Technical and Economic Assessment for using Ground-Source Heat Pumps in Commercial and Institutional Buildings

One of the most important methods proposed for reduction of consumed energy in facility and ventilation systems in a building is application of ground source heat pumps (GSHPs). With regard to the enhanced use of such pumps in providing heat and cold demands in homes, commercial centers, institutions and industrial buildings analysis of their performance as well as their benefits and deficiencies compared to common ventilation systems have gained interest of many researchers. Such systems apply ground as a thermal well in summer and as a heat source in winter. They can be used in various climatic conditions in different regions. They have no combustion and they only transfer heat. In the present article first, performance conditions of ground source heat pumps (in two modes of heating and cooling) are analyzed. Then in order to assess the performance of proposed model economically, its application in Iran will be studied. Finally after introducing the proposed plan and by concluding the overall results the return time for investment will be estimated. The obtained results from graph analysis would indicate the superiority of proposed model over other plans and also it provides an appropriate general context for the researchers for a better understanding and examining this system in comparison to other systems.DOI:http://dx.doi.org/10.11591/ijece.v2i4.146

Security Technology by using Firewall for Smart Grid

Due to the increasing development of computer systems and information networks, power grids should change extensively too. Nowadays, substantial movement has begun to implement the Smart Grid industry around the world. Since with the creation of smart electricity grids, it is possible to access the internal network from the external spaces, it is also necessary to protect information and data against unauthorized access. Therefore, a firewall should be used for information security. The firewall based on existing security regulations, decides which data is incoming to the network or going out of the network. Considering the discussions of passive defense topics at the national level and also the high importance of information security in Smart Grids, in this paper, in addition to examining the Firewalls, its advantages and disadvantages are also stated. Although the firewall has a major role in establishing security, and its installation and appropriate configuration can only be one of the primary activities in this field, we should also take advantage of other security mechanisms to enhance the security of the Smart Grid

Security Technology by Using Firewall for Smart Grid

Due to the increasing development of computer systems and information networks, power grids should change extensively too. Nowadays, substantial movement has begun to implement the Smart Grid industry around the world. Since with the creation of smart electricity grids, it is possible to access the internal network from the external spaces, it is also necessary to protect information and data against unauthorized access. Therefore, a firewall should be used for information security. The firewall based on existing security regulations, decides which data is incoming to the network or going out of the network. Considering the discussions of passive defense topics at the national level and also the high importance of information security in Smart Grids, in this paper, in addition to examining the Firewalls, its advantages and disadvantages are also stated. Although the firewall has a major role in establishing security, and its installation and appropriate configuration can only be one of the primary activities in this field, we should also take advantage of other security mechanisms to enhance the security of the Smart Grid

Attributes of Big Data Analytics for Data-Driven Decision Making in Cyber-Physical Power Systems

Big data analytics is a virtually new term in power system terminology. This concept delves into the way a massive volume of data is acquired, processed, analyzed to extract insight from available data. In particular, big data analytics alludes to applications of artificial intelligence, machine learning techniques, data mining techniques, time-series forecasting methods. Decision-makers in power systems have been long plagued by incapability and weakness of classical methods in dealing with large-scale real practical cases due to the existence of thousands or millions of variables, being time-consuming, the requirement of a high computation burden, divergence of results, unjustifiable errors, and poor accuracy of the model. Big data analytics is an ongoing topic, which pinpoints how to extract insights from these large data sets. The extant article has enumerated the applications of big data analytics in future power systems through several layers from grid-scale to local-scale. Big data analytics has many applications in the areas of smart grid implementation, electricity markets, execution of collaborative operation schemes, enhancement of microgrid operation autonomy, management of electric vehicle operations in smart grids, active distribution network control, district hub system management, multi-agent energy systems, electricity theft detection, stability and security assessment by PMUs, and better exploitation of renewable energy sources. The employment of big data analytics entails some prerequisites, such as the proliferation of IoT-enabled devices, easily-accessible cloud space, blockchain, etc. This paper has comprehensively conducted an extensive review of the applications of big data analytics along with the prevailing challenges and solutions

