Smart Distribution Grid Research Articles

Impedance sensitivity-based corrective method for online voltage control in smart distribution grids

With the rapid increase in hosting large penetration levels of Distributed Generation (DG), voltage stability problem has raised a main concern for distribution networks. This study proposes a new centralized voltage control method following a security purpose for active distribution grids. The method is based on a sensitivity analysis to optimally dispatch the control variables. The sensitivity analysis uses a Thevenin-based load impedance margin (TLIM) derived from the nodal measurements to take into the consideration the changes in the system operation, especially those caused by the rapid-response devices of DGs. Sensitivity of load and equivalent impedances to control variables is investigated via the derivation of nodal voltage and current with respect to control variables. Accordingly, the contribution of each control variable in change TLIM and, hence, in voltage control can accurately be obtained. The changes of the impedances of pilot bus, which has the smallest value among all the TLIMs, are formulated in a multi-step optimization problem in terms of impedance sensitivities for the optimal dispatch of controls. The proposed sensitivities and their application in voltage control are successfully validated by a 11-kV distribution grid including 77 bus and hosting 22 DG units. Simulation results show the validity and the accuracy of the proposed sensitivity method in voltage control during different scenarios.

Trilemma of Smart Distribution Grid: People, Processes and Environment

The paper has presented smart distribution grid from a new perspective of how the consumers (“People”) and different activities (“Processes”) of distribution companies are interconnected. Next, discussion has been given regarding how the core thoughts of smart grids (“Energy Conservation” and “Demand Management”) are helping in reducing degradation of “Environment”. These three dimensions of “People”, “Processes” and “Environment” are termed as “Trilemma of Smart Distribution Grid”. Each of these three dimensions is explained, in Sections 2, 3 and 4, respectively, using block diagram and simple desciption of each block. Further, recommendations have been given in Section 5 for distribution companies: (a) to follow guidelines and policies being issued by many authorities in Central / State / Local Governments; (b) to always keep in mind the benefits to “People” in whatever they do; (c) to conduct regular training and development programs for their staff to keep them updated about new developments; (d) to conduct free-training programs for industrial consumers to educate them about the latest trends in equipment and processes, so that they can plan for short-term and long-term measures for energy conservation and demand reduction in their operations; (e) to do cost-benefit analysis which would show them that they would get returns on their investments only if they take up large power-consuming city for making the grid “Smart”; and (f) to strengthen the distribution system in city to take care of large power demand expected from EV charging stations on city roads in next decade.

Research on operation control of low-voltage MTDC system in a cyber-physical environment

Cyber-physical system is becoming a new feature and hot topic in the development of smart grid and DC power distribution system. Based on the standardized cyber-physical modeling and communication system — IEC 61850, this paper establishes the operation control architecture of the low-voltage multi-terminal DC (LV-MTDC) system. The coordinated operation control strategies including power electronic transformer (PET), voltage source converter (VSC) is proposed. Then a cyber-physical model of the system based on IEC 61850 is built, according to the application requirements of operation control in the LV-MTDC system. On this basis, the implementation method of system operation control based on IEC 61850 is proposed, including the software/hardware design of intelligent electronic device (IED), dispatching operation and uninterrupted power supply. The simulation environment is further built to verify the system operation control technology, and the test platform is used to carry out the actual tests. The research results show that the operation control technology for the LV-MTDC system proposed in this paper is feasible, which can guarantee the rapid and accurate information exchange of control commands and settings, and thus effectively realize the operation control of the LV-MTDC system under complex conditions.

