Conventional Power Grid Research Articles

Improved Correction Strategy for Power Flow Control Based on Multi-Machine Sensitivity Analysis

Sensitivity analysis is a conventional power grid analysis method that has been widely used in active power safety correction of power systems. This method relies on linearizing the power flow equation, assuming that the control variable change will continue to act on the power system until a new steady-state operating point is reached. However, this method ignores the quasi-steady-state physical response of power equipment to various control operations, which makes the method not suitable for real-time decision-making. Therefore, according to the improved equal and opposite quantity adjustment principle, this paper proposes a practical power flow correction control strategy, that can avoid repeated and inefficient adjustments of the system. In the proposed method, the single-machine sensitivity matrix under the AC power flow model is obtained based on the Taylor series expansion of the power flow equation. Subsequently, the multi-machine sensitivity with no dependence on the choice of the balancing machine is proposed considering the quasi-steady-state method. The study is verified on a practical system, showing that the proposed method has an error of less than 1% with a rapid computation speed. The proposed method satisfies the requirements of real-time analysis and online control strategies, which can provide a more practical approach for active power safety correction.

Research on Influencing Factors of Equipment Asset Performance Evaluation Level of Regional Distribution Network Based on Interpretive Structure Model

The evaluation of equipment asset performance level of regional distribution network is an important link. As the equipment assets of the regional distribution network are affected by many factors, the performance level is low. Based on this, this paper considers 11 influencing factors from the two dimensions of cost input impact and performance output impact, establishes a model of the interpretation structure of the equipment asset performance level of the regional distribution network, and conducts detailed analysis and discussion. The results show that more attention needs to be paid to key factors such as the emission reduction rate of coal-to-electricity projects, annual conventional power grid construction investment costs, coal-to-electricity project investment, annual conventional grid operation and maintenance costs, and electricity sales revenue, which will help improve the performance level of equipment assets in the regional distribution network.

On the Stability of Power Electronics-Dominated Systems: Challenges and Potential Solutions

The modern power system is becoming more complicated due to the ever increasing penetration of power electronics, which is referred to as a power-electronics-dominated system (PEDS). In this case, the analysis, control, and operation of the entire power system should tone with the energy-paradigm transition pace, where the challenges should be properly tackled. After the brief introduction of grid-connected converters, this article explores stability challenges of PEDSs, especially on the low inertia issue and multitimescale characteristics, as well as the dynamics when connected to weak grids. The low inertia issue is considered as one of great challenges that power electronics introduce to the conventional power grid. Accordingly, the stability issues of PEDSs are discussed. The exploration reveals that the multitimescale coupling among various control loops and the mutual effects of multiple converters demand much more attention than ever before. The coordinated control of converters for the global stability of PEDSs is also summarized, part of which offers the possibility to solve the inertia problem. This article serves as an inspiration on potential solutions to these issues. In order to provide a more intuitive impression of the inertia problem in PEDSs, a case study is exemplified to highlight the analysis and discussion.

Stochastic Geometry-Based Model for Dynamic Allocation of Metering Equipment in Spatio-Temporal Expanding Power Grids

With smart grids replacing conventional power grids and rapidly expanding in both space and time, ensuring an acceptable system observability becomes a challenge in spatio-temporal expanding power grids. In addition, system operators face another challenge, namely, financial budget constraints. To address these challenges, a metering equipment allocation strategy for monitoring of the power grid state needs to be dynamic in both space and time. Unfortunately, existing metering allocation strategies are quite limited. They usually deal with static power grid topologies, and hence, do not reflect the spatio-temporal expansion of the power grid. In this paper, a spatio-temporal power grid model is proposed based on stochastic geometry, which we show that it is in a good match with real-world power grids. The proposed model enables us to carry out tractable dynamic allocation of metering equipment in a large (city-wide) and structurally evolving power grid. Using the developed model, a multi-year algorithm for the allocation of metering equipment is proposed based on finite horizon dynamic programming, given budgetary and technical constraints on system observability. Several case studies for metering allocation are demonstrated through simulation results.

