Security Of Power Supply Research Articles

Situation awareness method of the distribution network based on EMD-SVD and Elman neural network

In order to ensure reliability and security of power supply, the situation awareness of some elements in the distribution network is studied in this paper. Considering the influence of the interference signal, Empirical Mode Decomposition (EMD) is introduced to reduce it. Subsequently, according to operation characteristics of the actual distribution network, several evaluation indexes are proposed to describe the operation situation of the overall distribution network and internal elements, especially evaluation of fragile nodes. Based on these indexes and characteristics of actual distribution network, the comprehensive evaluation method of fragile nodes (CEMFN) is constructed, which mainly aims at the fragile nodes in the distribution network and synthesizes the single index coefficient to realize the identification of fragile nodes. Through the simulation calculation, it can be seen that the result of CEMFN is more accurate than that of the traditional evaluation model, which provides an important theoretical support for the operation and maintenance of distribution network and reliable power supply.

The Contribution of Small Modular Reactors to the Resilience of Power Supply

In recent years, there has been a growing interest in the design, development and commercialization of nuclear power Small Modular Reactors (SMRs). Actual SMR designs cover the full spectrum of nuclear reactor technologies, including water-, gas-, liquid-metal-, and molten-salt-cooled. Despite physical and technological differences, SMRs share some relevant design features, such as small size, modularity, inherent and passive safety systems. These features are expected to enhance availability, recoverability, promptness and robustness, thereby contributing to the resilience of power supply. Thanks to the peculiar design features of SMRs, they are likely to satisfy a number of Functional Requirements (FRs) for this objective, namely: (i) low vulnerability to external hazards; (ii) natural circulation of primary coolant; (iii) prompt, unlimited and independent core cooling under shutdown conditions; (iv) shutdown avoidance in response to variations of the offsite power supply quality and electrical load; (v) island mode operation; (vi) robust load-following; (vii) independent, self-cranking start. These make advanced Nuclear Power Plants (aNPPs) comprised of SMRs perfect candidates to withstand a broader range of natural disruptions and to recover faster from them, compared to conventional Nuclear Power Plants (cNPPs), thus rendering them a major potential asset for guaranteeing resilience and security of power supply. The review focuses on Natural Technological (NaTech) events that impact a typical Integrated Energy System (IESs) within which SMRs are embedded: IESs are, indeed, being developed to integrate different power generation plants with gas facilities, through gas and electricity infrastructures, because they are expected to bring increased security and resilience of power supply, as shown in the qualitative case study presented.

Low-Carbon Transformation of Electric System against Power Shortage in China: Policy Optimization

The low-carbon transition of the power system is essential for China to achieve peak carbon and carbon neutrality. However, China could suffer power shortages due to radical policies in some extreme cases. The gap between power demand and supply from March 2021 to November 2021 ranged between 5.2 billion kW·h and 24.6 billion kW·h. The main reason for the power shortage was over-reliance on renewable energy and insufficient coal power supply for the power system. The low-carbon transformation path of the electric system needs to be explored with more flexibility for power security. This study applied a modified LEAP model and carried out a forecast analysis of thermal power generation and installed capacity in 2025 and 2030 under normal and extreme weather scenarios. The results suggested that: the installed capacity of thermal power will need to account for about 44.6–46.1% of power generation in 2025 and 37.4–39.3% in 2030, with the assumption of power shortages caused by the instability and uncertainty of renewable power. In the future, China needs to pursue the development of diversified energy sources and enhance the power supply security capability while strengthening the development and utilization of renewable energy.

IGDT-based dynamic programming of smart distribution network expansion planning against cyber-attack

Power supply security is the vital driver in advent and development of the smart distribution networks (SDNs). Traditionally, SDN expansion planning (SDNEP) is used to identify the size, site, and time of the installation of new equipment or replacement of the pre-existent facilities to optimally satisfy electricity load demand that is increasing every year appropriately and cost-effectively while dealing with all the technical and operational constraints and needs. In SDNs, communication has a crucial role, but, cyber-physical security of the communication system is exceedingly vulnerable to cyber-attacks (CAs), especially in the consumer's sector. So, this paper aims to propose an approach for designing cyber-secure SDN (CSDN) by considering the problem as a dynamic model of tri-level cyber-secure SDNEP (CSDNEP) program. The procedure includes the design of SDN as ameshed topology equipped by multi-type switching devices, utilization of multi-type distributed generations, and demand response. The chaotic status of renewable resources, load and its market price, and ZIP modeling well incorporate into the problem. Also, for evaluation of different CSDNEP strategies, a risk-based method pivoting on information gap decision theory (IGDT) is applied. To size up the efficiency of CSDNEP, computer simulation is carried out on a large scale SDN and the results are touched upon.

