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In order to achieve paramount economy, hybrid renewable energy sources are gaining importance, as renewable sources are costless. Over the past few years wind energy incorporation drew more consideration in the electricity market, as wind power took an affirmative role in energy saving as well as sinking emission pollutants. Recently developed Grey wolf optimizer (GWO) algorithm has conspicuous behavior for verdicting global optima, without getting ensnared in premature convergence. In the proposed research the exploitation phase of the grey wolf optimizer has been further improved using random exploratory search algorithm, which uses perturbed solutions vectors along with previously generated solution vectors. The paper presents a hybrid version of Grey Wolf Optimizer algorithm combined with random exploratory search algorithm (hGWO-RES) for the solution of combinatorial scheduling and dispatch problem of electric power systems. To validate the feasibility of the algorithm, the proposed algorithm has been tested on 23 benchmark problems. To verify the feasibility and efficacy of operation of proposed algorithm on generation scheduling and dispatch of electric power systems, small and medium scale power systems consisting of 7-, 10-, 19-, 20- and 40-generating units systems taken into consideration. Commitment and scheduling pattern has been evaluated with and without wind integration and it has been experimentally founded that proposed hybrid algorithm provides superior solution as compared to other recently reported meta-heuristics search algorithms.

Abstract Energy storage systems (ESS) are widely used in active distribution networks (ADN) to smoothen the drastic fluctuation of renewable energy sources (RES). In order to enhance the scalability and flexibility of ESS, a virtual energy storage system (VESS), which is composed of battery energy storage system (BESS), RES as well as flexible loads (FL), is developed in this paper to realize the functionalities of ESS in more cost-effective way in ADN. Aiming at achieving voltage regulation, dynamic pricing strategies based on system voltage condition are designed for VESS. A distributed real-time power management model containing dynamic pricing strategies is proposed to accomplish the voltage regulation and economic power sharing in VESS. Moreover, a set of distributed algorithms, over time-varying unbalanced directed networks, are designed for dynamic pricing strategies and optimal power management model. Furthermore, the convergence property, optimality and system voltage stability are explained by detailed mathematical analysis. Three various case studies which were ran on a real time digital simulator (OPAL-RT OP5600) were designed to validate the effectiveness of the strategy. Finally, simulation results show that the economic power dispatch and voltage regulation are achieved among VESS simultaneously, even in the presence of time-varying directed and unbalanced communication networks.

In electric power generation and distribution systems, three structures are capable of impacting energy quality: generation, distribution and loads. Currently, the diversity of the latter ranges from purely resistive loads such as heating systems to extremely nonlinear loads such as switched electronic power supplies. This has dramatically affected the quality of electric energy. The operation of these loads contributes to the reduction of the power factor of the installation, the injection of harmonic currents in the electrical network and the imbalance of currents and voltages between the phases in the case of three-phase systems. The implementation of a method capable of recognizing electrical loads and identifying them through algorithms can be used to manage the electric energy consumption, contributing a lot to the improvement of the quality of electric energy. In order to deal with uncertainty in the identification of these loads, probability distributions will be applied, which are able to handle uncertainty through a probabilistic modeling using Bayesian Networks.

Abstract To achieve the EU climate and energy objectives, a transition towards a future sustainable energy system is needed. The integration of the huge potential for industrial waste heat recovery into smart energy system represents a main opportunity to accomplish these goals. To successfully implement this strategy, all the several stakeholders' conflicting objectives should be considered. In this paper an evolutionary multi-objective optimization model is developed to perform a sustainability evaluation of an energy system involving an industrial facility as the waste heat source and the neighbourhood as district heating network end users. An Italian case study of heat recovery from a steel casting facility shows how the model allows to properly select the district heating network set of users to fully exploit the available waste energy. Design directions such as the thermal energy storage capacity can be also provided. Moreover, the model enables the analysis of the trade-off between the stakeholders’ different perspectives, allowing to identify possible win-win solutions for both the industrial sector and the citizenship.

