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The production and consumption of non-renewable energy resources have disrupted the environment's biodiversity cycle. Global climate change, including worldwide warming, has made human life both now and in the future. The construction industry in the world has a significant share in the demand for energy consumption in these challenges. Therefore, the primary purpose of this paper is to implement standards to save and prevent energy loss to control and limit the demand for energy requested from the power network. Constructing a building with self-sufficient energy production that meets its energy needs by producing clean energy becomes more important. It also sells the excess energy to the grid, known as zero energy buildings. In the present paper, the issue is a constrained optimization problem that aims to minimize the total annual cost, including the initial investment cost for PV and batteries and their maintenance costs, as well as the cost of network exchanges. Among the limitations, the proposed model can mention the restrictions governing the battery, such as the limitations of the battery state of charge (SoC). The problem under optimization is a mixed integers nonlinear programming (MINLP) that will be solved by a particle swarm optimization (PSO) algorithm considering the total cost minimization.

This paper mainly focuses on investigating a stochastic energy management approach to enhance reliability of the networked microgrids within a smart island. In this regard, a networked microgrid is considered in the smart island, which is integrated with a multi-Energy Hub (multi-EH) system aiming to simultaneously support the electrical, thermal, and water demands of the island, isolated from the main grid. The objective function is organized as the cost of operation and reliability of the networked microgrid and is solved using a modified bat algorithm. The uncertainty of stochastic parameters is modelled using the 2-m point estimate method, which has notable advantages in terms of accuracy and simplicity of implementation. Different scenarios are considered both in critical and normal conditions to evaluate the performance of the studied model. Both GAMS and MATLAB software's were employed to study the proposed model. The proposed model improved the reliability of the networked microgrid system and results reveal that the proposed cooperative approach could decrease total operation and investment cost of the networked microgrid by 13%. [ABSTRACT FROM AUTHOR]

In order to prevent wastage of generated power of renewable resources, the energy storage systems can be utilized in the stand‐alone micro grids to store the excess produced power of the renewable generation units. When the generated power of the renewable resources is less than the required load, the energy storage systems can help to compensate all or part of the power shortage. In the current study, a stand‐alone micro grid including wind and tidal turbines, PV systems, batteries and fuel‐based generation units is considered to supply the required load of the micro grid. The generated power of each dispatch‐able generation units is determined in such a way as to minimize the operating cost. In the operating cost of the micro grid, the operating cost of the fuel‐based generation units and the reliability cost associated to the penalty of the curtailed loads are considered. To calculate the reliability cost of the micro grid, a comprehensive reliability evaluation of the micro grid considering the resource‐dependent failure rates for all composed components is performed. To study the effectiveness of the proposed reliability‐based scheduling approach, the numerical results associated to a stand‐alone micro grid containing wind, tidal, PV and fuel‐based generation units connected to the batteries are given. [ABSTRACT FROM AUTHOR]

Various wind turbines have been manufactured for converting wind power into electric energy. They are fixed speed concepts with squirrel cage induction generators, limited variable speed concepts with wound rotor induction generators, variable speed concepts with double fed induction generators, direct-drive concepts with electrically excited synchronous generators and gearbox-free concepts with permanent magnet induction technologies. The composed components and the power curve of these technologies are different and to select an appropriate wind turbine for a wind site, in addition to the economic parameter, reliability criterion must be considered. To address this, a reliability model is developed in this paper that considers both component failure and the unpredictable nature of wind speed for different types of wind turbines. The optimal state number of reliability presentations is determined using XB index calculation and fuzzy c-means clustering method to create multi-state presentations for wind turbines. The proposed approach can be used to determine the most reliable wind turbine for a given wind site by assessing the adequacy of the electric network containing various types of wind turbines. The approach's effectiveness is demonstrated through adequacy assessments of the RBTS and IEEE-RTS, which contain various types of wind turbines. [ABSTRACT FROM AUTHOR]

A run‐of‐the‐river power plant is a renewable energy source used for electricity production. Its power output depends on the varying water flow rate over time, which can impact the reliability of the electric network. Previous research has not studied the effects of water flow rate and temperature variations on the hazard rate of the plant's components. This paper addresses this gap by investigating the impact of these variations on the reliability of electric networks with run‐of‐the‐river power plants. The analysis considers the hazard rates of the plant's components, incorporating the relationship between hazard rate and temperature based on the Arrhenius law. Parameters such as power output, current, power loss, operating temperature, and hazard rate are calculated for different water flow rates and ambient temperatures. Numerical simulations on a test system are conducted to examine the influence of water flow rate and temperature on the reliability indices of the electric network. The results demonstrate that water flow rate and temperature significantly affect the hazard rates of run‐of‐the‐river power plants. This highlights the need to consider these factors in the reliability analysis of electric networks incorporating these renewable resources. [ABSTRACT FROM AUTHOR]

