The large-scale deployment of pervasive sensors and decentralized computing in modern smart grids is expected to exponentially increase the volume of data exchanged by power system applications. In this context, the research for scalable and flexible methodologies aimed at supporting rapid decisions in a data rich, but information limited environment represents a relevant issue to address. To this aim, this paper investigates the role of Knowledge Discovery from massive Datasets in smart grid computing, exploring its various application fields by considering the power system stakeholder available data and knowledge extraction needs. In particular, the aim of this paper is dual. In the first part, the authors summarize the most recent activities developed in this field by the Task Force on “Enabling Paradigms for High-Performance Computing in Wide Area Monitoring Protective and Control Systems” of the IEEE PSOPE Technologies and Innovation Subcommittee. Differently, in the second part,... [more]

The concept of virtual power plants (VPP) was introduced over 20 years ago but is still actively researched. The majority of research now focuses on analyzing case studies of such installations. In this article, the investigation is based on a VPP in Poland, which contains hydropower plants (HPP) and energy storage systems (ESS). For specific analysis, the power quality (PQ) issues were selected. The used data contain 26 weeks of multipoint, synchronic measurements of power quality levels in four related points. The investigation is concerned with the application of a global index to a single-point assessment as well as an area-related assessment approach. Moreover, the problem of flagged data is discussed. Finally, the assessment of VPP’s impact on PQ level is conducted.

Distributed energy resource (DER) has been widely deployed, and distributed generation (DG) can complement the distribution system. Favorable DG deployment provides the grid-connected microgrid (MG) with stable voltage and reduces emission and power generation costs. DGs are considered distributed feeders, and MG is required to be operated under the optimal state. Reconfiguration is a practical approach to optimizing resource allocation. The optimal global solution is obtained via optimization algorithms. In this paper, three objectives are defined, namely, minimization of economic cost (ECC), emission cost (EMC), and voltage deviation (VD). Consequently, a fuzzy moth-flame optimization (FMFO) algorithm is proposed to coordinate the interests of multiple objectives. Moreover, the simulation is conducted based on the standard IEEE 33-bus radial distribution system (RDS), under which the impact of deployment of various DG type and quantity on the MG is explored. In particular, diverse DG... [more]

The Multiple Microgrids (MMGs) concept has been identified as a promising solution for the management of large-scale power grids in order to maximize the use of widespread renewable energies sources. However, its deployment in realistic operation scenarios is still an open issue due to the presence of non-ideal and unreliable communication systems that allow each component within the power network to share information about its state. Indeed, due to technological constraints, multiple time-varying communication delays consistently appear during data acquisition and the transmission process and their effects must be considered in the control design phase. To this aim, this paper addresses the voltage regulation control problem for MMGs systems in the presence of time-varying communication delays. To solve this problem, we propose a novel hierarchical two-layer distributed control architecture that accounts for the presence of communication latencies in the information exchange. More spe... [more]

Improved irradiance forecasting ensures precise solar power generation forecasts, resulting in smoother operation of the distribution grid. Empirical models are used to estimate irradiation using a wide range of data and specific national or regional parameters. In contrast, algorithms based on Artificial Intelligence (AI) are becoming increasingly popular and effective for estimating solar irradiance. Although there has been significant development in this area elsewhere, employing an AI model to investigate irradiance in Bangladesh is limited. This research forecasts solar radiation in Bangladesh using ensemble machine-learning models. The meteorological data collected from 32 stations contain maximum temperature, minimum temperature, total rain, humidity, sunshine, wind speed, cloud coverage, and irradiance. Ensemble machine-learning algorithms including Adaboost regression (ABR), gradient-boosting regression (GBR), random forest regression (RFR), and bagging regression (BR) are dev... [more]

The present article is focused on a detailed computationalinvestigation of energy production capacity of various lightweight materials that are employed with piezoelectric vibration energy harvesters (PVEHs) subjected to various aeroelastic effects. Piezoelectric transducers are primarily employed to capture vibrational energy, which yields predictable and locally storable electrical energy. Higher energy extraction is possible under larger deflections of the structures when they are employed with PVEHs. In order to estimate the largest possible deflection of the structures, the response of them under external perturbations is estimated. An airplane wing consists of tapered planform, an advanced wind turbine blade, and the rectangular wings of an unmanned aerial vehicle (UAV) are considered for the vibrational analysis as the feasibility of achieving larger deflection is high compared with other aerodynamic surfaces. The stated elastic structures are modelled with different lightweight... [more]

Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources that can provide flexibility to support the DSO in actively managing their networks to facilitate reliability under extreme levels of solar PV. This flexibility can also be used to optimize system operations with respect to economic signals from wholesale energy and ancillary service markets. Here, we present a novel hierarchical scheme that actively controls behind-the-meter DERs to reliably manage each unbalanced distribution feeder and exploits the available flexibility to ensure reliable operation and economically optimizes the entire distribution network. Each layer of the scheme employs advanced optimization methods at different timesc... [more]

The smart grid is an unprecedented opportunity to shift the current energy industry into a new era of a modernized network where the power generation, transmission, and distribution are intelligently, responsively, and cooperatively managed through a bi-directional automation system. Although the domains of smart grid applications and technologies vary in functions and forms, they generally share common potentials such as intelligent energy curtailment, efficient integration of Demand Response, Distributed Renewable Generation, and Energy Storage. This paper presents a comprehensive review categorically on the recent advances and previous research developments of the smart grid paradigm over the last two decades. The main intent of the study is to provide an application-focused survey where every category and sub-category herein are thoroughly and independently investigated. The preamble of the paper highlights the concept and the structure of the smart grids. The work presented intens... [more]

Smart grids (SGs) are attracting attention as high value-added platforms, which mass-produce new business models through real-time information sharing. However, the open-ended information structure of SGs increases the risk of exposure to cyberattacks through the creation of multiple communication access points. In a power system where a real-time balance of supply and demand is essential, cyberattacks result in cascading failures leading to power outages. Therefore, this paper proposes a method to evaluate the robustness of large-scale SGs against cybersecurity disturbances. The proposed evaluation method established a hierarchy quantification technique considering the structural characteristics of SGs. With respect to the cyber hierarchy, relevant standards (NERC CIP, NIST FIPS) were applied to classify the grades of information security risk. In the case of physical hierarchy, the power system was calculated by using optimal power flow and analyzed the frequency stability. This stud... [more]

Modern power systems must provide efficient, reliable, and environmentally responsible energy. Recently, the inclusion of Microgrids (MGs) has allowed us to overcome some difficulties and face important challenges in this direction, especially related to the use of alternative energy sources. Increased and probabilistic demand, as well as limited energy supply, pose the need to evaluate the reliability of any distribution system (DS) when MGs are introduced. Here we reviewed and classified the state-of-the-art of reliability assessment (RA) in MGs. Initially, we contextualize RA in distribution systems. Next, each of the MGs subsystems components are introduced and the questions (1) why is it important to evaluate the reliability in Microgrids? (2) how do Microgrids influence the reliability of distribution systems? and (3) how does each of its subsystems influence the reliability of the Microgrids? are addressed. A total of 1395 research studies were published between 2002 and 2020. U... [more]

In today’s world, distributed generation (DG) is an outstanding solution to tackle the challenges in power grids such as the power loss of the system that is intensified by the exponential increase in demand for electricity. Numerous optimization algorithms have been used by several researchers to establish the optimal placement and sizing of DGs to alleviate this power loss of the system. However, in terms of the reduction of active power loss, the performance of these algorithms is weaker. Furthermore, the premature convergence, the precision of the output, and the complexity are a few major drawbacks of these optimization techniques. Thus, this paper proposes the multileader particle swarm optimization (MLPSO) for the determination of the optimal locations and sizes of DGs with the objective of active power loss minimization while surmounting the drawbacks in previous algorithms. A comprehensive performance analysis is carried out utilizing the suggested approach on the standard IEE... [more]

This exploratory research outlines an opportunity for increasing renewable energy share in Bangladesh by using electric rickshaws (e-rickshaws) as a catalyst. The overall objective of this research is to show how to utilise an existing opportunity, such as e-rickshaws, as energy storage options for integrating renewable energy sources. It proposes a grid-connected local energy system considering a battery swapping and charging station (BSCS) for e-rickshaws as a community battery energy storage (CBESS). This system was simulated using the HOMER Pro software. The simulation results show that such systems can help communities significantly reduce their dependency on the national grid by integrating solar PV locally. The proposed BSCS also shows an opportunity for battery demand reduction and circular battery management for electric rickshaws. The research also discusses the economies of scale of the proposed method in Bangladesh, and pathways for implementing microgrids and smart energy... [more]

The energy transition poses a challenge for the electricity distribution network design as new energy technologies cause increasing and uncertain network loads. Traditional static load models cannot cope with the stochastic nature of this new technology adoption. Furthermore, traditional nonlinear power methods have difficulty evaluating very large networks with millions of cables, because they are computationally expensive. This paper proposes a method which uses copulas for modeling the uncertainty of technology adoption and load profiles, and combines it with a fast linear load flow model. The copulas are able to accurately model the stochastic behavior of solar irradiance, load measurements, and mobility data, converting them into electricity load profiles. The linear load flow model has better scalability and stability compared to traditional load flow models. The models are applied to a case study which uses a real-world dataset consisting of a realistic technology adoption scena... [more]

