فصلنامه مهندسی و مدیریت انرژی
سال سیزدهم شماره 2 (پیاپی 48، تابستان 1402)

One of the new concepts in line with the development and decentralization of smart grids is energy democracy. Energy democracy means possible, easy, and non-discriminatory access to energy for all consumers. The presence of smart buildings in the smart grid as prosumers that can both produce and consume clean energy can contribute to the development of decentralization and decarbonization in electricity industry. An energy community includes a set of energy users as well as energy resources and energy consumption. Prosumers can participate in peer-to-peer (P2P) energy trading through appropriate communication infrastructures and contribute to the energy supply of the energy community. In this paper, the problem of energy management of smart grids, including energy communities, was solved while promoting energy democracy for the presence of smart buildings in P2P energy trading and residential demand response programs. An energy democracy model for the set of energy users including prosumers and managers within energy communities was introduced according to the concept of users’ preferences. In this paper, prosumers were classified into three flexible, economy-oriented, and community-oriented categories according to their preferences. Also, managers of energy communities were classified into two categories according to their preferences: managers with an interactive approach and managers with a non-interactive approach. The problem was solved by the CPLEX method in GAMS software. The results showed that the proposed approach improved energy democracy in the smart grid.

One of the main and important problems of power quality in the power distribution network is harmonic pollution. Understanding and quantifying the level of harmonics in the network is very important before proposing any suitable method to reduce the harmonic problems in the network as well as the network development plan. In this regard, in this paper, according to the classification of customers in the power distribution network and based on the most significant number of customers in the network, electrical loads are classified into four categories: residential, commercial, office, and combinatorial. Then the harmonic evaluation of the power distribution network for each type is carried out. In order to make the evaluation more operational and practical, two new harmonic indices are proposed as well as a new way of expressing the total current harmonic distortion. Considering that it can be assumed that each type of loads injects similar harmonics into the network, analyzing the measurement results for each type of load shows the harmonic behavior of each type of load in the distribution network to a large extent, which in the development and loading of distribution substations is very useful. According to the results, the current harmonic distortion of the load types is categorized as 1. office 2. commercial 3. residential 4. combinatorial in order from high to low. Based on this, it is possible to consider the range of harmonic factor K for combinatorial loads around 3, residential loads around 3.5, commercial loads around 5, and office loads around 11. Simulation results using MATLAB software show that third-order harmonic compensation can improve the total current harmonic distortion for office, residential, and combinatorial loads by up to 40%, and for commercial loads by up to 30%.

With penetration of renewable energy sources and increasing congestion in transmission networks, the issue of unit commitment (UC) problem has increased in importance, and power system operators demand effective approaches to find a suitable solution to this problem. In this paper, by considering a dynamic line rating (DLR) in the presence of wind power units, a model has been offeredfor the UC problem  to use the existing capacity of lines more effectively through adding smart-grid technologies to the power system. To adapt the proposed approach with real conditions, uncertainties of the problem parameters including wind speed, network load, and ambient temperature were modeled by a scenario-based method in form of a stochastic programming. A Monte-Carlo simulation was used to generate those scenarios, and K-means clustering algorithm was employed so as to reduce  scenarios . All problem limitations were taken into account, and transmission network constraints were considered by AC load flow relations. Numerical results on the IEEE RTS-24-bus system demonstrated the efficiency of the presented model in reducing transmission congestion, operating costs, wind power curtailment; and finally the enhancement of  the network’s technical criteria along with the reliable and stable planning for the power system. Rgarding simulation results, the presence of DLR increased the conductor temperature up to 7 oC by satisfying the maximum allowable temperature. This resulted in 34% higher loading of line compared to a static rating. In this way, the DLR brought  about a 15.33% reduction in total operating cost. In addition, the load shedding and wind power curtailment showed reductions of  88.9% percent  and 89.7% in the presence of DLR.

In this article, through using the theory of hybrid dynamical systems, the boost converter was modeled as a switching system. Then, by taking into account parameter uncertainty, input disturbance, and variable state delay in the presence of a switching with a constraint of average dwell time, the design problem of fault diagnosis along with output feedback-based control-   has been formulated as a multi-objective optimization problem. Onel2-gain performance index guarantees the robustness of the fault to disturbance; the other l2-gain performance criterion guarantees the sensitivity of the residual to fault. By adopting a switchable Lyapunov function, sufficient conditions have been obtained for fault detection along with control in terms of linear matrix inequalities. In this research, an approximate method was used; that is, an averaged state-space model of the boost converter. The simulation results showed the effectiveness of the present approach.

In traditional generation systems, about 25% of energy is wasted, and the presence of distributed energy resources (DER) such as photovoltaic, wind turbines, fuel cell, and the combined heat and power can reduce fuel consumption, pollution, and transmission losses. In this paper, a complete energy management framework in a microgrid is proposed by considering the constraints using Improved Shuffled Frog Leaping Algorithm, in which the exact share of energy production for different units is determined. The proposed scheme is used to select the best arrangement of DERs in the microgrid, the output of which is to determine the number and optimal location of DERs in several bus-bars. Then, the independent system operator determines the quantity of energy exchange and consumption by considering load distribution constraints. Boilers and CHPs have also been used to maintain the balance between the production of thermal power by energy sources and thermal demands. In addition, the Demand Response Program has been used with the aim of smoothing the load curve and of reducing the operating costs. Finally, the proposed method has been implemented and simulated using MATLAB software on a two standards 69-and- 118-bus IEEE system. The comparison of the results with other algorithms showed the accuracy and superiority of the proposed method from the point of view of reducing operating costs.

