Short term complex hydro thermal scheduling using integrated PSO-IBF algorithm

In this article, an integrated evolutionary technique such as particle swarm optimization (PSO) algorithm and improved bacterial foraging algorithm (IBFA) have been developed to provide an optimum solution to the scheduling problem with complex thermal and hydro generating stations. PSO algorithm is framed based on the intelligent behavior of the fish school and a flock of birds and the optimal solution in the multidimensional search region is achieved by assigning a random velocity to each potential solution (called the particle). BFA is designed by following the prey-seeking (chemotactic) nature of E. coli bacteria. This technique is followed in an improved manner to get the convergence rate in dynamic for a hyperspace problem by implementing a chemotactic step in a linearly decreased way instead of the static one. The effectiveness of this integrated algorithm is evaluated by using it in a complex thermal and hydro generating system. In this testing system, multiple numbers of cascaded reservoirs in hydro plants have a time coupling effect and thermal power units have a valve point loading effect. The simulation results indicate its merits by comparing it with other meta-heuristic techniques related to the fuel cost required to generate the thermal power.

Introducing adaptive machine learning technique for solving short-term hydrothermal scheduling with prohibited discharge zones

The short-term hydrothermal scheduling (STHTS) problem has paramount importance in an interconnected power system. Owing to an operational research problem, it has been a basic concern of power companies to minimize fuel costs. To solve STHTS, a cascaded topology of four hydel generators with one equivalent thermal generator is considered. The problem is complex and non-linear and has equality and inequality constraints, including water discharge rate constraint, power generation constraint of hydel and thermal power generators, power balance constraint, reservoir storage constraint, initial and end volume constraint of water reservoirs, and hydraulic continuity constraint. The time delays in the transport of water from one reservoir to the other are also considered. A supervised machine learning (ML) model is developed that takes the solution of the STHTS problem without PDZ, by any metaheuristic technique, as input and outputs an optimized solution to STHTS with PDZ and valve point loading (VPL) effect. The results are quite promising and better compared to the literature. The versatility and effectiveness of the proposed approach are tested by applying it to the previous works and comparing the cost of power generation given by this model with those in the literature. A comparison of results and the monetary savings that could be achieved by using this approach instead of using only metaheuristic algorithms for PDZ and VPL are also given. The slipups in the VPL case in the literature are also addressed

Short-term optimal hydro-thermal scheduling using clustered adaptive teaching learning based optimization

In this paper, Clustered Adaptive Teaching Learning Based Optimization (CATLBO) algorithm is proposed for determining the optimal hourly schedule of power generation in a hydro-thermal power system. In the proposed approach, a multi-reservoir cascaded hydro-electric system with a non-linear relationship between water discharge rate, net head and power generation is considered. Constraints such as power balance, water balance, reservoir volume limits and operation limits of hydro and thermal plants are considered. The feasibility and effectiveness of the proposed algorithm is demonstrated through a test system, and the results are compared with existing conventional and evolutionary algorithms. Simulation results reveals that the proposed CATLBO algorithm appears to be the best in terms of convergence speed and optimal cost compared with other techniques

SHORT TERM HYDRO THERMAL SCHEDULING PROBLEM: A REVIEW

Operation of a system having both hydro and thermal plants is far more complex and is of much more importance in a modern interconnected power system. The objective of the STHS problem is to optimize the electricity production, considering a short-term planning horizon. This paper presents an extensive review of a short term hydro thermal scheduling problem. The paper demonstrates results of various evolutionary and analytical methods applied on a short term hydro thermal scheduling problem .All the assumptions made and a brief description of the solution methods is presented in the paper. The paper provides helpful information and resources for the future studies for researchers those interested in the problem or intending to do additional research in this area

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

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

Relaxação Lagrangeana

Esta dissertação visa o problema da afetação ótima de unidades e a sua resolução. Nos dias atuais é impensável pensar numa sociedade sem energia elétrica. Assim, o sistema de energia elétrica tem de atender à demanda em cada hora do dia, respeitando as restrições operativas das unidades de geração, tentando produzir energia ao menor custo possível, tendo em conta as crescentes preocupações ambientais. Os sistemas de energia elétrica são sistemas de grande dimensão e complexidade, dessa forma, necessitam cada vez mais de um planeamento entre as suas centrais, ou seja, uma afetação ótima de unidades. A resolução deste problema de forma direta é de todo inviável, o que permite que este seja um tema de grande investigação, sendo aqui abordado um dos vários métodos de resolução, a Relaxação Lagrangeana. Este método permite a resolução do problema primal de uma forma indireta, apresentando, contudo, algumas dificuldades na obtenção de uma solução fazível. São apresentadas essas mesmas dificuldades neste trabalho, quer ao nível da resolução do problema de forma direta, quer de forma indireta. A fim de demonstrar a aplicação do método da relaxação Lagrangeana é apresentado um problema de 5 unidades geradoras para um período de 24 horas, e são retiradas algumas conclusões.This thesis aims the optimal resource scheduling and their resolution. Nowadays it is unthinkable to think of a society without electric energy. The electric power system has to meet the demand at every hour of the day respecting the operating restrictions of the generation units, trying to produce energy at the lowest possible cost, taking into account the growing environmental concerns. The electric power systems are systems of great size and complexity, so they require an increasing planning between their plants, that is, an optimal Unit Commitment. The resolution of this problem in a direct way is totally impracticable, which allows this to be a subject of great research, the method here addressed is one of many possible resolution, the Lagrangian relaxation method. This method allows the resolution of the primal problem in an indirect way, having some difficulties in obtaining a realistic (better) solution. These same difficulties are presented in this work, either at the level of solving the problem directly or indirectly. For demonstrate the application of the Lagrangian relaxation technique, a problem of 5 generating units is presented for a period of 24 hours, and deduce some conclusion

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

Application of Power Electronics Converters in Smart Grids and Renewable Energy Systems

This book focuses on the applications of Power Electronics Converters in smart grids and renewable energy systems. The topics covered include methods to CO2 emission control, schemes for electric vehicle charging, reliable renewable energy forecasting methods, and various power electronics converters. The converters include the quasi neutral point clamped inverter, MPPT algorithms, the bidirectional DC-DC converter, and the push–pull converter with a fuzzy logic controller

Integration of High Voltage AC/DC Grids into Modern Power Systems

Electric power transmission relies on AC and DC grids. The extensive integration of conventional and nonconventional energy sources and power converters into power grids has resulted in a demand for high voltage (HV), extra-high voltage (EHV), and ultra-high voltage (UHV) AC/DC transmission grids in modern power systems. To ensure the security, adequacy, and reliable operation of power systems, the practical aspects of interconnecting HV, EHV, and UHV AC/DC grids into the electric power systems, along with their economic and environmental impacts, should be considered. The stability analysis for the planning and operation of HV, EHV, and UHV AC/DC grids in power systems is regarded as another key issue in modern power systems. Moreover, interactions between power converters and other power electronics devices (e.g., FACTS devices) installed on the network are other aspects of power systems that must be addressed. This Special Issue aims to investigate the integration of HV, EHV, and UHV AC/DC grids into modern power systems by analyzing their control, operation, protection, dynamics, planning, reliability, and security, along with considering power quality improvement, market operations, power conversion, cybersecurity, supervisory and monitoring, diagnostics, and prognostics systems