Decarbonisation of heat and transport will cause congestion issues in distribution networks. To avoid expensive network investments, demand flexibility is necessary to move loads from peak to off-peak periods. We provide a method and metric for assessing and selecting the optimal demand response strategy for a given network congestion scenario and applied it to a case study network in Coleraine, Northern Ireland. We proposed a Price Approximation/Mean Grouping strategy to deal with the issue of congestions occurring at the lowest-price period in real-time pricing schemes. The Mean Grouping strategy increased the average lowest-price hours from 1.32 to 3.76. We show that a three-cluster tariff is effective in solving medium congestion issues in Northern Ireland and could save consumers an average of £117/year on their heating bill. However, for networks with low headroom suffering from serious congestion issues, a smart control strategy is needed.

In the context of smart grids, Distribution Systems State Estimation (DSSE) is notoriously problematic because of the scarcity of available measurement points and the lack of real-time information on loads. The scarcity of measurement data influences on the effectiveness and applicability of dynamic estimators like the Kalman filters. However, if an Extended Kalman Filter (EKF) resulting from the linearization of the power flow equations is complemented by an ancillary prior least-squares estimation of the weekly active and reactive power injection variations at all buses, significant performance improvements can be achieved. Extensive simulation results obtained assuming to deploy an increasing number of next-generation smart meters and Phasor Measurement Units (PMUs) show that not only the proposed approach is generally more accurate and precise than the classic Weighted Least Squares (WLS) estimator (chosen as a benchmark algorithm), but it is also less sensitive to both the number... [more]

Auxiliary services are vital for the operation of a substation. If a contingency affects the distribution feeder that provides energy for the auxiliary services, it could lead to the unavailability of the substation’s service. Therefore, backup systems such as diesel generators are used. Another alternative is the adoption of a microgrid with batteries and photovoltaic generation to supply substation auxiliary services during a contingency. Nevertheless, high battery costs and the intermittence of photovoltaic generation requires a careful analysis so the microgrid capacity is defined in a compromise between the investment and the unavailability reduction of auxiliary services. This paper proposes a method for the capacity sizing of a microgrid with batteries, photovoltaic generation, and bidirectional inverters to supply auxiliary services in substations under a contingency. A set of alternatives is assessed through exhaustive search and Monte Carlo simulations to cater for uncertaint... [more]

Reactive power management in microgrids with high penetration of distributed renewable energy sources (DRESs) is challenging. The intermittent generation of DRES makes the power management cumbersome. Generally, Flexible AC Transmission System (FACTS) devices such as Distribution Static Compensator (DSTATCOM) are employed for reactive power compensation in microgrids. However, for effective results in microgrids, coordinated operation between DSTATCOM and Distributed Energy Resources (DERs) is required. In this paper, IEC 61850 communication is proposed for realizing coordinated operation between microgrid controller (MGCC), DSTATCOM and DERs. In microgrids, there may be large number of DERs dispersed over a large area. Hence, the underlying communication network technology for IEC 61850 communication must be highly scalable with wide range. Recently developed communication technology Long Term Evolution (LTE) is a promising solution since it offers high data rates, reliability, scalab... [more]

The electrical distribution system has experienced a number of important changes due to the integration of distributed and renewable energy resources. Optimal integration of distributed generators (DGs) and distribution network reconfiguration (DNR) of the radial network have significant impacts on the power system. The main aim of this study is to optimize the power loss reduction and DG penetration level increment while keeping the voltage profile improvements with in the permissible limit. To do so, a hybrid of analytical approach and particle swarm optimization (PSO) are proposed. The proposed approach was tested on 33-bus and 69-bus distribution networks, and significant improvements in power loss reduction, DG penetration increment, and voltage profile were achieved. Compared with the base case scenario, power loss was reduced by 89.76% and the DG penetration level was increased by 81.59% in the 69-bus test system. Similarly, a power loss reduction of 82.13% and DG penetration le... [more]

The electricity grid faces the possibility of outages due to extreme weather events, cyber-attack, and unexpected events. When these unwanted events occur, it is desired that electricity be restored as soon as possible to meet the power demands of critical loads. The microgrid approach to power restoration holds a lot of promise, since microgrids can operate in island mode. This paper presents a novel sequential restoration methodology for microgrid black start. The microgrid architecture considered is assumed to be operating in multi-master mode. The master distributed generators (DGs) are coordinated to operate together through droop control. Several operational constraints are formulated and linearized to realize a mixed-integer linear programming (MILP) problem. The method is studied on an islanded microgrid based on a modified IEEE 13 node test feeder. Detailed transient simulation in PSCAD was used to verify the accuracy of the restoration methodology. The developed restoration m... [more]

