IRANIAN ELECTRIC INDUSTRY JOURNAL OF QUALITY AND PRODUCTIVITY (IEIJQP)
Year:2020 | Volume:8 | Issue:3 (17) |Papers Count:8

In residential section, Studies have shown that, along with the use of various household consumption management techniques, the so-called hubs of energy can also be used to improve the performance and management of home energy management. In each electrical energy system, customers are aiming to minimize their energy costs. In this paper, it can be seen that in each home a home-made residential energy hub can be used, including different consumables, energy storage systems (Battery, electric vehicle), energy production systems (solar photovoltaic, wind or energy produced from a gas plant Solar hybrid) and two-way communication links between these components. It should be noted that in this paper, the hub system consists of CHP (combined heat and power), PHEV (plug-in hybrid electric vehicle), HLM (home load management), DR (demand response program) and TS (thermal storage), which should reduce the electrical and thermal load with the lowest cost of feeding. Finally, the effects of load accountability and storage systems in the numerical study are reviewed and the results are compared, which indicates the effectiveness of the proposed model.

Advanced Metering Infrastructure (AMI) is one of the most significant applications of the Smart Grid. It is used to measure, collect, and analyze data on power consumption. In the AMI network, the smart meters traffics are aggregated in the intermediate aggregators and forwarded to the Meter Data Management System (MDMS). The infrastructure used in this network should be reliable, real-time and scalable in order to guarantee reliable and timely transmission of information. In this paper, we propose an SDN (Software-Defined Network)-based infrastructure for the AMI networks which can enhance the reliability of the network and reduce network latency. In the proposed method, we have proposed a new method in which a dynamic aggregator is assigned to each smart meter, and, in addition, an appropriate routing algorithm is proposed in order to ensure the timely and reliable transmission of smart meter data to MDMS. The bandwidth required for each flow will be reserved in all links along the path. This approach increases the reliability of AMI network and satisfies the flow requirements such as bandwidth and delay. The simulation results show that proposed infrastructure significantly improves the AMI reliability and reduces the sensitivity to aggregator down.

The penetration of distributed generation sources and energy storage units in distribution networks is increasing. Therefore, their impact on the reliability of the network is very necessary. In this study, in order to provide an optimal energy management strategy for smart distribution network, the multi-objective optimization problem of dynamic distribution feeder reconfiguration in the presence of distributed generation sources and energy storage units has been optimized. The objective functions in this study are loss of energy, energy not supplied and operation cost. In order to simultaneously optimize the reliability index and other target functions, an optimal scheme for charging and discharging energy storage systems as well as optimal topology for distribution network feeders is presented. Also, in order to solve the multi-objective optimization problem in this study, the combination of particle swarm optimization and shuffled frog leaping algorithm has been used. The proposed strategy has been tested on a 95-boset network to demonstrate the capability of the proposed method.

The boiler is one of the most vulnerable parts of a power plant, which is responsible for producing steam for moving turbines. In order to increase the thermal efficiency of the power plant, it is necessary to prevent heat loss in the boiler combustion chamber and simultaneously control the environmental pollutant parameters such as NOx and CO. Failure to control environmental pollutants will increase fuel consumption, rupture of water and wastewater, and, as a result, an unplugged unit of the plant, which will cause a lot of economic damage to power plants and the environment. Therefore, in this research, it has been tried to study the environmental parameters of the combustion chamber output and its effect on the shape of the flame and the heat output of the boiler as well as the amount of CO and Nox contaminants due to changes in the conditions of operation (Applying The excess air to the furnace-the change in the inlet air flow-the change in the outlet air flow-is measured and monitored. The results of this work are that by controlling the oxygen level, adjusting the fuel paths to the burner, the flow rate in the fuel paths, measuring and controlling the initial air flow and blower air, accurate control of the air to fuel ratio, mechanical oscillation of the burners and damper, The quality of the fuel consumed is estimated by the amount of pollutant production and effective planning to reduce the production of NOx and CO pollutants.

The conventional real power-frequency and reactive power-voltage droop characteristics are commonly employed to share the electric power among parallel distributed generation (DG) units. Despite some advantages such as easy implementation and no need for communication infrastructure, inaccurate reactive power sharing is one of the main disadvantages of conventional droop control. This paper presents a modified droop control scheme based on changing the y-intercept of the voltage droop characteristic. In this method, the initial control of the inverter-based DG units is performed using conventional droop characteristics. Then, the reactive power sharing error for each DG unit is determined by injecting a small real power disturbance and making a coupling between the real and reactive powers. Accordingly, the modified reactive power controller modifies the generated reactive power of each DG unit by changing the output voltage. As this process should be simultaneously implemented in all DG units and employment of the central controller and the communication link for activation of the modification procedure has some disadvantages, this paper presents a local activation mechanism. The proposed scheme operates based on a significant change of reactive power and ensures the execution of all stages of modified droop control and its reactivation to respond to the microgrid power changes. Several simulation case studies using a low voltage microgrid network verify the effectiveness of the proposed control scheme.

Energy hub is a concept relates various energy carriers which has been expanded in recent years. Operation of energy hub is often attended with uncertainties. Therefore, this paper presents a linear model based on information gap decision theory (IGDT) to solve the energy hub problem. This approach can consider plenty of uncertainties, simultaneously. Energy hub under study includes a combined heat and power (CHP) unit, a boiler, a wind turbine and trades electricity with day ahead and real time markets as well as natural gas network. Different uncertainties affect the problem. Here, the uncertainties of real time and day ahead electricity prices, wind turbine generation and natural gas prices are taken into account. Since, nature of IGDT is a bi-level optimization problem, it has been linearized using the Karush Kohen Tucker (KKT) conditions and strong duality theorem and then, it is solved. The simulations have been done on the mentioned case study verifying the efficiency of the proposed model.

In recent years, multi-energy microgrids including electricity, gas and thermal are more grown; that presents demand response (DR) models considering multi-energy storages and renewable resources. Appropriate DR management with storages may lead to optimal flexibility. In this paper, a probabilistic linear model is introduced to assess the effect of flexibility and DR. In the proposed model, electrical and thermal DR, multi-energy storages, and participation in reserve market are considered as the main contribution. The proposed model guarantees thermal comfort as well as increasing flexibility and reserve commitment. By applying the proposed method on a distribution network in UK, it is illustrated that by utilization of the proposed DR program the flexibility of microgrid increases and the cost of operation decreases.

Reducing electric power theft is a significant part of the potential benefits of implementing the concept of smart grid. This paper proposes a data-based approach to identify locations with unusual electricity consumption. The new distance-based method classifies the new data as violator costumers, if their distance is long to the primary consumption data. The proposed algorithm determines the number of final clusters based on the number of initial clusters and a specific index. This method is based on the dynamic fuzzy clustering algorithm. The framework removes the defect of violator subscribers by mistake. In this article are studied regional and subscriber sections of Urmia city between 2000 and 2017 years and significantly more effective than other methods of uncontrolled learning and introduced as an efficient unsupervised developed method.