This paper presents a method of load-frequency control in power systems in the presence of wind turbines in the presence of wind uncertainty. To do this, using power system modelled on power factory@ software and considering classic stabilizers, the speed of the wind turbines is controlled.  In the case of increasing the system damping performance, using intelligent particle swarm optimization algorithm, stabilizer parameters are optimized. Also, in order to evaluate wind units stability through different natural situations, considering the wind and load uncertainties evaluated through LHS sampling algorithm, the wind turbines frequency control are investigated. Results indicate the proper performance of the controller in the presence of wind and load uncertainties.

Air conditioning systems account for a significant portion of electricity consumption in buildings. Therefore, the use of new technologies to reduce electricity consumption is essential for engineers and researchers. In this research, an ice storage system in combination with the air conditioning system of an office building has been investigated to reduce the electrical energy consumption of the air conditioning system. For this purpose, a building in Chabahar-Iran (as a region with a high cooling load required region) is considered. The building is simulated in TRNSYS software at the existing condition as well as with the added ice storage system to predict the performance of the systems. The study shows that ice storage system is more efficient in the partial load strategy than other examined strategies. It was also found that by using an ice storage system the total electricity consumption could be reduced about 37.89%, and the new system was able to transfer 37.9% of energy consumption from peak load hours to medium and low load hours. Economically, it is proved that by employing the ice storage system in the partial load strategy, a significant amount of reduction in electricity bill, about 62%, can be achieved.

The challenge of energy and environmental pollution has forced researchers to make more use of solar energy. In the present study, a new solar air heater collector system with a synthetic combination of arc-shaped wire roughness and external recycle of airflow has been presented, and its performance has been evaluated in different conditions. Modeling is performed using energy conservation equations for different parts of the collector and is solved by a semi-analytical method. The validation of the present results indicates the accuracy of the method used. The results showed that the new hybrid system effectively increased energy and exergy efficiencies at mass flows less than about 0.04 kg/s. Also, in a constant roughness condition and at low mass flow rates, increasing the flow recycle ratio to about 3, increased the collector performance.  However, in high flow rates and recycle ratios, exergy efficiency was reduced sharply due to high pressure drop, despite an increase in energy efficiency. Thus, it was less than the simple collector system. Increasing the intensity of solar radiation increased energy and exergy efficiencies in the new system. Examination of the geometric parameters of artificial roughness showed that an increase in the diameter of the curved wire improved the performance of the new system while changing the curvature angle of the wire had little effect.

This paper deals with the energy harvesting of microbeam reinforced with functionally graded carbon nanotubes. The microbeam is intended to place a harmonic position. The effects of size are assumed using strain gradient theory. The effective modulus of the nanocomposite beam is obtained using the principle of porosity. Based on the theory of sine theory, the final relations of motion are calculated. Using the differential square solution and Newmark methods, the energy harvesting and dynamic instability region of the microbeam is calculated. The effects of boundary conditions, volume fraction and distribution of carbon nanotubes, size, temperature and length-to-thickness ratio of microbeam on the dynamic instability curve are shown. Numerical results show that the dynamic instability region occurred at higher resonant frequencies and with increasing volume fraction of carbon nanotubes. In addition, the resonant frequency is higher for functionally graded carbon nanotubes with X-shaped distribution compared to the uniform state. In addition, the electric power produced increases with the increase in the thickness of the piezoelectric layer.

Due to importance of pigging operations for purposes such as monitoring-cleaning, which leads to an increase in the service life of pipeline networks, management, and optimization of energy consumption in oil and gas industries, providing accurate numerical models is a research need that has been very vital. Considering advantages of meshless methods, for the first time in this research a model is presented for evaluating the flow around the pig using the smooth particle hydrodynamics (SPH) method and the standard k-ε model to simulate the turbulence of the flow. Besides, the performance of the model based on the experimental study has been evaluated and validated. The results showed that the average error rate of the SPH model compared to the laboratory model was less than 5%, which indicated the research model's high accuracy and acceptable performance. After validating the performance of the research model, the simulation of the flow around the stationary and mobile pig was modeled, and the results were compared and evaluated with the existing numerical results. In addition, by using a meta-heuristic algorithm of gray wolves optimization (GWO), studies wereconducted on the relative diameter parameter of the bypass pig to achieve optimal values of this parameter. The results of the optimization model showed that the optimal relative diameter of the bypass pig was equal to d⁄D=0.418. The results of this research showed that the presented model had an acceptable accuracy in modeling the flow around the bypass pig in the pipe, and it could also be used as a reference model based on the SPH method for modeling the flow around the bypass pig.