Developments in Nanoparticles Enhanced Biofuels and Solar Energy in Malaysian Perspective: A Review of State of the Art

The rapid rise in global oil prices, the scarcity of petroleum sources, and environmental concerns have all created severe issues. As a result of the country’s rapid expansion and financial affluence, Malaysia’s energy consumption has skyrocketed. Biodiesel and solar power are currently two of the most popular alternatives to fossil fuels in Malaysia. These two types of renewable energy sources appear to be viable options because of their abundant availability together with environmental and performance competence to highly polluting and fast depleting fossil fuels. The purpose of adopting renewable technology is to expand the nation’s accessibility to a reliable and secure power supply. The current review article investigates nonconventional energy sources added with nanosized metal particles called as nanomaterials including biodiesel and solar, as well as readily available renewable energy options. Concerning the nation’s energy policy agenda, the sources of energy demand are also investigated. The article evaluates Malaysia’s existing position in renewable energy industries, such as biodiesel and solar, as well as the impact of nanomaterials. This review article discusses biodiesel production, applications, and government policies in Malaysia, as well as biodiesel consumption and recent developments in the bioenergy sector, such as biodiesel property modifications utilizing nanoparticle additions. In addition, the current review study examines the scope of solar energy, different photovoltaic concentrators, types of solar energy harvesting systems, photovoltaic electricity potential in Malaysia, and the experimental setup of solar flat plate collectors (FPC) with nanotechnology.

Moguća uloga hidrosistema „Lim-Zapadna Morava“ u obezbeđivanju elektroenergetske, privredne i društvene sigurnosti i stabilnosti u Srbiji

Increased climate changes and environmental pollution cause a decrease of available quality water quantities and increase differences in precipitation amounts by seasons. The question is how to provide sufficient quantities of water to supply the population, agriculture, industry, and electricity generation. Sources of quality water are most often located in areas far from the centers of consumption, so it is necessary to construct large water management systems. In order to mitigate the variations in the available quantities of water during the year, reservoirs of significant, seasonal capacity must be built. The power system stability is additionally endangered by the growing impact of renewable sources with extremely variable electricity generation, which is manifested both on an intraday and seasonal level. Therefore, seasonal accumulations, with multi-purpose and even multiple use of the same amount of water, represent a winning option and a stronghold on which power supply, economic and social security and stability should be built. In the case of Serbia, apart from seasonal ones, there are also a spatial differences in the quantities and quality of water in the river basins. In the areas of Zapadna and Velika Morava, Šumadija, Kolubara and Belgrade, the required quantities of water for the supply exceed their own resources. On the other hand, the Drina basin is rich in water of significantly higher quality, and the possibilities of leveling the waters of river Lim are extremely limited. This paper reaffirms the old idea of building a multi-purpose hydro system „Lim-Zapadna Morava“, which would solve these problems. Beside those in power industry, other positive effects that would be achieved by the realization of this strategic project are also presented in this paper.

CECRE: Supervision and Control of Spanish Renewable Energies in the Last 15 years

From its commissioning in 2006 to the present, the Spanish Control Centre for Renewable Energies (CECRE) has been a worldwide pioneer and reference centre in the integration of renewable energies in the electrical system. In the last 15 years, CECRE has allowed a high penetration of renewable energies in Spanish electrical system by means of the supervision and control of renewable facilities, while ensuring the power supply security. This paper defines the bases of renewable energy operation in CECRE and introduces forecasting systems for renewable energies. Furthermore, this paper describes the participation of renewable energies in balancing services and congestion management. Finally, new challenges for Spanish transmission system operator (TSO) are presented for the integration of renewable energies along with the energy transition and decarbonization.

A panel empirical modeling on the driving factors of provincial electricity consumption in China.

This study aims to explore the relationships between electricity consumption and per capita GDP, urbanization rate, and the proportion of tertiary industry in China during 2005-2018. The results demonstrate that electricity consumption and its determinants are cointegrated. Then fully modified ordinary least square (FMOLS) and fixed effect with varying coefficients and intercept techniques are used to explore the relationships. The empirical results show that all three factors positively affect electricity consumption, per capita GDP has exerted positive impacts on electricity consumption in the 28 provinces, urbanization rate also contributes a positive influence on electricity consumption in 29 provinces, while the positive effect of the proportion of tertiary industry emerges only in 10 provinces. Meanwhile, the urbanization rate makes the most considerable contribution to electricity consumption, while the proportion of the tertiary industry is the least essential determinant. The panel causality results reveal that per capita GDP and urbanization rate cause electricity consumption in the short run and per capita GDP and electricity consumption Granger cause each other in the long run. Finally, we propose policy implications including enhancing the security and reliability of power supply and optimizing the structure of electricity consumption in different industries in China.

