Unit Commitment and Thermal Optimization — Problem Statement

1993 ◽  
pp. 143-171
Author(s):  
H. Braun
Keyword(s):  
Optimization Problem ◽  
Unit Commitment ◽  
Problem Statement ◽  
Thermal Optimization

scholarly journals A review of optimization techniques applied to solve unit commitment problem in microgrid

2019 ◽  
Vol 15 (3) ◽  
pp. 1161
Author(s):  
Karthik N ◽  
A K Parvathy ◽  
Arul Rajagopalan ◽  
S Baskar
Keyword(s):  
Literature Review ◽  
Optimization Problem ◽  
Time Perspective ◽  
Unit Commitment ◽  
Optimization Techniques ◽  
Energy Sources ◽  
Power Demand ◽  
Unit Commitment Problem ◽  
Ecological Constraints ◽  
Commitment Problem

<p>Unit Commitment (UC) is an optimization problem used to find out the least cost dispatch of obtainable generation resources to meet up an expected electric power demand over a certain time perspective under generational, technical and ecological constraints. In the midst of the momentous increase of non-conventional energy sources incorporation into the power system networks, effects caused by these system alterations to the UC are dynamically being studied and examined by worldwide researchers. This paper presents a literature review of application of several optimization algorithms to elucidate the UC problem in microgrids. Lastly a few basic challenges arising from the new optimization approaches in microgrids are addressed.</p>

scholarly journals Identification of gas pipelines hydraulic efficiency coefficients

2019 ◽  
Vol 102 ◽  
pp. 03002
Author(s):  
Andrey A. Belevitin ◽  
Victoria G. Ryzhkova
Keyword(s):  
Nonlinear Optimization ◽  
Optimization Problem ◽  
Original Problem ◽  
Solution Procedure ◽  
Hydraulic Efficiency ◽  
Gas Pipelines ◽  
Problem Statement ◽  
Nonlinear Optimization Problem ◽  
Successive Linear Programming ◽  
The Given

This study investigates the identification of non-measureable parameters of the gas transmission system (gas pipelines hydraulic efficiency coefficients). The problem statement and solution procedure are presented. The original problem is divided into two interrelated components: the nonlinear optimization problem and the temperature calculation. The nonlinear optimization problem is solved using the Successive Linear Programming (SLP) method. The problems of insufficiency of measurements and multiplicity of solutions are described, and appropriate approaches are proposed (introduction of additional subcriteria and uniting gas pipelines into groups). Identification of gas pipelines hydraulic efficiency coefficients for gas transmission systems of various complexity has been performed using the given algorithm.

Evolutionary layout design synthesis of an autonomous greenhouse using product-related dependencies

2020 ◽  
pp. 1-16
Author(s):  
Yann-Seing Law-Kam Cio ◽  
Yuanchao Ma ◽  
Aurelian Vadean ◽  
Giovanni Beltrame ◽  
Sofiane Achiche
Keyword(s):  
Optimization Problem ◽  
Development Process ◽  
Layout Design ◽  
Product Development Process ◽  
Mechatronic System ◽  
Problem Statement ◽  
Design Synthesis ◽  
Heating Systems ◽  
Management Of Resources

Abstract The development of autonomous greenhouses has caught the interest of many researchers and industrial considering their potential of offering an optimal environment for the growth of high-quality crops with minimum resources. Since an autonomous greenhouse is a mechatronic system, the consideration of its subsystem (e.g. heating systems) and component (e.g. actuators and sensors) interactions early in the design phase can ease the product development process. Indeed, this consideration could shorten the design process, reduce the number of redesign loops, and improve the performance of the overall mechatronic system. In the case of a greenhouse, it would lead to a higher quality of the crops and a better management of resources. In this work, the layout design of a general autonomous greenhouse is translated into an optimization problem statement while considering product-related dependencies. Then, a genetic algorithm is used to carry out the optimization of the layout design. The methodology is applied to the design of a fully autonomous greenhouse (45 cm × 30 cm × 30 cm) for the growth of plants in space. Although some objectives are conflictual, the developed algorithm proposes a compromise to obtain a near-optimal feasible layout design. The algorithm was also able to optimize the volume of components (occupied space) while considering the energy consumption and the overall mass. Their respective summed values are 2844.32 cm3, which represents 7% of the total volume, 5.86 W, and 655.8 g.

