In this paper, a novel risk-based, two-objective (technical and economical) optimal reactive power dispatch method in a wind-integrated power system is proposed which is more consistent with operational criteria.  The technical objective includes the minimization of the new voltage instability risk index. The economical objective includes cost minimization of reactive power generation and active power loss. The proposed voltage instability risk employs a hybrid possibilistic (Delphi-Fuzzy)-probabilistic approach that takes into consideration the operator’s experience, the wind speed and demand forecast uncertainties when quantifying the risk index. The decision variables are the reactive power resources of the system. To solve the problem, the modified multi-objective particle swarm optimization algorithm with sine and cosine acceleration coefficients is utilized. The method is implemented on the modified IEEE 30-bus system. The proposed method is compared with those in the previously published literature, and the results confirm that the proposed risk index is better at estimating the voltage instability risk of the system, especially in cases with severe impact and low probability. In addition, according to the simulation results compared to typical security-based planning, the proposed risk-based planning may increase the security and economy of the system due to better utilization of system resources.

The recent state of electrical system comprises the conventional generating units along with the sources of renewable energy. The suggested article recommends a method for the solution of single and multi-objective optimal power flow, incorporating wind energy with traditional coal-based generating stations. In this article, the two Thermal power plants are replaced with the wind power plants. The techno-economic analysis are done with this state of electrical system. In proposed work, Weibull probability distribution functions is used for calculating wind power output. A non-dominated sorting based multi-objective moth flame optimization technique is used for the optimization issue. The fuzzy decision-making approach is applied for extracting the best compromise solution. The results are authenticated though modified IEEE-30 bus test system, which is combined with wind and Thermal generating plants.

In this research, the economic and technical method of power plant wastewater treatment and removal of heavy metal (specially in Sahand wastewater) has been studied. The result indicate quality and quantity of that wastewater in power plant depend on the type of fuel, combustion units capacity, their operation and material used in this structure. Common point in wastewater is that any of them is not permanent and all of them are periodic. In this research ,PH changes and flocculation and coagulation are being used to study the removing of heavy metals. Therefore, with similar artificial wastewater characteristics for preheating air and chemical washing boiler wastewater of Sahand power plant wastewater prepared. It should be mentioned that there are heavy metals only, in preheating air and chemical acidic washing boiler wastewater. Hence removal percent of heavy metal in mentioned wastewater and in the other wastewaters is studied to define the acidity neutralization. In poisoned air preheating wastewater and acidic washing boiler wastewater treatment, following the method of precipitation of heavy metals in basic PH, at first pH of two wastewaters is raised to 8,9,10 with addition of caustic soda. In this step removal percentage of heavy metals measured in atomic absorption method, illustrates in air preheating wastewater with PH =9 and in acidic washing boiler wastewater with PH =8 the most removal percentage of heavy metals obtained. In air preheating wastewater and with PH =9, removal percentage of Fe, V, Ni, Cu respectively is equal to 99.88%, 93.54%, 99.77%, 95.73% and in acidic washing boiler wastewater with PH =8 the removal quantity of Fe obtained 99.65%. Hence, in order to obtain more removal percentage of heavy metals and reaching to Iran environment standard, treatment was continued with flocculation and coagulation method by using Ferric chloride, Ferric sulfate and Alum in 4 concentrations 25, 50, 75, 100. In air preheating wastewater, after atomic absorption test on these samples and evaluation of results, it was obvious that the most removal percentage was obtained by adding of alum with concentration of 25 mg/lit. In this condition the removal percentage of Fe, V, Ni, Cu respectively is equal to 99.98%, 99.99%, 99.97%, and 99.89%. In acidic washing boiler wastewater the most removal percentage was obtained by adding Alum with concentration of 50 mg/lit. In this condition the removal percentage of Fe was equal to 99.98 Acidic amount in basic wastewater treatment was measured and for neutralization step, sulfuric acid was added to wastewater. In preparation boiler surface wastewater, aeration method was being used in order to removal Ammonia. Ammonia quantity in Wastewater can be recognized from its order. But after aeration in 0.5 hour, the quantity is decreased and the odor is no more recognizable. After finishing aeration for neutralization step, sulfuric acid was added to wastewater.

