Neural Based Tabu Search method for solving unit commitment problem with cooling-banking constraints

This paper presents a new approach to solve short-term unit commitment problem (UCP) using Neural Based Tabu Search (NBTS) with cooling and banking constraints. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to find the optimal generating unit commitment in the power system for next H hours. A 7-unit utility power system in India demonstrates the effectiveness of the proposed approach; extensive studies have also been performed for different IEEE test systems consist of 10, 26 and 34 units. Numerical results are shown to compare the superiority of the cost solutions obtained using the Tabu Search (TS) method, Dynamic Programming (DP) and Lagrangian Relaxation (LR) methods in reaching proper unit commitment

Unit Commitment Problem in Electrical Power System: A Literature Review

Unit commitment (UC) is a popular problem in electric power system that aims at minimizing the total cost of power generation in a specific period, by defining an adequate scheduling of the generating units. The UC solution must respect many operational constraints. In the past half century, there was several researches treated the UC problem. Many works have proposed new formulations to the UC problem, others have offered several methodologies and techniques to solve the problem. This paper gives a literature review of UC problem, its mathematical formulation, methods for solving it and Different approaches developed for addressing renewable energy effects and uncertainties

Short-term Hydro-thermal Coordination By Lagrangian Relaxation: A New Algorithm for the Solution of the Dual Problem

For decades, researchers have been studying the unit commitment problem in electrical power generation. To solve this complex, large scale and constrained optimization (primal) problem in a direct manner is not a feasible approach, which is where Lagrangian relaxation comes in as the answer. The dual Lagrangian problem translates a relaxed problem approach, that indirectly leads to solutions of the original (primal) problem. In the coordination problem, a decomposition takes place where the global solution is achieved by coordinating between the respective subproblems solutions. This dual problem is solved iteratively, and Lagrange multipliers are updated between each iteration using subgradient methods. To tackle, time-consuming tuning tasks  or user related experience, a new adaptative algorithm, is proposed to better adjust the step-size used to update Lagrange multipliers, i.e., avoid the need to pre-select  a set of parameters. A results comparison against a traditionally employed step-size update mechanism, showed that the adaptive algorithm manages to obtain improved performances in terms of the targeted primal problem. Keywords: Hydro-Thermal coordination, Lagrangian relaxation, Lagrangian dual problem, Lagrange multipliers, Subgradient method

Metaheuristics for the unit commitment problem : The Constraint Oriented Neighbourhoods search strategy

Tese de mestrado. Faculdade de Engenharia. Universidade do Porto. 199

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

Evaluación mediante indicadores clave de rendimiento del despacho económico hidrotérmico resuelto por medio de técnicas heurísticas

El presente artículo resuelve el problema de coordinación hidrotérmica mediante la utilización de técnicas heurísticas como alternativa a los métodos de optimización exactos. Las técnicas utilizadas son el método de enjambre de partículas, algoritmos genéticos con sus variantes de selección por ruleta y torneo y el novedoso y reciente algoritmo lobo gris. El objetivo del modelo de optimización planteado radica en la minimización de la función objetivo referente al costo de combustibles de las centrales térmicas considerando, además, el efecto de punto de válvula que le da un toque más realista al problema. La metodología de solución propuesta incluye penalizaciones en la función objetivo relacionadas a las violaciones de las restricciones de balances de potencia y el balance dinámico de los reservorios. El despacho económico se ejecuta para un sistema de prueba compuesto por múltiples centrales térmicas y varias centrales hidroeléctricas con reservorios en cascada. Los algoritmos desarrollados se implementaron en el software Matlab. Adicionalmente, se evalúa innovadoramente los resultados logrados por cada técnica heurística mediante la utilización de diferentes indicadores clave de rendimiento.This paper solves the hydrothermal scheduling problem by using heuristic techniques as an alternative to exact optimization methods. The techniques used are the particle swarm method, genetic algorithms with its variants of selection by roulette and tournament and the novel and recent grey wolf algorithm. The objective of the proposed optimization model lies in the minimization of the objective function regarding fuel costs of thermal power plants, also considering the valve point effect that gives a more realistic touch to the problem. The proposed solution methodology includes penalties in the objective function related to the violations of constraints of the power balance and dynamic balance of reservoirs. The economic dispatch is executed for a test system composed of multiple thermal power plants and several hydroelectric power plants with cascaded reservoirs. The algorithms developed were implemented in the Matlab software. Additionally, the results achieved by each heuristic technique are innovatively evaluated using different key performance indicators

Fuzzy Logic Based Solution to the Unit Commitment Problem

The aim of the unit commitment is to obtain the best combination of generation units to be turned on/off for each power demand of the daily load curve in order to ensure economic scheduling of power generation to minimize the production cost while satisfying a variety of constraints. Different techniques are available to handle the unit commitment problem to provide quality solutions in order to increase the potential savings of the power system operation such as deterministic and stochastic or modern search techniques. In this study, a proposed approach based on the fuzzy logic to handle the unit commitment problem is introduced where the suggested method is used to formulate the problem, to provide superior detection of the logic rules required, and to develop adequate algorithm that better solves them. To test the validity and effectiveness of the proposed approach, the outcomes of this approach are compared with those obtained by the dynamic programming which is the mostly used method to handle the unit commitment problem. Firstly, the production costs obtained by the fuzzy-logic and the dynamic programming for the same unit combination at each time interval loading are compared and secondly, the production costs of the fuzzy-logic and the dynamic programming are compared when both methods are employed separately to provide unit combination and production costs for each time interval. To undertake this study, two models of the Tuncbilek Thermal Power Plant in Turkey are selected. The first model consists of four generation units while the other consists of ten units. The load demand is assumed to vary over eight time periods for the four-unit model while it is assumed to vary on an hourly basis during the course of the day for the ten-unit model. The fuzzy logic approach has been successfully implemented to both models and the results have shown that the fuzzy-logic performs better than the dynamic programming in all cases of comparison

Selected Papers from the ICEUBI2019 - International Congress on Engineering - Engineering for Evolution

Energies SI Book "Selected Papers from the ICEUBI2019 – International Congress on Engineering – Engineering for Evolution", groups six papers into fundamental engineering areas: Aeronautics and Astronautics, and Electrotechnical and Mechanical Engineering. ICEUBI—International Congress on Engineering is organized every two years by the Engineering Faculty of Beira Interior University, Portugal, promoting engineering in society through contact among researchers and practitioners from different fields of engineering, and thus encouraging the dissemination of engineering research, innovation, and development. All selected papers are interrelated with energy topics (fundamentals, sources, exploration, conversion, and policies), and provide relevant data for academics, research-focused practitioners, and policy makers