Design and Development of High Efficiency 150 kW Very Compact PLA Core Electromagnetic Coupler for Highly Resonant Power Transfer Technology

Highly Resonant Power Transfer (HRPT) technology is currently receiving very significant attention from the industry and the smart power grid distribution community in particular. This technology ensures electrical power transmission between two points while controlling the level of transmitted power and ensures the immediate shutdown of the transmitted power in the event of a problem. This paper reviews the inductive power transfer method and describes the design of an ultra-compact PLA core electromagnetic coupler. The proposed architecture confines the magnetic field in a toroidal PLA core transformer, and by avoiding the use of heavy and bulky shielding plates, reduces magnetic losses and avoids the Curie point. As a result, the overall unit has a weight of 5 kg and a volume of only 0.013 m3. The electromagnetic coupler is capable of transferring a peak power of 150 kW with an operating frequency of 193 kHz, giving a satisfactory efficiency of 95%. The proposed novel system was first investigated through CST 3D numerical modelling to determine the electrical parameters of the coupler’s equivalent circuit and its efficiency, to verify its compatibility with the ICNIRP 2010 standard and to evaluate its temperature rise with an air-cooling system. Afterwards, the designed coupler was built with a 3D printing device and finally tested experimentally. Simulation and experimental results are compared and show a good agreement.

Laboratory- and field-test validations of a smart distribution grid system

Laboratory- and field-test validations of a smart distribution grid system

Economic and environmental aspects of Smart Grid technologies implementation in Ukraine

Interruptions in electricity supply may have a series of failures that can affect banking, telecommunications, traffic, and safety sectors. Due to the two-way interactive abilities, Smart Grid allows consumers to automatically redirect on failure, or shut down of the equipment. Smart Grid technologies are the costly ones; however, due to the mitigation of possible problems, they are economically sound. Smart grids can't operate without smart meters, which may easily transmit real-time power consumption data to energy data centers, helping the consumer to make effective decisions about how much energy to use and at what time of day. Smart Grid meters do allow the consumer to track and reduce energy consumption bills during peak hours and increase the corresponding consumption during minimum hours. At a higher level of management (e.g., on the level of separate region or country), the Smart Grid distribution system operators have the opportunity to increase the reliability of power supply primarily by detecting or preventing emergencies. Ukraine's energy system is currently outdated and cannot withstand current loads. High levels of wear of the main and auxiliary equipment of the power system and uneven load distribution in the network often lead to emergencies and power outages. The Smart Grid achievements and energy sustainability are also related to the energy trilemma, which consists of key core dimensions– Energy Security, Energy Equity, and Environmental Sustainability. To be competitive in the world energy market, the country has to organize efficiently the cooperation of public/private actors, governments, economic and social agents, environmental issues, and individual consumer behaviors. Ukraine gained 61 positions out of 128 countries in a list in 2019 on the energy trilemma index. In general, Ukraine has a higher than average energy security position and lower than average energy equity, and environmental sustainability positions. Given the fact that the number of renewable energy sources is measured in hundreds and thousands, network management is complicated and requires a Smart Grid rapid response. Keywords: economic development, Smart Grid, electricity supply, economic and environmental efficiency.

Temperature impact assessment on multi-objective DGs and SCBs placement in distorted radial distribution systems

In smart grid distribution systems, the applications of Shunt Capacitor Banks (SCBs) and Distributed Generations (DGs) are widely known and installed for system loss reduction, voltage stability improvement of system buses, and to free up the system loading. However, the installation of SCBs and DGs in distribution systems with distorted waveforms will increase the harmonic distortion level if they are not placed at appropriate locations. In this paper, a Multiobjective Grey Wolf Optimizer (MOGWO) is proposed to find the optimal size and locations of SCBs and DGs simultaneously with regard to the impact of ambient temperature on distorted distribution systems. Electric utilities will be able to reduce system active losses, enhance the voltage stability for system buses, release the section loading, and reduce the total harmonic distortion level. Fuzzy set theory is utilized to choose the optimum compromise solution from the Pareto front solutions of the MOGWO method. The proposed method is applied to IEEE 69-bus and real data taken from the Saudi Electricity Company (SEC). The results show a higher capability in finding optimum solutions for SCBs and DGs placement in distorted Radial Distribution Systems (RDSs) compared to conventional methods.

