This paper proposes a particle swarm optimization (PSO) method for solving the economic dispatch (ED) problem in power systems. Many nonlinear characteristics of the generator, such as ramp rate limits, prohibited operating zone, and nonsmooth cost functions are considered using the proposed method in practical generator operation. The feasibility of the proposed method is demonstrated for three different systems, and it is compared with the GA method in terms of the solution quality and computation efficiency. The experimental results show that the proposed PSO method was indeed capable of obtaining higher quality solutions efficiently in ED problems.

Particle swarm optimization to solving the economic dispatch considering the generator constraints

Evolutionary programming has emerged as a useful optimization tool for handling nonlinear programming problems. Various modifications to the basic method have been proposed with a view to enhance speed and robustness and these have been applied successfully on some benchmark mathematical problems. But few applications have been reported on real-world problems such as economic load dispatch (ELD). The performance of evolutionary programs on ELD problems is examined and presented in this paper in two parts. In Part I, modifications to the basic technique are proposed, where adaptation is based on scaled cost. In Part II, evolutionary programs are developed with adaptation based on an empirical learning rate. Absolute, as well as relative, performance of the algorithms are investigated on ELD problems of different size and complexity having nonconvex cost curves where conventional gradient-based methods are inapplicable.

Evolutionary programming techniques for economic load dispatch

With the fast-paced changing technologies in the power industry, new power references addressing new technologies are coming to the market. So there is an urgent need to keep track of international experiences and activities taking place in the field of modern unit-commitment (UC) problem. This paper gives a bibliographical survey, mathematical formulations, and general backgrounds of research and developments in the field of UC problem for past 35 years based on more than 150 published articles. The collected literature has been divided into many sections, so that new researchers do not face any difficulty in carrying out research in the area of next-generation UC problem under both the regulated and deregulated power industry.

Unit commitment-a bibliographical survey

This study presents a smart energy management system (SEMS) to optimise the operation of the microgrid. The SEMS consists of power forecasting module, energy storage system (ESS) management module and optimisation module. The characteristic of the photovoltaics (PV) output in different weather conditions has been studied and then a 1-day-ahead power forecasting module is presented. As energy storage needs to be optimised across multiple-time steps, considering the influence of energy price structures, their economics are particularly complex. Therefore the ESS module is applied to determine the optimal operation strategies. Accordingly, multiple-time set points of the storage device, and economic performance of ESS are also evaluated. Smart management of ESS, economic load dispatch and operation optimisation of distributed generation (DG) are simplified into a single-object optimisation problem in the SEMS. Finally, a matrix real-coded genetic algorithm (MRC-GA) optimisation module is described to achieve a practical method for load management, including three different operation policies and produces diagrams of the distributed generators and ESS.

Smart energy management system for optimal microgrid economic operation

Online 24-h solar power forecasting based on weather type classification using artificial neural network

Solution methodology of unit commitment (UC) using genetic algorithms (GA) is presented. Problem formulation of the unit commitment takes into consideration the minimum up and down time constraints, start up cost and spinning reserve, which is defined as minimization of the total objective function while satisfying the associated constraints. Problem specific operators are proposed for the satisfaction of time dependent constraints. Problem formulation, representation and the simulation results for a 10 generator-scheduling problem are presented.

Unit Connuitment Solution Methodology Using Genetic Algorithm

This paper describes the construction and the performance of a distributed power generating system of photovoltaics (PV) using solar energy estimation. Instead of conventional batteries a new storage device, called energy capacitor system (ECaSS), is used for its various advantages. A procedure is described to estimate the PV output power by calculating solar radiation. To calculate the daily insolation, Hottel's equation and Liu-Jordan's equation have been used with some modification. The accuracy of the procedure is verified by comparing the calculated solar radiation with the practically measured one. To apply the procedure even in cloudy/rainy weather, the characteristic of the PV output in different weather conditions has been studied using 1-day-ahead weather forecasts. With an aim to set the optimum amount of buy power, a simulation program has been developed. The system is being operated in optimal economic mode in different weather conditions. The financial benefit and load-leveling capacity of the system have been studied and presented here. It was found that the system provides an excellent economic benefit for nonflat price of electricity and load-leveling facility with a good overall efficiency.

Novel Distributed Power Generating System of PV-ECaSS Using Solar Energy Estimation

A fast transient stability assessment method and a preventive control strategy, considering both security and economy of power systems, are presented. The pattern recognition approach with two dimensional feature space is used to assess transient security. If a power system is said to be in an alert state, then quick and appropriate control actions are required. A transient security constrained economic load dispatch (ELD) which is able to shift generator outputs so that system security can be maintained, is developed. The effectiveness of the proposed method is ascertained through numerical examples for model power systems.

On-Line Secure-Economy Preventive Control of Power Systems by Pattern Recognition

Since the application of the Lagrange relaxation method to the unit commitment scheduling by Muckstadt in 1979, many papers using this method have been published. The greatest advantage of applying the Lagrange relaxation method for the unit commitment problem is that it can relax (ignore) each generator's output dependency caused by the demand–supply balance constraint so that a unit commitment of each generator is determined independently by dynamic programming. However, when we introduce the transmission loss into the demand–supply balance constraint, we cannot decompose the problem into the partial problems in which each generator's unit commitment is determined independently and have to take some measures to obtain an optimal schedule by the Lagrange relaxation method directly. In this paper, we present an algorithm for the unit commitment schedule using the Lagrange relaxation method for the case of taking into account transmission losses. © 2005 Wiley Periodicals, Inc. Electr Eng Jpn, 152(4): 27–33, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/eej.20119

https://onlinelibrary.wiley.com/doi/pdf/10.1002/eej.20119

Susumu Yamashiro

Papers

Unit Connuitment Solution Methodology Using Genetic Algorithm

Novel Distributed Power Generating System of PV-ECaSS Using Solar Energy Estimation

On-Line Secure-Economy Preventive Control of Power Systems by Pattern Recognition

Unit commitment scheduling by Lagrange relaxation method taking into account transmission losses

A Survey Study on Estimation of Customer Interruption Costs