Electricity theft mitigation in the Nigerian power sector

Electricity theft is a pervasive problem all over the world. With electricity generation in Nigeria falling short of the required generation ca-pacity, it is disturbing that the little power generated is also being stolen by some unscrupulous consumers. Electricity distribution compa-nies in Nigeria (DisCos) lose about ₦30 billion every month owing to electricity theft. This amount is whopping, and if significantly re-duced and spent on the power infrastructure and management, it would improve the power situation in the country. This paper proffers the deployment of Smart Grid (SG) with its inherent smart metering as a solution to the electricity theft situation in Nigeria, as a result of its improved flexibility, security and reliability. Smart Grid also supports energy diversification, by allowing the integration of various renewa-ble energy sources into the conventional power grid. This will tend to help in improving the epileptic power situation in the country.

False data injection attacks against smart gird state estimation: Construction, detection and defense

As a typical representative of the so-called cyber-physical system, smart grid reveals its high efficiency, robustness and reliability compared with conventional power grid. However, due to the deep integration of electrical components and computinginformation in cyber space, smart grid is vulnerable to malicious attacks, especially for a type of attacks named false data injection attacks (FDIAs). FDIAs are capable of tampering meter measurements and affecting the results of state estimation stealthily, which severely threat the security of smart grid. Due to the significantinfluence of FDIAs on smart grid, the research related to FDIAs has received considerable attention over the past decade. This paper aims to summarize recent advances in FDIAs against smart grid state estimation, especially from the aspects of background materials, construction methods, detection and defense strategies. Moreover, future research directions are discussed and outlined by analyzing existing results. It is expected that through the review of FDIAs, the vulnerabilities of smart grid to malicious attacks can be further revealed and more attention can be devoted to the detection and defense of cyber-physical attacks against smart grid.

A Review of the Prospects and Benefits of Smart Gridding Technology Adoption in Bangladesh's Power Sector

Smart gridding of conventional power grids is key to ensuring the optimal use of electricity. Incorporation of contemporary smart gridding technologies (SGTs) within the power sector of Bangladesh can lead to expansion of the national grid infrastructure, improvement in energy‐use efficiencies, betterment of the reliability of power supply, and reduction in the monetary values of system losses. In addition, the accommodation of renewable energy within smart grids can raise the share of renewable electricity as a percentage of total electricity output of Bangladesh. This, in turn, is anticipated to provide off‐grid electrification opportunities and play a critically important role in mitigating the urban‐rural divide in access to electricity.

Probability-driven transmission expansion planning with high-penetration renewable power generation: A case study in northwestern China

The incorporation of power generation derived from renewable energy sources, or renewable power generation (RPG), into conventional electric power grids has been rapidly increasing on a large scale in recent years. However, this process can be expected to inevitably increase the uncertainty associated with transmission line investment owing to the inherent uncertainty associated with RPG. While robust transmission expansion planning (RTEP) has been commonly employed for optimizing transmission line investments, this method suffers from serious disadvantages such as the neglect of available RPG probability information, overly conservative solutions, and exceedingly time consuming solution processes. The present work addresses these disadvantages by modeling the probability of RPG uncertainty according to RPG output probabilities obtained over a long-term planning horizon based on available historical data using a hybrid probability uncertainty set constructed using 1-norm and ∞-norm metrics. A probability-driven RTEP model is then proposed to obtain an optimal investment strategy that provides a security guarantee under the worst-case RPG probability distribution, while alleviating the need for overly conservative solutions with high total expansion costs. In addition, a modified column-and-constraint generation algorithm is developed to solve the proposed tri-level probability-driven RTEP model, where the large-scale inner bi-level component of the optimization problem is decomposed into several small-scale linear models that can be solved in parallel. The proposed algorithm requires no dual variables in the inner problem and eliminates all highly non-convex bilinear terms like those obtained in conventional RTEP solution algorithms. This can effectively increase the computational speed of the solution process. The effectiveness, good applicability, and robustness of the proposed model and solution algorithm are demonstrated by numerical applications based on a Garver’s 6-bus test system and an existing electric grid system in northwestern China.