Problems and Solutions in Integrated Regulation and Control of Smart Grid Distribution Network

Problems and Solutions in Integrated Regulation and Control of Smart Grid Distribution Network

Experimental studies on the rtEthernet-based centralized fault management system for smart grids

The distribution smart grids in future are likely to have looped structures with a variety of new electronic devices to integrate renewable energy. However, tremendous challenges are brought to the fault management system (FMS), particularly the ultra-fast speed of fault localization with data acquisition at many different locations over a large geographical area. In this work, we propose a centralized fault management system (CFMS) with operation resilience based on real-time Ethernet (rtEthernet) protocols for the protection of smart grids. First, we propose a model to estimate the communication cycle time and the mis-synchronization error based on rtEthernet protocols. The model can be used to design CFMS over a large geographical area with a large number of power system devices. Second, we propose to use the instantaneous values of sample points in the percentage differential protection algorithm, instead of the value of root mean square (RMS), so that ultra-fast speed for data sampling and fault localization can be achieved. Third, we have established a comprehensive test-bed for the CFMS by using our large-scale real-time digital system (RTDS) to simulate the power system. Our extensive experimental studies have demonstrated that the proposed CFMS achieves ultra-fast speed within a sub-cycle and protects the smart grids successfully.

A review on intentional controlled islanding in smart power systems and generalized framework for ICI in microgrids

Blackouts or cascade failures are costly events which may threaten the integrity of electrical energy systems. The Intentional Controlled Islanding (ICI) is the last measure to reduce the undesirable technical, economic and social consequences of a blackout. In case of an emergency, the ICI of Distributed Generation (DG) units is a solution to preserve reliable power supply in a smart distribution grid. In this paper, three important aspects of ICI problem, namely the proper time of ICI (When), its optimal boundary (Where), and its execution method (How) are comprehensively reviewed. After reviewing the basic algorithms and procedures, to find the best (optimal) time, boundary and execution details, the different methods of the mentioned aspects are summarized and discussed. Finally, a discussion about current challenges and future trends of ICI in smart power systems (in distribution and transmission levels) are provided and moreover, a generalized framework for implementation of ICI in Active Distribution Networks (ADNs) and smart microgrids are presented.

Assessing capacity credit of demand response in smart distribution grids with behavior-driven modeling framework

In smart grid, demand response (DR) provides the utilities with a new alternative to mitigate the operational uncertainties and achieve the power balance target. However, unlike conventional generation units, the performance of DR is strongly dependent on behavioral pattern of customers. As such, to what extent DR programs could be utilized to provide capacity support and contribute to the adequacy of the supply turns out to be an important concern for the utilities. In order to resolve this issue, this paper presents a new methodological framework for assessing the reliability value of DR in a context of distribution grid. The proposed approach is developed on the generation-oriented concept of capacity credit (CC) and it extends the CC application to a DR setting. As the major contribution of this work, the proposed framework accounts for the impacts of both physical and human-related factors on the availability of DR; furthermore, the uncertainty issue that associated with demand-side performances is also explicitly considered in our study. To properly handle the ambiguities of customers’ willingness for DR participation, a novel Z-number-based technique is introduced. Through such an approach, not only the inherent randomness accruing from the demand-side could be captured, but the impact of information creditability would also be accounted for, which could allow a more realistic characterization of DR as compared with existing studies. By jointly using fuzzy-expectation technique and the centroid method, the different types of uncertain variables (probabilistic and Z-numbers) involved in our analysis can be normalized into comparable quantities and then used for the CC evaluation of DR. The proposed framework is illustrated based on both a small test case and a real distribution system, and the obtained results verify the significant role of DR in enhancing the reliability of supply, as well as its sensitivity to different influencing factors.

Autonomous Self-Healing in Smart Distribution Grids Using agent Systems

When a fault occurs on a distribution system, it should be isolated. After isolation, the distribution system can be reconfigured to restore the out-of-service area. The distribution system configuration can be changed by performing switching actions on the feeders. This paper proposes an agent-based approach for service restoration in smart distribution systems. The proposed multiagent approach has three different types of agents, namely, feeder agents, zone agents, and switch agents. The agents can communicate and cooperate with each other in order to supply services to out-of-service customers. The restoration plan is built on the basis of local data considering system conditions, operational constraints, and the fault location. Different loading conditions have been considered under different scenarios, and the results of the proposed multiagent approach for each scenario have been compared. Simulation results show the efficiency of the proposed agent architecture.