Recently, renewable power plants utilize clean and sustainable resources for electricity generation. The Ocean Thermal Energy Conversion (OTEC) system uses ocean surface water as a high-temperature source and the water at a depth of the ocean as a low-temperature source. The difference between these temperatures is 20, C or greater, and the working fluid with a low boiling point can be used for electricity generation. In a closed-cycle OTEC system, the working fluid through a thermodynamic cycle based on the Rankine cycle can rotate the turbine and generate electricity. Due to the ocean surface temperature variation, the output power of the OTEC system changes and yields numerous states concerning the generated power of this plant. Thus, for integrating the OTEC systems with the power system, many aspects of power system including reliability may be affected and thus, new approaches must be developed for investigation of these effects. In this paper, the reliability of the power system containing the OTEC system based on the multi-state reliability model and the conditional value at risk concept is evaluated and the valuable indices used for generation expansion planning of the power system are calculated.

The present research deals with the opportunities for the availability predictive modeling of a Thermal plant using the Markov process and probabilistic approach. These opportunities will be identified by evaluation of a power generation system of a Thermal power plant. This feasibility study covers two areas: development of a predictive model and evaluation of performance with the help of the developed model. The present system under study consists of four subsystems with three feasible states: full working, reduced capacity working and failed. Failure and repair rates of all subsystems are assumed to be constant. After drawing a transition diagram, differential equations are generated and then a probabilistic predictive model using Markov approach has been developed, considering some assumptions. The availability matrix for each subsystem is also developed, which provides various availability levels for different combinations of failure and repair rates of all subsystems. On the basis of this study, the performance of a power generation system is evaluated. The developed model helps in the comparative evaluation of alternative maintenance strategies.

The majority of the power transformers failures are caused by the Thermal stresses under abnormal operating conditions, such as harmonic loads. Therefore, it is of great interest to determine the temperature distribution inside the power transformers. In this paper, a new Thermal equivalent circuit is presented by which the temperature in different regions of the transformer is estimated under harmonic loads. Also, the three-dimensional Finite Element (FE) Model of the power transformer is developed to calculate the power losses in each part of the transformer that are considered as the heat sources in the proposed equivalent circuit. The computed hotspot and average oil temperatures are compared with those obtained from IEEE Std C57. 91 method, thereby the accuracy of the proposed method for calculating the temperature rise due to harmonic loads, is investigated. Finally, derating of the power transformer is discussed under harmonic loads.

In this paper, the optimization of long term operation and determination of the reliability level of a hydro-Thermal power system are integrated into a unified model. Inflow to reservoirs is modeled as a random variable. Furthermore, the demand for energy is also assumed to be a random variable with normal distribution. In order to minimize the total cost, the reliability level of the system is determined, rather than considering it as a priori input data. Since the resulting model is a large-scale stochastic nonlinear programming, it is necessary to develop a special method to solve it. This method, which provides an optimal solution within three stages, consists of a decomposition technique, Lagrangian relaxation and nonlinear and dynamic programming methods. To test the method, it has been implemented in Khuzestan power system and the results are compared with the existing operation procedures.

In the world today, fossil fuels as conventional energy sources have a crucial role in energy supply since they are substantial drivers of the “ Industrial Revolution” , as well as the technical, social, and economic developments. Global population growth along with high levels of prosperity have resulted in a significant increase in fossil fuels consumption. However, fossil fuels have destructive impacts on the environment, being the major source of the local air pollution and emitter of greenhouse gases (GHGs). To address this issue, using renewable energy sources especially solar energy as an abundant and clean source of energy, has been attracted considerable global attention, which can provide a large portion of electricity demand. To make the most of solar energy, concentrated solar power (CSP) systems integrated with cost effective Thermal energy storage (TES) systems are among the best options. A TES system has the ability to store the Thermal energy during sunshine hours and release it during the periods with weak or no solar radiation. Thus, it can increase the working hours as well as the reliability of a solar system. In this paper, the main components of the solar Thermal power systems including solar collectors, concentrators, TES systems and different types of heat transfer fluids (HTFs) used in solar farms have been discussed.