JOURNAL OF ENERGY MANAGEMENT
Year:2017 | Volume:6 | Issue:4 |Papers Count:6

In the preset study, the performance of a solar assisted heating, ventilation and air conditioning (HVAC) system in an operating theater building was studied. The yearly performances of the existing HVAC system and the system with the added solar collectors were simulated in terms of energy consumption and provided air conditions using a transient system simulation software (TRNSYS). In the modified system, the solar collectors feed a liquid-to-air heat exchanger, which is defined to be replaced with the main heater of the HVAC system during the day times throughout the year. Three solar integrated HVAC system configurations consisting of three types of standard liquid flat-plate collectors namely, Configuration A: unglazed, Configuration B: glazed painted, and Configuration C: evacuated tube solar collectors were examined to determine the most proper configuration in terms of the energy consumption and provided air conditions. Based on the simulation results, all the configurations examined are capable of providing proper air into the space. However, the energy performance of the configurations indicates that the Configuration A has the priority in terms of energy consumption level and is recommended to be implemented in the existing HVAC system.

This paper investigates impacts of possible energy generation policy and consumption behavior changes on optimal energy management and feasibility study of a hybrid energy system. The study was performed on a remote area near Esfarjan, a village located in Shahreza, Iran. In the main scenario, where the current energy generation policy is applied, the customers’ consumption behavior is studied applying an incentive based demand response algorithm. However, the sensitivity analysis scenario applies the near future condition that is gradually taking place by reducing the energy subsidies, whereas customers are assumed to be inflexible. Impacts of uncertainties related to gas and electricity price, environmental issues and inflation rates are evaluated in the latter scenario. Simulations have been done on six different system configurations for both the scenarios. Results highlight the significant role of long-term energy generation policies in analogy with customer’s short-term consumption behavior. It is also indicated that configurations involving renewable resources will become stronger rivals for configurations involving the external grid in the near future, which in turn results in more interest in investing on renewable resources.

One of the basic obstacles in the deployment of the clean technologies such as wind turbines or PV modules is their intermittent nature due to dependency to the wind speed and solar radiance. The authors in this paper aim to analyze the effect of the clean technologies such as wind turbines and PV modules in the total and individual costs of the distribution system. In order to model the uncertain nature of the clean technologies, a probabilistic method is proposed in this study. So, a DG planning problem based on the hourly variations in the wind speed and solar radiance in order to reduce the total cost of the distribution system is proposed. The hourly variations of the load as well as the hourly variations in the wind speed and solar radiance is considered. All of the defined economic, technical and environmental functions are turned into cost functions. An encouraging and punishment mechanism is defined beside the other cost functions. The planning problem is formulated as mixed integer nonlinear programming problem (MINLP). The proposed method is applied on the 9-bus distribution system and the results show a significant reduction in annual costs of the distribution system in presence of the DG units.

The aim of this paper is present an optimizing method to use of maximum capacity of the photovoltaic panels. Here, we are presenting a method for the maximum power point tracking in the photovoltaic systems by using of the neural networks and the adaptive controller. In the proposed system, we estimate an error by using of neural network. If this error was less than of the allowable systems error, the system is working at the maximum power point, and if the error value was greater than of the allowable error, the output power can be adjusted by using of the adaptive controller. The adaptive part of the proposed system, is consists of two fuzzy controllers with two different rule base. The first controller designed to produce the duty cycle of the boost converter and the second controller designed to adjusting online the outputs scaling factor of the first controller. We simulate the proposed system in the MATLAB software and then compare the output power of this system with the output power of the conventional fuzzy and the P& O methods. The comparison' s results show that the proposed system has better performance with comparison of the two mentioned above methods.

Making targeted subsidies and the process of releasing energy market and specified criteria for quality of delivered energy to consumers shows the necessity in explanation of producing energy in Iran. In the meantime, Thermal power plants produce about 85% of electricity generation in Iran. Steam and gas turbine power plants have created the vast capacity of thermal plants power generation but the significant portion of this generated power is not in the sense of new energy policy. Therefore the reconstructing and improvement of thermal power plants has undeniable importance. In this paper, considering two major methods in reconstructing of the thermal power plants, eligible power plants have been presented. Results are being discussed according to the important economic parameters like electricity generation costs, capital return rate, cost benefit, annual interest and etc. In the meantime, estimation of changes in target plants in terms of technical and economical characteristics will have an effective role in our decisions it means the changes have been effected by considering features of current plants and their potentials. The efficacy of reconstructing on average efficiency, capacity and electricity generation cost can be effective parameters in future management decisions.

In this paper we have continued to studying a previously done research. Three types of power plants include an organic Rankine cycle (ORC), a dual-fluid-hybrid (DFH) and a single-fluid hybrid-fuelled (HYB) have been re-modeled. After model validation, thermodynamic studies and exergy analysis have been extended for the defined cases using the first and second laws of thermodynamics. Then thermoeconomic analysis by three various parametric capital cost functions was conducted to select the best model with more exactitude. As had been already concluded, from the viewpoint of thermodynamics the HYB plant with cyclohexane is the best option, but the new results shows that from the economical approach the DFH plant with R245fa and R236fa are suitable chooses. According to the results of first step, the DFH plant has better overall performance thus in the next step, it was studied more and variant organic fluids were evaluated as operating fluid for its low pressure cycle. It was observed that as the thermodynamic approach toluene was the best option and as the economical approach R236fa and toluene were suitable for DFH plant. With a comprehensive survey, R717 is the best choice as operating fluid for DFH plant.