Phase Balancing and Reactive Power Support Services for Microgrids

Alternating current (AC) microgrids are expected to operate as active components within smart distribution grids in the near future. The high penetration of intermittent renewable energy sources and the rapid electrification of the thermal and transportation sectors pose serious challenges that must be addressed by modern distribution system operators. Hence, new solutions should be developed to overcome these issues. Microgrids can be considered as a great candidate for the provision of ancillary services since they are more flexible to coordinate their distributed generation sources and their loads. This paper proposes a method for compensating microgrid power factor and loads asymmetries by utilizing advanced functionalities enabled by grid tied inverters of photovoltaics and energy storage systems. Further, a central controller has been developed for adaptively regulating the provision of both reactive power and phase balancing services according to the measured loading conditions at the microgrid’s point of common coupling. An experimental validation with a laboratory scale inverter and a real time hardware in the loop investigation demonstrates that the provision of such ancillary services by the microgrid can significantly improve the operation of distribution grids in terms of power quality, energy losses and utilization of available capacity.

Optimal allocation of unified power quality conditioner in the smart distribution grids

The optimal operation of current distribution networks has a great importance due to growing electrical demand and significant power losses. In this paper, the optimal allocation of unified power quality conditioner (UPQC) in smart grid with responsive loads is investigated as an appropriate solution to reduce power losses. Also, in order to consider different consumption patterns and to predict the demand with the lowest error, different linear and nonlinear models of responsive loads are taken into account. New pricing method in demand response programs (DRPs) is another concept which is developed in the paper by which optimal electricity prices in DRP during peak, off-peak, and valley periods are determined. Moreover, DRPs are prioritized by the Topsis method based on the different Utility’s policies. The final proposed model has been applied on the IEEE 12-bus, IEEE 33-bus, and the practical 94-bus Portuguese RDS distribution system. The results show that the UPQC allocation in the presence of DRPs is a win–win game both for the Utility and for customers.

A Hybrid Method for Non-Technical Loss Detection in Smart Distribution Grids

Non technical losses (NTLs) are a major problem faced by DSOs all over the world. Traditional meter inspection techniques are not effective in detecting NTL, while the wide adoption of smart meters and smart grid technologies provide new opportunities for solving the problem. The proposed NTL detection system utilizes voltage sensitivity analysis, power system optimization, and support vector machines (SVMs) for correctly detecting NTLs in the distribution grid under various conditions. Breakout detection is used for extracting features from consumption time series and training an SVM classifier. Generalized least squares is used for estimating the network voltage self-sensitivities. Finally, the NTL detection problem is formed as a non-linear non-convex optimization problem solved with semi-definite programming relaxation. The three modules can be operated either autonomously or combined. The proposed NTL detection system is demonstrated under different scenarios to test its effectiveness.

A novel approach for multi-objective optimal scheduling of large-scale EV fleets in a smart distribution grid considering realistic and stochastic modeling framework

The ever-increasing number of grid-connected electric vehicles (EVs) has led to emerging new opportunities and threats in electrical distribution systems (DS). Developing a realistic model of EV interaction with the DS, as well as developing a strategy to optimally manage these interactions in line with distribution system operators (DSOs) intentions, are the most important prerequisites for gaining from this phenomenon especially in modern smart distribution systems (SDS). In this paper, a comprehensive model describing the electric vehicle integration to an SDS is presented by considering the real-world data from EV manufacturers and DSOs. Moreover, a novel energy management strategy (EMS) based on the multi-objective optimization problem (MOOP) is developed to fulfill the operational objectives of DSO and EV owner, including peak load shaving, loss minimization, and EV owner profit maximization. In this regard, an innovative dimension reduction approach is presented, to make it feasible to apply the heuristic optimization methods to a MOOP with a large number of decision variables. Thanks to this method, the improved electromagnetism like algorithm (IEMA) is employed to perform the multi-objective energy scheduling for a large-scale EV fleet. In addition, a novel method is devised for estimating the optimal hosting capacity of an SDS in adopting EVs without the need for sophisticated computations. The presented method is applied to the modified IEEE-33 bus test system. Obtained results reveal that employment of a realistic model concludes to more accurate results than a simplified model. In addition, the efficiency of the proposed EMS in satisfying EV owner and DSO objectives are approved by analyzing obtained computation results.

