Journal of Green Energy Research and Innovation

Abstract Restructuring the distribution system in the presence of distributed generation (DG) sources is an effective solution to reduce the cost of power generation and improve the technical and economic parameters of networks. This paper models the optimal design of the location and capacity of DGs in a distribution system as a multi-objective optimization problem. The technical parameters of the problem include network losses, voltage stability index, and voltage profile improvement. Moreover, the economic parameters of the problem are the capital and operation costs of the system. The optimization problem presented in this paper is of mixed-integer nonlinear programming (MINLP) type, so the enhanced imperialist competition algorithm (EICA) is adopted to minimize the objective function. In this algorithm, adding a new implementation phase to the ICA increases searchability and thus enhances the algorithm's efficiency over ICA. The proposed method is first implemented on a standard IEEE 33-bus system. Then, a real network is incorporated to optimize the technical and economic parameters. The analysis and comparison of the results demonstrate the efficacy of the suggested algorithm in the optimal design of the system compared to the original ICA. In this article, we are finally able to bring the voltage profile and voltage stability index of the "Rahdarkhaneh" distribution feeder close to 1 pu and significantly reduce the network losses.

Abstract In this paper, the effect of a battery energy storage system (BESS) as a spinning reserve is considered to control the frequency of a ‎microgrid consisting of a diesel generator, photovoltaic, BESS, and electrical loads. In this stand-alone microgrid, the output power of ‎diesel generators and the BESS are subject to variations to compensate for power fluctuations caused by the load and output power of ‎photovoltaic. Therefore, secondary control, in addition to the primary control, has been proposed to deal with frequency deviation and ‎accelerate the operation of spinning reserve. The scheme is simulated in a hybrid power plant, where results show the effectiveness of the ‎secondary control on frequency deviation damping of the microgrid, thus improving dynamic stability.

Abstract Today, with the expansion of low-inertia (such as wind power plants) and non-inertia (such as ‎photovoltaic power plants) technologies, the amount of network inertia and power related to the ‎primary frequency response has decreased significantly. As a result, in the event of ‎disturbances, the frequency changes with a relatively higher slope and it may violate its ‎permissible range. To solve this problem, several methods have been presented so far that ‎create artificial inertia by power electronic converters connected to storage devices or ‎renewable generation. Therefore, the models make the operation of these sources similar to ‎traditional power plants and increase their contribution to the frequency response during ‎storage contribution events. In this paper, the sensitivity analysis of energy storage contribution ‎to providing inertia for the primary frequency response has been carried out. IEEE 3-bus and ‎‎118-bus networks are used as test networks. MATLAB software is also adopted for ‎optimization. The results show the impact of each storage parameter on the frequency response ‎and how it is possible to meet the frequency response limitations of the network by managing ‎the storage devices.‎

Abstract The Power Quality (PQ) issue refers to the occurrence of irregular voltage, current, or frequency that leads to failure or incorrect functioning of equipment used by end users. The PQ meter is utilized to monitor a diverse range of power supply characteristics, all of which possess the capacity to impact the effectiveness of both operational procedures and machinery. The dynamic voltage restorer (DVR) performs the role of a specialized power device employed to mitigate the voltage drop experienced at the terminal of a sensitive load. DVR can be controlled by various control designs. This work conducts a comparative analysis on a normally managed voltage system and a medium-power DVR controlled by a neural network (NN), fuzzy logic (FL), or adaptive neuro-fuzzy inference system (ANFIS) by utilizing an output voltage regulator. The identification and rapid compensation of voltage perturbations, such as voltage sag, are essential elements in monitoring and controlling DVRs. The conventional PI controller is commonly employed in regulating DVRs. While the traditional controller possesses certain merits, it is not free of limitations. One such downside pertains to its utilization of constant gains, which can impede its capability to provide optimal control performance in instances where system parameters undergo fluctuations. Possible solutions have been proposed to effectively tackle this issue, such as the use of NNs, FL, or ANFIS controllers. Furthermore, to attain both rapid dynamic response and robustness, a modified d-q converted three-phase voltage regulator was adopted. Instead of employing a conventional three-phase regulator, this particular regulator is operated by means of an NN, FL, ANFIS, or PI controller. The suggested voltage regulator offers a prompt solution for rectifying voltage irregularities, such as voltage sag, by promptly restoring the voltage to the nominal magnitude. The primary source of power adopted in this study is a wind turbine unit.

Abstract Environmental concerns, advancements in the new energy industry, and rising power generation and transmission costs are driving the electricity industry towards innovation. This has led to the installation of distributed energy resources (DERs) in many regions. Virtual power plants (VPPs), which manage decentralized energy systems by aggregating the capacity of various distributed generations (DGs), storage devices, and distributable loads, are used for trading energy and services. The research focuses on the planning of price-based unit commitment (PBUC) managed by VPPs over a 24-hour period. Simulation results demonstrate that the proposed framework effectively develops strategies for VPP market production and consumer interaction, especially with load-shedding capabilities. A key aspect of the study is examining the impact of uncertainties on VPP strategies. Probability density functions and the Monte Carlo method are used to model and assess these uncertainties. Simulations without energy price and demand uncertainties indicate that the model is suitable for strategizing VPP market production and consumer interaction. However, simulations that include market price uncertainties and predicted VPP loads show that VPP profits are influenced by market volatility. Increased price and demand fluctuations significantly affect VPP strategies, sometimes resulting in losses during certain periods.

Abstract Cryptocurrency mining requires high consumption power. In recent years, because of the increase in the price of cryptocurrencies and due to the cheap price of electricity in Iran, mining Bitcoin and other cryptocurrencies has been very profitable. Some miners are legally engaged in cryptocurrency mining, but many miners do it illegally and without permission. Since cryptocurrency mining is an operation that consumes a lot of electricity, it is one of the reasons for the lack of electricity, especially in the summer season, and it has caused power outages and financial losses to various industries. In this paper, different methods of detection of illegal mining are reviewed. In this research, by collecting the small number of researches done in the world, a comprehensive study of this issue has been tried. The methods of identifying miners and related consumers are divided into several different categories. Some of them are based-on data mining and mostly to identify consumers who use the output of the converter for the miner device. The second category is related to people who illegally get their electricity from behind the meter or unmetered branches, which are much more difficult to identify than the first type. These methods will be mentioned more in this article. Finally, some suggestions are provided for better identification of these consumers. Furthermore, at the end of the paper, some renewable and new sources of electrical power are discussed for using as an electricity power for miners instead of traditional fossil fuel and gas planes.