Control Techniques for Bidirectional Interlinking Converters in Hybrid Microgrids: Leveraging the advantages of both ac and dc

Ac or dc microgrids using renewable energy sources (solar, wind, and others) are effective for helping address the energy crisis and environment problems. AC microgrids offer flexible interoperability with conventional power grids through transformers. Meanwhile, dc microgrids are highly stabile and require relatively inexpensive transmission equipment and cables. Recently, dcand ac-dominated hybrid microgrids have gained popularity as they can maximize advantages of both ac and dc microgrids while providing improved compatibility characteristics. The stable and economical operation of intricate hybrid systems requires proper power coordination control for bidirectional interlinking converters (BICs), which provide the required interconnect between the ac and dc subgrids. This article focuses on the commonly applied control techniques for hybrid microgrids.

Cost Effective Power Quality Improvement Technique by Utilization of Solar Power for Non-Linear Loads

Nowadays usage of digital gadgets and other low power devices has increased exponentially, which has power converters to convert from utility AC voltage to required level of DC voltage. These power converters (Adopters), which are considered as Non-linear loads, in turn induces harmonics on the supply side. Due to these induced harmonics, power quality of the utility supply will be degraded affecting the performance of other linear loads connected to the same supply. This paper discusses the effects of non-linear loads and corrective actions available in the literature. An effort has been made to analyze the performance of some domestic non-linear loads using MATLAB/SIMULINK software and verify the same by experimental setup. The Total Harmonic Distortion is analysed using FFT window and simulation and experimental results were compared. Then, a solar powered DC supply is proposed which can power all digital gadgets and other low power devices. As DC supply is generated from the solar power, the connection of non-linear loads to utility supply is reduced, thereby improving the power quality of the distribution side. Adoption of the proposed DC supply for low power digital gadgets, both in rural and urban areas will definitely make the domestic power consumers to be independent of depleting conventional grid power supply at low cost.

Smart energy coordination of autonomous residential home

The smart grid technology permits the revolution of the electrical system from a conventional power grid to an intelligent power network which has led the improvements in electrical system in terms of energy efficiency and sustainable energy integration. This study presents the energy management/coordination scheme for domestic demand using the key strategy of smart grid energy efficiency modelling. The structure consists of combining renewable energy resources, photovoltaic (PV) and wind power generation connected to the utility grid with energy storage system (ESS) in an optimal control manner to coordinate the power flow of a residential home. Based on the demand response schemes in the framework of real-time electricity pricing, this work designs a closed-loop optimal control strategy that is created by the dynamic model of the ESS to compute the system performance index, which is formulated by the cost of the energy flows. A dynamic distributed energy storage strategy (DDESS) is implemented to optimally coordinate the energy system, which reduces the total energy consumption from the main grid of more than 100% of the load demand. The designed model introduces a payback scheme while robustly optimising the energy flows and minimising the utility grid's energy consumption cost.

A coupled thermo-hydro-mechanical model for evaluating air leakage from an unlined compressed air energy storage cavern

Compressed air energy storage (CAES), a large-scale energy storage technology, is a link between unstable renewable energy and conventional power grids. Air leakage may significantly impact the CAES efficiency. This paper presented a coupled thermo-hydro-mechanical model to evaluate the air leakage from an unlined CAES cavern. This model was validated with field tests, numerical simulations, and an analytical solution. The impacts of air leakage on the variations of temperature and pressure within a CAES cavern and the air seepage in surrounding rock were numerically analyzed. Finally, the effects of rock permeability, mass flow rate of air injection, and cavern radius on air leakage were investigated. It is found that rock permeability is a key parameter to air leakage. For the first cycle and under operational pressure of 5 and 8 MPa, rock permeability should be smaller than 3 × 10−19 m2 to satisfy the tightness requirement for an unlined CAES cavern. That is less than 1% daily air leakage percentage. Larger cavern radius and higher mass flow rate of air injection are helpful to reducing the daily air leakage percentage. These results can provide guidelines for tightness requirements for existing cavern repair or new CAES cavern construction design.