Efficiency analysis for performance evaluation of electric distribution companies

In power systems, the electricity distribution sector requires proper regulation to guarantee power supply security, electricity tariffs modicity and universal service to customers. Generally, electric utilities operate differently and are distinguished in terms of costs, quality of supply, market and network size, and other aspects, that affect their efficiency. In this context, the Data Envelopment Analysis has been used in electricity distribution regulation to define efficiency scores and compare practices. The Data Envelopment Analysis application sometimes comes with weight restrictions and negative variables that modify the original methodology which affects the efficiency scores. The main goal of this paper is to evaluate weights restrictions influence on efficiencies results and to perform a sensitivity analysis of efficiency scores using additional benchmarking techniques. We apply the Cross-Efficiency Analysis and the Ratio-based Efficiency Analysis benchmarking methods, in order to provide relevant quantitative information to compute relative efficiency scores and perform peer evaluations among utilities even if they are outside of the efficient frontier. The Brazilian electricity distribution system is selected as study case. Brazil has strong diversity in terms of economic development, climate and geography, and the current procedure adopted by the regulator determine efficiency metrics for all distribution companies based on their operation cost. Results from our analysis show that the diversity of concession areas significantly influence the stability of efficiency scores. Moreover, considering the approach proposed here it is possible to identify an efficiency relationship among all the distribution companies and not only using the ones that are in the efficiency frontier.

Optimal sizing of off-line microgrid via hybrid multi-objective simulated annealing particle swarm optimizer

In this paper, a simple and efficient hybrid Simulated Annealing Particle Swarm (SAPS) algorithm is proposed to determine the optimal size of a Microgrid (MG) that guarantees economically and reliable operation of the off-line mode and/or on-line mode of the MG. The proposed SAPS optimizer considers the intermittent nature of renewable energy sources (RESs) while boosting the power supply security/stability. Batteries are resized to enhance the power supply reliability and acting as virtual synchronous inertia. During disturbances/fault circumstances, the primary frequency control is provided by batteries and diesel generators. The constraints are set to achieve higher levels of power supply security and frequency stability. Qena AL-Gadida (QA) city is the MG under concern. The SAPS results are validated versus Simulated Annealing (SA) and Particle Swarm Optimization (PSO). The results revealed the reliability and applicability of the proposed sizing procedure. Moreover, adopting the primary frequency regulation of batteries resulted in a slight increase in the overall costs.

Evaluation of hierarchical controls to manage power, energy and daily operation of remote off-grid power systems

Integration of locally available renewable energy sources and energy storage have proven to be a cost-effective and eco-friendly retrofit for the primarily diesel-based remote off-grid power systems. However, in the presence of multiple sources and energy storage, the energy management and power management mechanisms must be properly designed to enhance their envisioned benefits while assuring stability, availability, and security of power supply. This paper presents a hierarchical controller equipped with both energy management and power management strategies to obtain an optimum and stable system operation subjecting remote off-grid power systems. An operation evaluation framework is deployed to assess the applicability of the derived optimum operational routines as well as to verify the competence of the low-level controls. Results are demonstrated for a remote off-grid PV-Diesel-Battery power system under different diurnal and seasonal variations. Results revealed the competence of incorporated power management strategies as well as the use of proposed operation evaluation mechanism in identifying certain risks associated with optimum operational routines derived through energy management systems. The overall study confirmed that a coordinated control and operation evaluation platform is required to achieve a logical and quantitatively optimized operational trajectory.

Three-Phase State Estimation for Distribution-Grid Analytics

Power-distribution grids consist of assets such as transformers, cables, and switches, of which the proper utilization is essential for the provision of a secure and reliable power supply to end customers. Distribution-system operators (DSOs) are responsible for the operation and maintenance of these assets. Due to the increased use of renewable sources such as wind and solar, grid assets are prone to operation conditions outside safe boundaries, such as overloading, large voltage unbalance, and a rise in voltage. At present, distribution grids are poorly monitored by DSOs, and the above-mentioned problems may thereby go unnoticed until the failure of a critical asset occurs. The deployment of smart meters in distribution grids has enabled measurements of grid variables such as power, current, and voltage. However, their measurements are used only for billing purposes, and not for monitoring and improving the operating condition of distribution grids. In this paper, a state-estimation algorithm is proposed that utilizes smart-meter data for offline analysis, and estimates the loading of grid assets and power losses. Single- and three-phase state-estimation algorithms are compared through simulation studies on a real-life low-voltage distribution grid using measured smart-meter data. The three-phase state-estimation algorithm based on the nonlinear weighted least-squares method was found to be more accurate in estimating cable loading and line power losses. The proposed method is useful for DSOs to analyze power flows in their distribution grids and take necessary actions such as grid upgrades or the rerouting of power flows.

