ◽  
Jesús M. López-Lezama ◽  
Álvaro Jaramillo-Duque ◽  
Juan G. Villegas
Keyword(s):  
Decision Making ◽  
Power Systems ◽  
Large Scale ◽  
Unit Commitment ◽  
Reaction Times ◽  
Mixed Integer ◽  
Feasible Region ◽  
Solution Strategy ◽  
Unit Commitment Problem ◽  
Joint Strategy

The uncertainty related to the massive integration of intermittent energy sources (e.g., wind and solar generation) is one of the biggest challenges for the economic, safe and reliable operation of current power systems. One way to tackle this challenge is through a stochastic security constraint unit commitment (SSCUC) model. However, the SSCUC is a mixed-integer linear programming problem with high computational and dimensional complexity in large-scale power systems. This feature hinders the reaction times required for decision making to ensure a proper operation of the system. As an alternative, this paper presents a joint strategy to efficiently solve a SSCUC model. The solution strategy combines the use of linear sensitivity factors (LSF) to compute power flows in a quick and reliable way and a method, which dynamically identifies and adds as user cuts those active security constraints N − 1 that establish the feasible region of the model. These two components are embedded within a progressive hedging algorithm (PHA), which breaks down the SSCUC problem into computationally more tractable subproblems by relaxing the coupling constraints between scenarios. The numerical results on the IEEE RTS-96 system show that the proposed strategy provides high quality solutions, up to 50 times faster compared to the extensive formulation (EF) of the SSCUC. Additionally, the solution strategy identifies the most affected (overloaded) lines before contingencies, as well as the most critical contingencies in the system. Two metrics that provide valuable information for decision making during transmission system expansion are studied.

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