Antlion optimization algorithm for optimal non-smooth economic load dispatch

This paper presents applications of Antlion optimization algorithm (ALO) for handling optimal economic load dispatch (OELD) problems. Electricity generation cost minimization by controlling power output of all available generating units is a major goal of the problem. ALO is a metaheuristic algorithm based on the hunting process of Antlions. The effect of ALO is investigated by solving a 10-unit system. Each studied case has different objective function and complex level of restraints. Three test cases are employed and arranged according to the complex level in which the first one only considers multi fuel sources while the second case is more complicated by taking valve point loading effects into account. And, the third case is the highest challenge to ALO since the valve effects together with ramp rate limits, prohibited operating zones and spinning reserve constraints are taken into consideration. The comparisons of the result obtained by ALO and other ones indicate the ALO algorithm is more potential than most methods on the solution, the stabilization, and the convergence velocity. Therefore, the ALO method is an effective and promising tool for systems with multi fuel sources and considering complicated constraints

Integration of Energy Storage into a Future Energy System with a High Penetration of Distributed Photovoltaic Generation

Energy storage units (ESU) are increasingly used in electrical distribution systems because they can perform many functions compared with traditional equipment. These include peak shaving, voltage regulation, frequency regulation, provision of spinning reserve, and aiding integration of renewable generation by mitigating the effects of intermittency. As is the case with other equipment on electric distribution systems, it is necessary to follow appropriate methodologies in order to ensure that ESU are installed in a cost-effective manner and their benefits are realized. However, the necessary methodologies for integration of ESU have not kept pace with developments in both ESU and distribution systems. This work develops methodologies to integrate ESU into distribution systems by selecting the necessary storage technologies, energy capacities, power ratings, converter topologies, control strategies, and design lifetimes of ESU. In doing so, the impact of new technologies and issues such as volt-VAR optimization (VVO), intermittency of photovoltaic (PV) inverters, and the smart PV inverter proposed by EPRI are considered. The salient contributions of this dissertation follow. A unified methodology is developed for storage technology selection, storage capacity selection, and scheduling of an ESU used for energy arbitrage. The methodology is applied to make technology recommendations and to reveal that there exists a cost-optimal design lifetime for such an ESU. A methodology is developed for capacity selection of an ESU providing both energy arbitrage and ancillary services under a stochastic pricing structure. The ESU designed is evaluated using ridge regression for price forecasting; Ridge regression applied to overcome numerical stability and overfitting issues associated with the large number of highly correlated predictors. Heuristics are developed to speed convergence of simulated annealing for placement of distributed ESU. Scaling and clustering methods are also applied to reduce computation time for placement of ESU (or any other shunt-connected device) on a distribution system. A probabilistic model for cloud-induced photovoltaic (PV) intermittency of a single PV installation is developed and applied to the design of ESU

Optimization Methods Applied to Power Systems Ⅱ

Electrical power systems are complex networks that include a set of electrical components that allow distributing the electricity generated in the conventional and renewable power plants to distribution systems so it can be received by final consumers (businesses and homes). In practice, power system management requires solving different design, operation, and control problems. Bearing in mind that computers are used to solve these complex optimization problems, this book includes some recent contributions to this field that cover a large variety of problems. More specifically, the book includes contributions about topics such as controllers for the frequency response of microgrids, post-contingency overflow analysis, line overloads after line and generation contingences, power quality disturbances, earthing system touch voltages, security-constrained optimal power flow, voltage regulation planning, intermittent generation in power systems, location of partial discharge source in gas-insulated switchgear, electric vehicle charging stations, optimal power flow with photovoltaic generation, hydroelectric plant location selection, cold-thermal-electric integrated energy systems, high-efficiency resonant devices for microwave power generation, security-constrained unit commitment, and economic dispatch problems

Experimental and Theoretical Analysis of Pressure Coupled Infusion Gyration for Fibre Production

In this work, we uncover the science of the combined application of external pressure, controlled infusion of polymer solution and gyration in the field of nanofiber preparation. This novel application takes gyration-based method into another new arena through enabling the mass production of exceedingly fine (few nanometres upwards) nanofibres in a single step. Polyethylene oxide (PEO) was used as a model polymer in the experimental study, which shows the use of this novel method to fabricate polymeric nanofibres and nanofibrous mats under different combinations of operating parameters, including working pressure, rotational speed, infusion rate and collection distance. The morphologies of the nanofibres were characterised using scanning electron microscopy, and the anisotropy of alignment of fibre was studied using two dimensional fast Fourier transform analysis. A correlation between the product morphology and the processing parameters is established. The response surface models of the experimental process were developed using the least squares fitting. A systematic description of the PCIG spinning was developed to help us obtain a clear understanding of the fibre formation process of this novel application. The input data we used are the conventional mean of fibre diameter measurements obtained from our experimental works. In this part, both linear and nonlinear fitting formats were applied, and the successes of the fitted models were mainly evaluated using Adjusted R2 and Akaike Information Criterion (AIC). The correlations and effects of individual parameters and their interactions were explicitly studied. The modelling results indicated the polymer concentration has the most significant impact on fibre diameters. A self-defined objective function was studied with the best-fitted model to optimise the experimental process for achieving the desired nanofibre diameters and narrow standard deviations. The experimental parameters were optimised by several algorithms, and the most favoured sets of parameters recommended by the non-linear interior point methods were further validated through a set of additional experiments. The results of validation indicated that pressure coupled infusion gyration offers a facile way for forming nanofibres and nanofibre assemblies, and the developed model has a good prediction power of experimental parameters that are possible to be useful for achieving the desirable PEO nanofibres