Torrefaction is considered as a method for producing biofuels with improved characteristics compared to those of the “raw” biomass (higher calorific value, moisture resistance, better grindability). The torrefaction process is an endothermic process that is usually carried out in a gaseous atmosphere in the absence of oxygen. To reduce the required heat input, it is proposed to employ the oxidative torrefaction and conduct the process in a fluidized bed agitated with flue gases containing less than 6% oxygen. Preliminary studies of the oxidative torrefaction of sunflower husks, including thermogravimetric analysis of the treated material, have shown that the heat treatment time for the biomass should be at least 5 min. A fluidized bed is a reactor with ideal mixing of the treated material where uniform treatment of raw material particles cannot generally be attained. To overcome this disadvantage of the fluidization technique and achieve the required residence time for biomass in a fluidized bed during a continuous torrefaction process, it was proposed to equip a torrefaction reactor with a series of vertical baffles spaced at 50 mm. These baffles induce a loop-like flow of the processed biomass from the inlet to the outlet of the reactor. To investigate the residence time for husk particles in the reactor, a tracer, which was colored to husk particles' color with a water-soluble dye which did not change the weight and size of the particles, was injected into the bed of uncolored particles. Tracer samples were taken every 30 s at the outlet of the reactor and were analyzed using a special procedure to determine the fraction of colored particles in each sample. This enabled us to gauge the time during which the colored particles injected into the fluidized bed reached the point of their discharge from the bed. Studies performed in a “cold” model of the reactor showed that a series of vertical baffles in the bed can provide the required residence time for biomass in a reactor including commercial reactors. Plates can provide the necessary biomass residence time in the reactor.

An approach is proposed for predicting the change in the reliability of reactor pressure vessels of nuclear power plants. A computer program was used to perform a series of calculations for finding the invariant classification as a function of the degree of stochastic action on a time interval. A stable solution was obtained by modeling the stochastic action with a root mean square deviation of up to 15% of the instantaneous normalized value of the parameter. The proposed approach is not universal, but has the advantages of easily correcting forecast data, avoiding extreme conservatism, and usability at all stages of design, fabrication, assembly, and operation. 7 refs., 1 tab.

A method is presented for calculating the electromagnetic forces on the end windings of turbine generators for both the steady state and transient modes of operation. Part 1 of this paper deals with the basic concepts of the force calculation and gives several examples of steady state forces and how they vary with load and power factor. PartII deals with several types of transient operation. The currents and fields which these transients produce are discussed and forces are found for various cases such as short circuits, synchronizing out of phase and transmission line switching.

The article deals with studies of the arcing performance of SF6 puffer breakers at currents of up to 80 kA and voltages of up to 200 kV, using an interrupter unit fitted with viewing windows. The studies are mainly concerned with the behavior of the arc at current zero and with restrike phenomena under various conditions. In addition to measurements of the electrical variables and the pressure variation, the tests cover the use of high-speed cameras, spectroscopic diagnostic methods, and schlieren methods. The density fields and flow fields derived from the latter are used to optimize the gas flow. On the basis of the breaker data and those of its operating mechanism a method for computing the essential variables, e.g., pressure, gas flow, back pressure, and contact travel, is developed. The variation of these parameters as a function of the interrupter data for various currents and with due allowance for the interaction between the arc and the operating mechanism must be known if the breaker design is to be optimized. The method uses simplified equations for the gas flow and the arc. The relationship between the gas data (e. g., density, enthalpy, speed of sound, electrical conductivity, and dielectric strength) and the temperature is taken into account by using approximation functions. The temperature of the arc core is matched to the test results.

Abstract Limiting the increase of global temperature requires electrification of the railway transport, which is relatively a distinct mode of transport in terms of economy, business and socialization of a country. However, battery complemented railway transport systems such as fuel cell hybrid railway propulsion systems are constrained by the high cost of the battery, and suboptimal performance of the fuel cell under varying loads. Optimized selection of battery can reduce its costs associated with sizing, life and utilization. Similarly, managing the load distribution between the battery and fuel cell can reduce the load variations concern for fuel cell. In this study, model-based selective characterization of the battery and fuel cell is done to identify the optimal features and constraints. Following characterization, the load allocation to battery and fuel cell is determined with the targets of collaborative utilization of optimal features and mitigation of constraints. Subsequently, considering this load allocation and results of characterization, conditions are proposed for reliable sizing and optimized selection of battery. The significance of the proposed conditions in reliable sizing is explored. Based on these conditions, certain commercially developed batteries are evaluated for optimized selection of battery. The results signify this study as a foundation for research on the reliable sizing and optimized selection of battery in fuel cell hybrid railway propulsion systems.