Enabling a Decentralized Smart Grid Using Autonomous Edge Control Devices

As a large number of distributed devices are connected to the modern smart grid, the traditional centralized connectivity models fail to provide economic value. These models have relied on sending data to the cloud for processing and receiving commands to exert control actions, resulting in an “on-demand system” with high bandwidth, low latency, and an overload of data on the cloud. For realizing a decentralized system, there is a strong need to embed intelligence at the “edge of the network.” These intelligent devices, capable of sensing, local data processing, and exerting control actions, report only actionable information to the cloud, acting as an edge control node. The system can then function autonomously, without constant cloud inputs, tolerating longer delays in communication, and making the overall system ultralow cost. The global asset monitoring, management, and analytics platform is a novel ultralow-cost, secure platform that operates through a Bluetooth-based delay tolerant network. It relies on so-called “data mules” to bridge the last mile connectivity gap in an inherently secure way. Due to this model, the platform requires no in-country certifications, does not rely on a dedicated backhaul technology and is immune to technology migration. This architecture also addresses some gaps identified in traditional Internet of Things-based solutions in remote areas and sparse connectivity. A functional unit of the edge computing node has been built, taking into account various constraints like costs, customizations, data storage, cybersecurity, and power management. The platform has been built, deployed and has demonstrated distributed smart grid applications like power quality sensing, automated metering infrastructure, and utility asset monitoring.

Cyber security requirements engineering for low-voltage distribution smart grid architectures using threat modeling

Incorporating renewable energy into a grid still poses a challenge, that can only be tackled with precise measurement and control. Transferring power from producer to consumer as locally as possible in order to maximize efficiency requires measurement and control functions to be present on the low-voltage grid level. This can only be achieved by massively interconnected, ICT-enhanced sensors and actuators. Interconnecting the former, in turn exposes the grid to various threats from cyberattacks. This creates the need for a holistic, structured and comprehensive approach to engineering a low-voltage smart grid architecture that allocates its resources in such a way that cyber security is preserved. While known previous work either lacks a risk-based approach, comprehensiveness or best practices, this article provides a smart grid-specific methodology that combines risk assessment and threat modeling to generate a holistic set of security requirements. Furthermore, it presents best practices to secure an archetypal smart low-voltage grid architecture based on a concrete example. It considers threats on the architectural, protocol, and device level, while also considering environmental constraints to assure security using mainly state-of-the-art mitigation measures.

High-Penetration Grid-Tied Photovoltaics: Analysis of Power Quality and Feeder Voltage Profile

More People are Turning to Photovoltaic (PV) technology to supply energy needs as concerns rise about greenhouse gases. Thus, installed PV capacity across the smart grid distribution systems has been rising. However, the high penetration of PVs could affect the operation and planning of distribution networks. To evaluate the impact of PVs connected to the grid, a case study on power quality and voltage profile was conducted using a 1.1-MW ac gridconnected PV power plant in Miami, Florida. As part of the power quality analysis, total harmonic distortion (THD) was explored, and high-power and high-energy ramp rate analyses were made.

Short-term economic dispatch of smart distribution grids considering the active role of plug-in electric vehicles

A new methodology to dispatch in an economic and controlled manner the energy requirements of multiple energy storage devices, dispersed generators and loads belonging to a smart distribution grid (SDG) is presented in this paper. Plug-in electric vehicles (PEV) are mainly managed over a 24-hour time window. To maximize the economic social welfare of both a utility and PEV working as prosumers, this short-term economic dispatch (ED) problem incorporates two optimization processes interacting as an integrated model. In the first, aggregators located in the SDG maximize the economic benefits obtained by a PEV group. Fuzzy inference systems are used to estimate the decisions made by each PEV during its participation in energy exchanges with the SDG, which influence the PEV benefits. Using these results and a Mean-Variance Mapping Optimization algorithm, the economic benefits of the utility are maximized in the second process and, the ED is then solved.