Fog Computing for Smart Grid Systems in the 5G Environment: Challenges and Solutions

Currently, the demand for electricity is increasing day by day, which necessitates upgrading of the existing power grid system. The conventional power grid has already been replaced with modern ICT-based infrastructure, which is known as smart grid (SG). In SG, smart meters generate a huge amount of data, and it is a challenging task to store, process, and analyze the data, which varies with respect to volume, velocity, and variety. The data generated in an SG system is generally stored and analyzed using cloud computing (CC), which provides real-time response for various applications. However, to handle the latency issue during the data analytics in SG, fog computing (FC) has emerged as a new technology that provides most of the computing resources in proximity of the end users. It acts as a bridge between SG and CC to fill the gap between processing power of remote data centers and smart devices in SG systems. To handle the aforementioned issues, there is a requirement to set up advanced sensors and measurement systems having communication network backbones in the upcoming fifth generation (5G). In this article, we discuss the architecture of SG in the context of FC for making the decision about energy requirements by the smart devices at the fog layer. Moreover, the communication and computing aspects are also explored in the context of 5G network infrastructure. We examine the influence of FC on response time, transmission delay, and energy management costs for delay-sensitive applications.

Framework for estimation of the direct rebound effect for residential photovoltaic systems

Over the past two decades the market for residential rooftop photovoltaic (PV) systems has grown substantially due mainly to declining costs—a trend that is expected to continue. One drawback of PV system diffusion is the potential for a rebound effect, a well-known economic response through which potential energy savings are partially offset by increased demand resulting from lower energy costs. Our work differs from the existing literature, however, because the rebound effect associated with the adoption of rooftop PV is due not to an improvement in energy efficiency, but to the availability of a zero-marginal cost alternative to grid electricity. This paper develops a novel method for estimating the rebound effect for rooftop PV based on economic and geographic information systems modeling. The method is illustrated through a numerical example, using neighborhood-level data from Fulton County, Georgia, USA. We discuss possible applications of our proposed method, which include (i) enhancing the predictive capability for conventional power grid managers in balancing forecasted demand with dispatchable supply, and (ii) aiding policy makers in designing policies to mitigate the rebound effect associated with solar PV adoption.

Multicriteria environmental analysis for choosing alternative sources of electricity in isolated areas: the case of the Pantanal, Brazil

ABSTRACTUniversal access to electricity in isolated areas is a social imperative and a substantial challenge for service providers. One such area is the Pantanal, which is one of the world’s largest wetlands and located in the central-west region of Brazil. The energy supply to this region is complex not only due to technical aspects but also, and primarily, because of environmental issues such as large areas under environmental preservation and seasonal flooding. To incorporate environmental feasibility into decision-making for the electricity supply to remote areas, a survey of the environmental aspects of several supply alternatives was performed. Solar, wind and fossil-fuel power generation sources and the expansion of the conventional power grid were considered. Using multicriteria decision analysis (MCDA), these alternatives were scaled, scored and weighted to develop socioenvironmental indices, which express the socioenvironmental impact of the supply alternatives in the affected areas. The results, presented in the form of georeferenced maps, are essential for identifying and measuring the existence and scope of impact of the supply alternatives and represent an important support source for decision-makers.

IoT-enabled smart grid via SM: An overview

Power quality and reliability issues are big challenges to both service provider and consumers in conventional power grids. The ongoing technological advancements in the Internet of Things (IoT) era provide better solutions to enhance the management of these challenges and enforce the measures of a Smart Grid (SG). Advanced Metering Infrastructure (AMI) and Smart Metering (SM) technologies are enabler technologies that can modernize the conventional power grid through exposing the hidden details of electrical power by introducing two-way communication scheme during power transaction process between utilities and consumers. Throughout literature, AMI and SM technologies are widely discussed. However, few studies discuss the role of SM in power quality and reliability monitoring in IoT-enabled SGs. Hence, the paper aims to comprehensively review the feasibility of employing SM for power quality and reliability monitoring. First, we provide a detailed overview about the SMs, wireless communication technologies, and routing algorithms as enabling technologies in AMI. Then, we categorize the existing literature works that target power quality and reliability monitoring. Finally, open research issues are outlined based on shortages in the existing literature.