scholarly journals Sobre la síntesis óptima de mecanismos

2019 ◽  
pp. 16-22
Author(s):  
Ixshel Jhoselyn Foster-Vázquez ◽  
Rogelio De Jesús Portillo-Vélez ◽  
Eduardo Vazquez-Santacruz
Keyword(s):  
Optimization Problem ◽  
Optimization Problems ◽  
Great Influence ◽  
General Rule ◽  
Linear Constraints ◽  
Synthesis Problem ◽  
Mechanism Synthesis ◽  
Problem Statement ◽  
Engineering Design Process ◽  
The Impact

In the engineering design process, it is of particular relevance the problem statement that has to be solved to guarantee an optimal design. There is no general rule for this, and in the particular case of the synthesis of flat mechanisms, the solution strongly depends on the problem statement for the design or mechanism synthesis. The object this paper is presenting one proposal at synthesis problem of a four-bar flat mechanism for cartesian trajectory tracking. The mechanism synthesis problem is stated as a nonlinear optimization problem with non linear constraints. Four different approaches are considered in order to demonstrate the impact of the considered statement of the optimization problem for its solution. The solution of the four optimization problems is obtained by means of numerical calculations using genetic algorithms. The numerical results of the four optimization problem statemens are compared under fair circumstances and they depict the great influence of the initial problem statement for its solution.

scholarly journals Network Mobility Route Optimization Problem Statement

2007 ◽  
Author(s):  
C. Ng ◽  
P. Thubert ◽  
M. Watari ◽  
F. Zhao
Keyword(s):  
Optimization Problem ◽  
Route Optimization ◽  
Network Mobility ◽  
Problem Statement

scholarly journals Artificial salmon tracking algorithm: Preliminary designing approach for optimizing the integrated mixed energy composition

2018 ◽  
Vol 204 ◽  
pp. 04002 ◽  
Author(s):  
A.N. Afandi ◽  
Irham Fadlika ◽  
Quota Alief Sias ◽  
Y. Rahmawati ◽  
D. Lestari ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Total Energy ◽  
Optimization Problem ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Tracking Algorithm ◽  
Energy Sources ◽  
Optimal Composition ◽  
Energy Mix ◽  
Technical Requirements

Recently, an energy mix providing becomes an important problem to face unsustainable energy sources fuelled by coal derivation. The optimal composition between various energy sources also leads to the generated portion of the unit commitment. By considering this issues, these works are subjected to find out the optimal scheduled production of the energy mix throughout an optimization problem considered conventional and renewable energy sources. Moreover, these studies also introduce Artificial Salmon Tracking Algorithm for carrying out the problem. By considering technical requirements, results show that the total energy mixing is produced dynamically to feed the hourly demand. The contribution of the conventional and renewable energy sources affect to discharged pollutants.

scholarly journals An Improved DA-PSO Optimization Approach for Unit Commitment Problem

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2335 ◽  
Author(s):  
Sirote Khunkitti ◽  
Neville R. Watson ◽  
Rongrit Chatthaworn ◽  
Suttichai Premrudeepreechacharn ◽  
Apirat Siritaratiwat
Keyword(s):  
Optimization Problem ◽  
Unit Commitment ◽  
Economic Dispatch ◽  
Optimization Techniques ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Sigmoid Function ◽  
Unit Commitment Problem ◽  
Commitment Problem ◽  
Metaheuristic Techniques

Solving the Unit Commitment problem is an important step in optimally dispatching the available generation and involves two stages—deciding which generators to commit, and then deciding their power output (economic dispatch). The Unit Commitment problem is a mixed-integer combinational optimization problem that traditional optimization techniques struggle to solve, and metaheuristic techniques are better suited. Dragonfly algorithm (DA) and particle swarm optimization (PSO) are two such metaheuristic techniques, and recently a hybrid (DA-PSO), to make use of the best features of both, has been proposed. The original DA-PSO optimization is unable to solve the Unit Commitment problem because this is a mixed-integer optimization problem. However, this paper proposes a new and improved DA-PSO optimization (referred to as iDA-PSO) for solving the unit commitment and economic dispatch problems. The iDA-PSO employs a sigmoid function to find the optimal on/off status of units, which is the mixed-integer part of obtaining the Unit Commitment problem. To verify the effectiveness of the iDA-PSO approach, it was tested on four different-sized systems (5-unit, 6-unit, 10-unit, and 26-unit systems). The unit commitment, generation schedule, total generation cost, and time were compared with those obtained by other algorithms in the literature. The simulation results show iDA-PSO is a promising technique and is superior to many other algorithms in the literature.

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