The use of underground XLPE cables in power systems is increasing due to the problems associated with overhead lines. However, insulation failure, primarily caused by partial discharge (PD) phenomenon, remains a major concern. Monitoring the insulation condition of XLPE cables, particularly the magnitude and trend of PDs, is crucial. Detecting and localizing PDs online pose a significant challenge due to the presence of various environmental noises that must be eliminated. In recent years, power systemintroduced noises like impulse noises generated by power electronic devices have become prevalent. Therefore, effective de-noising techniques are required to filter out the noises and interferences from the detected PD signals. This paper proposes the use of wavelet transform, which encompasses both time and frequency domains, to remove various noises from PDs, considering their non-stationary nature. To determine the suitable mother wavelet transform, threshold, and number of decompositions, experimental tests are conducted to investigate the characteristics of PD signals in the cables. Additionally, background noise at the measurement site, which varies in substations, is recorded as reference noise for the wavelet-based noise removal process. Using MATLAB software, reference noises and noisy PD signals are measured in substations, and the de-noising process is executed. The proposed method is evaluated on a sample cable, and the results are discussed. Furthermore, the method is applied to detect PD signals in multiple 20 kV substations in Iran, utilizing high-frequency current transformers connected to shield wires, oscilloscopes with high-frequency bandwidth, and MATLAB software. [ABSTRACT FROM AUTHOR]

A suitable mixture of renewable resources including wind, tidal and photovoltaic units can be used in the microgrids installed in coastal areas or islands. However, the variation in the renewable resources such as wind speed, tidal current speed and solar radiation is significant that affects the reliability performance of these microgrids. Thus, to accurately evaluate the reliability of the microgrids, the failure rate of composed components affected by the variation in the renewable resources must be considered. To study the impact of variation in the temperature and renewable resources on the failure rate of components, different equations including Arrhenius law, temperature modification factor, fatigue strength, bending and contact stress, limit state function of turbine, thermal loss of semiconductor devices, the temperature rise of transformer and cable, the temperature coefficient of voltage and power of photovoltaic panels are developed. According to the developed equations, the components failure rate, and consequently the failure rate of the microgrid considering the variation in the temperature and renewable resources are determined. Then, by simulation, the impact of different energy sources on the failure rate of the whole system is evaluated and the reliability in a microgrid consisting of offshore renewable energy sources will be studied. [ABSTRACT FROM AUTHOR]

As an independent unit, microgrid operator (MGO) should respond to the energy demand of customers with an optimal provision cost. Apart from the ability to guarantee the security of microgrid (MG) operation, the MGO should consider the greenhouse emission effects as well. This paper investigates a novel energy management system for an islanded MG. In the proposed strategy, two efficient methodologies are used to maximize the profit and security of the MG: (a) the optimal operation of electric vehicles (EVs) in vehicle‐to‐grid (V2G) mode and (b) the use of demand response (DR) program. Besides, a hierarchical control structure is proposed to manage frequency and voltage uncertainties in a permissible range. Improving the reliability of the MG is another goal of the proposed strategy, which is pursued by the studied controlling framework. The proposed approach is evaluated through a set of simulation and GAMS tests. Results indicate that the frequency deviation of the MG is damped through the proposed management strategy and place the spotlight on the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

In recent years, renewable resources, especially large‐scale wind farms, are increasingly used to generate clean electricity in modern power systems. The penetration level of these power plants is significant, and due to the variation in the wind speed resulting in the variation in the generated power, different aspects of power systems, especially reliability, may be affected that must be studied. Reliability evaluation of power system considering large‐scale wind farms is dependent on two factors: the failure rates of composed components including turbine, generator, electrical converters, transformer, and cable and the variation in the generated power arising from variation in the wind speed. In this paper, dependency of different component failure rates on the wind speed variation is considered, and using the Monte Carlo simulation, reliability evaluation of power systems containing large‐scale wind farms is performed. A wind farm equipped with the permanent magnet synchronous generator is considered, and the failure rate of composed components considering wind speed variation is determined. Based on the wind speed‐dependent failure rate associated with the components of energy conversion system, the important reliability indices of Roy Billinton test system including loss of load expectation and expected energy not supplied are calculated. [ABSTRACT FROM AUTHOR]