Philippine Electricity Power Market Supply Options: Challenges and Policy Implications for Greening Economic Growth, Climate Resiliency, and Low Carbon Future

Over the past few years, energy security and sustainable development have moved up the global agenda. Energy is what makes an economy run. There is a strong correlation between economic development and energy consumption. Energy security plays an important role in all economic sectors in attaining the long-term vision of inclusive economic growth and development of the economy. The attainment of this vision is difficult as it is challenged by the need to build energy infrastructures that are not only responsive to the growing demand but can withstand the maximum credible natural disaster. One of the primary objectives of sustainable development is to make people without access to enough energy be able to meet their needs through the provision of stable, reliable, clean, safe, and affordable energy services. This research will use the Granger Causality test to analyze the causal relationship among the endogenous variables among (1) GNI per capita; (2) GHG Emissions; and (3) Herfindahl-Hirschman Index (HHI) between energy-economic development and the influencing factors of power supply security indicators. In the end, this paper expects to suggest that the paper electric power development plans in the country also have implications for the path that would lead the country to what is known as a green economy. It is in this background that energy security and economic growth development are intertwined by public policy. In a broader development sense, public policy draws in the active involvement of the community in identifying problems. Anchored deeply in the national development agenda, the local community develops its own sets of development goals and pushes itself towards realizing this long-range vision. 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Application of Intelligent Sensor Technology in Steady State Operation of Power System

Wireless sensor network technology is a new monitoring technology to ensure the stable and safe operation of power system. The network has many advantages: light weight, corrosion resistance, high temperature resistance and so on, which can effectively solve the measurement problems that conventional detection technology can not afford. With its unique physical properties, the sensor technology has a relatively broad application prospect in power system. This paper focuses on the main development achievements of wireless sensor technology, and analyzes its application in power system. This paper focuses on the key technologies in the implementation of WSN. This paper discusses the routing of WSN, low power algorithm of nodes, channel deployment, antenna selection, power supply and network security. At the same time, this paper implements the low-power algorithm of the node. The node can run stably for a long time without outside interference. In this paper, through the research on the key technology of theory, the WSN technology is applied to the field investigation and verification of distribution communication network and transmission line condition monitoring, which can be used as the main technical means of the last kilometer network in the power communication terminal network planning. WSN has a broad application prospect in power system.

Coordinated Control Strategy of CU-MTDC under Abnormal Conditions Considering Power Supply Security

The coastal urban multi-terminal DC (CU-MTDC) is a prospective solution for enhancing the power supply security of the coastal urban power (CUP) grid and integrating the large-scale offshore wind farm. However, the large DC disturbances may significantly impact the CUP power supply security. The existing DC unbalanced power distribution methods are difficult to be applied in the CU-MTDC because of the complicated optimization process and the expansion of the influence range of a DC fault. To solve the above problems, this paper proposes a coordinated control strategy of CU-MTDC under abnormal conditions. First, calculation principles for the active power reference of center coastal urban power (CCUP) grid converters are proposed. Second, a DC unbalanced power coordinated distribution strategy under abnormal conditions is used based on the dynamic priority control to ensure power supply security of the critical AC lines. Third, the controller parameters of CCUP grid converters are calculated. Through a simple control process, the number of the regulation converters is dynamically scheduled according to the DC unbalanced power. The DC fault influence range on the urban power grid can be limited in a sufficiently small area. Simulation verified the effectiveness of the proposed control strategy.