This paper describes a control methodology for electronic power converters distributed in low-voltage microgrids and its implementation criteria in general microgrid structures. In addition, a real-time simulation setup is devised, implemented, and discussed to validate the control operation in a benchmark network. Considering these key aspects, it is shown that operational constraints regarding the power delivered by sources, flowing through network branches, and exchanged at the point of connection with the main grid can generally be fulfilled by the presented control approach. The control is performed considering a cost function aiming at optimizing various operation indexes, including distribution losses, current stresses on feeders, voltage deviations. The control system allows an enhanced operation of the microgrid, specifically, it allows dynamic and accurate power flow control enabling the provision of ancillary services to the upstream grid, like the demand−response, by exploi... [more]

Decision-making for the condition-based maintenance (CBM) of power transformers is critical to their sustainable operation. Existing research exhibits significant shortcomings; neither group decision-making nor maintenance intention is considered, which does not satisfy the needs of smart grids. Thus, a multivariate assessment system, which includes the consideration of technology, cost-effectiveness, and security, should be created, taking into account current research findings. In order to address the uncertainty of maintenance strategy selection, this paper proposes a maintenance decision-making model composed of cloud and vector space models. The optimal maintenance strategy is selected in a multivariate assessment system. Cloud models allow for the expression of natural language evaluation information and are used to transform qualitative concepts into quantitative expressions. The subjective and objective weights of the evaluation index are derived from the analytic hierarchy pro... [more]

Isolated microgrids are microgrids which operate autonomously. This paper presents an isolated microgrid which combines a Hydraulic Turbine Generator (HTG) with a Wind Turbine Generator (WTG) to supply consumers forming a Wind Hydro Isolated Microgrid (WHIM). The WHIM includes a Dump Load (DL) to dissipate the active power excess. The WHIM has been modeled and its operation has been simulated in two modes: Wind-Hydro (WH), where both HTG and WTG supply power, and Wind-Only (WO) mode, where the WTG is the active power supplier and the HTG keeps connected to the grid with null power to generate the grid voltage. In WO, a fast frequency regulation is achieved by means of a controller which commands the DL to consume the WTG power excess. Additionally, the simulation of the mode transition from WO to WH, which is triggered by a system active power deficit in WO mode, is shown. A kick starting system designed to speed up the HTG power production improves the transient from WO to WH mode cha... [more]

It is imperative to increase the connectable capacity (i.e., hosting capacity) of distributed generation in order to decarbonise electricity distribution networks. Hybrid generation that exploits complementarity in resource characteristics among different renewable types potentially provides value for minimising technical constraints and increasing the effective use of the network. Tidal, wave and wind energy are prominent offshore renewable energy sources. It is of importance to explore their potential complementarity for increasing network integration. In this work, the novel introduction of these distinct offshore renewable resources into hosting capacity evaluation enables the quantification of the benefits of various resource combinations. A scenario reduction technique is adapted to effectively consider variation of these renewables in an AC optimal power flow-based nonlinear optimisation model. Moreover, the beneficial impact of active network management (ANM) on enhancing the r... [more]

In some power networks, components of frequency less than the frequency of the fundamental voltage harmonic called subharmonics or subsynchronous interharmonics occur. In this paper, the effect of voltage subharmonics on currents, power losses, speed fluctuations and electromagnetic torque is examined. The results of numerical computations using the finite element method for an induction cage motor of rated power of 5.6 MW and four motors of rated power of 200 kW with different numbers of poles are presented. An extraordinary harmful effect on high-power induction motors is demonstrated. Among other effects, voltage subharmonics cause significant torque pulsations whose frequencies may correspond to the elastic-mode natural frequency. Possible resonance can result in excessive torsional vibration and the destruction of a power train.

The research work hereby presented, emerges from the urge to answer the well-known question of how the uncertainty of intermittent renewable sources affects the performance of a microgrid and how could we deal with it. More specifically, we want to evaluate what could be the impact in performance of a microgrid that is intended to serve a smart-building (powered by photovoltaic panels and with battery energy storage), when the uncertainty of the photovoltaic-production forecasts is considered in the energy management process through the use of quantile forecasts. For this, several objectives (or services) are targeted based in a two-step (double-objective) energy management framework, which combines optimization-based and rule-based algorithms. The performance is evaluated based on some particular services, namely: energy cost, carbon footprint, grid peak power, and grid commitment; with the latter being a novel service proposed in the domain of microgrids. Simulations are performed wh... [more]