A robust, distributed, and privacy-preserving aggregation scheme for smart grid communications

ABSTRACTSmart grid is a new type of power grid that integrates advanced information communication technology and measurement technology into conventional power grids. It provides an efficient and intelligent energy service. However, the entities in the smart grid are easily hacked and sometimes even collapsed; then the whole grid system could be jeopardized. Therefore, the security of user privacy and communication in smart grids is still facing great challenges. In this paper, we propose a robust, distributed, and privacy-preserving aggregation scheme, RDPA for short, which uses the homomorphic Paillier cryptosystem technique combined with signature technique to ensure the confidentiality and integrality of users’ electricity consumption. In addition, we employ the threshold secret sharing technology and secret factors injection method to improve the robustness of smart grid systems. For example, RDPA can still run well even when a gateway is hacked. The experimental results and analysis demonstrate that RDPA can resist various attacks and protect user privacy, and its security and performance are better than other related schemes.

Software Defined Networks-Based Smart Grid Communication: A Comprehensive Survey

The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid also known as, smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication (SGC) system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SGC system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. By separating the control plane from the data plane, SDN helps the network operators to manage the network flexibly. Since SG heavily relies on communication networks, therefore, SDN has also paved its way into the SG. By applying SDN in SG systems, efficiency and resiliency can potentially be improved. SDN, with its programmability, protocol independence, and granularity features, can help the SG to integrate different SG standards and protocols, to cope with diverse communication systems, and to help SG to perform traffic flow orchestration and to meet specific SG quality of service requirements. This paper serves as a comprehensive survey on SDN-based SGC. In this paper, we first discuss taxonomy of advantages of SDN-based SGC. We then discuss SDN-based SGC architectures, along with case studies. This paper provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.

Comparative Analysis of Electrical Power Utilization in Nigeria: From Conventional Grid to Renewable Energy-based Mini-grid Systems

The electrical power grid in Nigeria is limited in terms of reach and utilization, and this leaves a large section of the population without access to power supply. This paper therefore reviews literature on the current state of the conventional electrical power grid in Nigeria. The generation, transmission and distribution sectors of the grid are briefly reviewed before examining the extent, capacity and power generation technologies used by some currently deployed mini-grid systems. It is observed that a majority of deployed mini-grid systems depend on solar photovoltaic renewable energy sources and such systems are mostly isolated from the conventional grid. Therefore, to make a case for improved access to electrical power supply in the country, statistical and demographic analysis has been carried out to reveal the size of the electrical energy market available to mini-grids and the need to integrate current and future mini-grids to the conventional grid. It is noted that with substantial but targeted investments, a number of existing smart grid technologies can be employed to integrate mini-grids to the conventional grid thereby providing affordable access to electricity for communities that are hitherto unserved or underserved by the conventional grid. Some of the available smart grid technologies that have been identified to be suitable for integration purposes include advanced metering infrastructure (AMI), flexible alternating current transmission system (FACTS) and high voltage direct current (HVDC) transmission lines. A top-level schematic of how and where such technologies can be deployed is provided.

Deep Learning-Based Interval State Estimation of AC Smart Grids Against Sparse Cyber Attacks

Due to the aging of electric infrastructures, conventional power grid is being modernized toward smart grid that enables two-way communications between consumer and utility, and thus more vulnerable to cyber-attacks. However, due to the attacking cost, the attack strategy may vary a lot from one operation scenario to another from the perspective of adversary, which is not considered in previous studies. Therefore, in this paper, scenario-based two-stage sparse cyber-attack models for smart grid with complete and incomplete network information are proposed. Then, in order to effectively detect the established cyber-attacks, an interval state estimation-based defense mechanism is developed innovatively. In this mechanism, the lower and upper bounds of each state variable are modeled as a dual optimization problem that aims to maximize the variation intervals of the system variable. At last, a typical deep learning, i.e., stacked auto-encoder, is designed to properly extract the nonlinear and nonstationary features in electric load data. These features are then applied to improve the accuracy for electric load forecasting, resulting in a more narrow width of state variables. The uncertainty with respect to forecasting errors is modeled as a parametric Gaussian distribution. The validation of the proposed cyber-attack models and defense mechanism have been demonstrated via comprehensive tests on various IEEE benchmarks.