Applications of Particle Swarm Optimization Algorithm to Solving the Economic Load Dispatch of Units in Power Systems with Valve-Point Effects

Reduction of operating costs in power system in order to return the investment costs and more profitability has vital importance in power industry. Economic Load Dispatch (ELD) is one of the most important issues in reducing operating costs. ELD is formulated as a nonlinear optimization problem with continuous variables within the power plants. The main purpose of this problem is optimal planning of power generation in power plants with minimum cost by total units, regarded to equality and inequality constraints including load demand and the range of units' power productivity. In this article, Economic Load Dispatch problem has been modeled by considering the valve-point loading effects with power plants' constraints such as: the balance of production and consumption in system, the forbidden zones, range of production, increasing and decreasing rates, reliability constraints and network security. To solve the problem, Particle Swarm Optimization (PSO) Algorithms has been employed. To evaluate the effectiveness of the proposed method, the problem has been implemented on a power system with 15 generating units and the results have been evaluated.DOI:http://dx.doi.org/10.11591/ijece.v4i6.672

Blockchain outlook for deployment of IoT in distribution networks and smart homes

Nowadays, unlike depleting fossil fuel resources, the integration of different types of renewable energy, as distributed generation sources, into power systems is accelerated and the technological development in this area is evolving at a frantic pace. Thus, inappropriate use of them will be irrecoverably detrimental. The power industry will reach a turning point in the pervasiveness of these infinite energy sources by three factors. Climate changes due to greenhouse gas accumulation in the atmosphere; increased demand for energy consumption all over the world, especially after the genesis of Bitcoin and base cryptocurrencies; and establishing a comprehensive perspective for the future of renewable energy. The increase in the pervasiveness of renewable energy sources in small-scale brings up new challenges for the power system operators to manage an abundant number of small-scale generation sources, called microsources. The current structure of banking systems is unable to handle such massive and high-frequency transactions. Thus the incorporation of cryptocurrencies is inevitable. In addition, by utilization of IoT-enabled devices, a large body of data will be produced must be securely transferred, stored, processed, and managed in order to boost the observability, controllability, and the level of autonomy of the smart power systems. Then the appropriate controlling measures must be performed through control signals in order to serve the loads in a stable, uninterruptible, reliable, and secure way. The data acquires from IoT devices must be analyzed using artificial intelligence methods such as big data techniques, data mining, machine learning, etc. with a scant delay or almost real-time. These measures are the controversial issues of modern power systems, which are yet a matter of debate. This study delves into the aforementioned challenges and opportunities, and the corresponding solutions for the incorporation of IoT and blockchain in power systems, particularly in the distribution level and residential section, are addressed. In the last section, the role of IoT in smart buildings and smart homes, especially for energy hubs schemes and the management of residential electric vehicle supply equipment is concisely discussed

Estimating the Potential to Achieve Electrical Energy from Biomass Resources in Iran (A Case Study in Isfahan)

ABSTRACT The IRAN has a significant biomass resource, estimated at an annual 25 million tons, but only a fraction of this is captured effectively for energy, contributing approximately 3.8% of the IRAN's heat and electricity production. Much biomass combustion technology may be considered as mature, although bottlenecks in the quality and quantity of feedstock are apparent, and further fundamental research is required to increase crop yield in a sustainable manner, with low chemical inputs to ensure efficient energy balance. In the short term, it could be useful for the IRAN to focus on developing a limited number of bioenergy chains, linked to combined heat and power micro-generation and the use of bioenergy for community and public sector projects. This should be linked to a joined up policy and regulatory framework. A clear strategy for land management is also required, since many competing uses for land will emerge in the coming decades, including food production, nature conservation, carbon sequestration, urbanization and other forms of renewable energy use. This finite resource must be managed effectively. In the long term future, considerable excitement exists about the possibility of new bioscience technologies harnessed to improve photosynthetic gains for bioenergy, including the use of synthetic biology. It may be possible to produce the designer energy plant whose outputs would include high quality chemical and liquid biofuels. Gasification of biomass also requires further technology development