A robust decision-support method based on optimization and simulation for wildfire resilience in highly renewable power systems

Wildfires can pose a major threat to the secure operation of power networks. Chile, California, and Australia have suffered from recent wildfires that have induced considerable power supply cuts. Further, as power systems move to a significant integration of variable renewable energy sources, successfully managing the impact of wildfires on the power supply can become even more challenging due to the joint uncertainty in wildfire trajectories and the power injections from wind and solar farms. Motivated by this, this paper develops a practical decision-support approach that concatenates a stochastic wildfire simulation method with an attacker-defender model that aims to find a worst-case realization for (i) transmission line and generator contingencies, out of those that can potentially be affected by a given wildfire scenario, and for (ii) wind and solar power trajectories, based on a max-min structure where the inner min problem represents a best adaptive response on generator dispatch actions. Further, this paper proposes an evaluation framework to assess the power supply security of various power system topology configurations, under the assumption of limited transmission switching capabilities, and based on the simulation of several wildfire evolution scenarios. Extensive computational experiments are carried out on two representations of the Chilean power network with up to 278 buses, showing the practical effectiveness of the proposed approach for enhancing wildfire resilience in highly renewable power systems.

WTA-WTP Disparity: The Role of Perceived Realism of the Valuation Setting

Based on a survey among more than 5,000 German households and a single-binary choice experiment in which we randomly split the respondents into two groups, this paper elicits both households' willingness to pay (WTP) for power supply security and their willingness to accept (WTA) compensations for a reduced security level. In accord with numerous empirical studies, we find that the mean WTA value substantially exceeds the mean WTP bid, in our empirical example by a factor of 3.56. Yet, the WTA-WTP ratio decreases to 2.35 among respondents who believe that the hypothetical valuation setting is likely to become true. Conversely, the WTA-WTP ratio increases to 3.81 among respondents who deem the setting unlikely. On the basis of these results, we conclude that inquiring about respondents' perception of the realism of the valuation setting is an easy-to-implement and promising survey element to mitigate excessive WTA-WTP disparities, particularly if private or quasi-public goods are under scrutiny.

The dynamic effects of renewable-energy and fossil-fuel technological progress on metal consumption in the electric power industry

This paper used the systematic generalised method of moments (SYS-GMM) to investigate the dynamic heterogeneous effects of renewable-energy technological progress (RETP) and fossil-fuel technological progress (FFTP) on the consumption of 10 metal materials from 1996 to 2016. The findings indicate strong evidence that the technological progress of the electric power industry exhibits a strong metal consumption effect. Specifically, both RETP and FFTP significantly increase the consumption of base metals such as iron, chromium, aluminium, copper, lead, nickel and zinc, while the consumption of critical metals such as indium, neodymium and dysprosium is mainly due to RETP. Additionally, we also found that RETP is the main contributor to metal consumption in the electric power industry in countries dominated by fossil fuel electric power generation. In contrast, in the group of countries dominated by renewable energy electric power generation, RETP and FFTP work together to increase the consumption of metal materials. The dynamic heterogeneous consumption effects of different types of technological progress on different types of metals in the electric power industry provide effective policy support for national low-carbon electric power supply and metal mineral resource security strategies.

Fault location in distribution system using convolutional neural network based on domain transformation

Distribution lines are integral parts of the modern power system, which can affect the security and stability of power supply directly. An effective power system protection scheme should be able to detect all occurring faults as soon as possible. There are two tasks in fault diagnosis. One is the fault classification, where high accuracy rates have already achieved. Thus, this paper focuses on the other task, i.e. fault location. Enlightened by Fourier transform, this paper proposes an online data-driven method, which transforms signals from time domain to image domain through signal-to-image (SIG) algorithm and then process the transformed images with framework based on convolutional neural network (CNN). On the one hand, we can extract more crucial characteristic and information from image domain. On the other hand, the CNN-based structure is much smaller than others. It needs less memory space and would be easier to be transplanted to hardware platform. Moreover, the proposed algorithm does not require synchronous devices. The numerical comparison shows that the proposed SIG-CNN fault location model achieves robust and accurate results compared with other data-driven algorithms.

Short-Term Wind Power Forecasting Using R-LSTM

Renewable energies such as wind and solar begin receiving remarkable popularity in accordance with the energy demand, expeditious expansion of solar and wind energy generation involves acute forecasting of wind and solar power, so in past and recent years it has become an intensive research area. An accurate forecast of wind power to maintain an affordable, secure, and economical power supply is most significant. Numerous investigations and research have been performed in this area in recent years. This research article aims to develop a short-term wind power forecasting model to improve the accuracy of the prediction. Therefore, a novel approach based on LSTM (Long Short-Term Memory) is proposed to forecast from 1 to 6 hours ahead of wind power. A recursive strategy is used when predicting short-term wind power, unlike the conventional LSTM approach. The proposed model is implemented using historical generated wind power data for Gujarat state. A comparative analysis is performed between the proposed and existing approach presented in the literature, from the analysis, it is noted that the proposed R-LSTM (Rolling-LSTM) model outperformed with minimal error and better accuracy.