Artificial Intelligence-Based Power System Stabilizers for Frequency Stability Enhancement in Multi-machine Power Systems

Low frequency oscillations (LFOs) occur in a system of interconnected generators connected by weak interconnection. A power system stabilizer (PSS) is commonly used to improve the capacity of the power system dampening. Under a variety of operating conditions, traditional PSSs fail to deliver superior damping. To address this issue, a Farmland Fertility Algorithm (FFA-PSSs controller) was used to solve an optimization problem for optimal design of PSSs system parameters, and its performance efficiency was compared to GA and PSO-based PSSs controllers. In addition to PSS, flexible current transmission (FACTS) devices are widely used. PSSs controllers and FACTS devices are frequently constructed in tandem to improve the dampening efficiency of the system. In this study, an Interline Power Flow Controller (IPFC) FACTS device will be added to the PSSs controller to improve the power system’s oscillatory stability. PSSs optimal design and supplemental controller of power fluctuations for IPFC were conducted out on WSCC multi-machine test systems using a linear system model. Using time-domain simulations and quantitative analysis, the proposed IPFC model was compared to the FFA-PSSs controller in terms of performance and efficiency. The main disadvantage of this technique is the difficulty in designing a dynamic IPFC model in test systems, as well as the burden of IPFC coordinated PSSs optimization. In both PSSs design using FFA method and FFA-optimized PSS with IPFC cases, rise in the computational and simulation costs was found unavoidable. To compensate for these flaws and obtain the research contribution, this paper proposes a Neuro-Fuzzy Controller (NFC) developed as a damping controller that can take the place of the two controllers (research objectives three). The application of the NFC substitutes the computational and simulation cost involved in designing multi-machine PSS and IPFC-FACTS systems simultaneously. With the availability of NFC in SIMULINK, a dynamic model of the WSCC three-machine system was developed under a variety of operating situations. Quantitative analysis results from the WSCC test system simulation show that when comparing the proposed NFC model to the IPFC model for the WSCC test system, the proposed NFC model was found to be 149 percent and 0 percent efficient in terms of the time to settle of rotor angle respond for G2 and G3, respectively, but 394 percent efficient when compared to the uncontrolled model. The decreased settling time values ensured the proposed NFC model’s efficacy in damping down the LFO and achieving superior stability over the two controllers. The proposed NFC model was shown significant performance improvement in both the transient and steady-state areas than when the system was designed with the two damping controllers

Exploring Social Capital in Situation-Aware and Energy Hub-Based Smart Cities: Towards a Pandemic-Resilient City

Although the severity of the COVID-19 pandemic has appears to have subsided in most parts of the world, nevertheless, in addition to six million deaths, it has yielded unprecedented challenges in the economy, energy, education, urban services, and healthcare sectors. Meanwhile, based on some reports, smart solutions and technologies have had significant success in achieving pandemic-resilient cities. This paper reviews smart city initiatives and contributions to the prevention and treatment of coronavirus disease, as well as reducing its destructive impact, leading towards pandemic-resilient economic and health systems. Furthermore, the situational awareness contributions are reviewed in pandemic-resilient governance. The main contribution of this study is to describe the construction of social capital in smart cities as a facilitator in creating a pandemic-resilient society in crisis through two analyses. Moreover, this research describes smart cities’ energy as interconnection of energy hubs (EHs) that leads to a high level of resiliency in dealing with the main challenges of the electricity industry during the pandemic. Energy-hub-based smart cities can contribute to designing pandemic-resilient energy infrastructure, which can significantly affect resilience in economic and health infrastructure. In brief, this paper describes a smart city as a pandemic-resilient city in the economic, energy, and health infrastructural, social, and governmental areas