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Journal Of Operation And Automation In Power Engineering (24234567)12(2)pp. 175-185
With the advent of advanced measurement and supervisory devices in power systems, wide area measurement systems and real-time monitoring of power systems have become viable. Accordingly, modeling techniques should be updated as well. This paper proposes a transformer asset management model based on real-time condition monitoring in the presence of distributed generation. The model is tested under different case studies and compared with the previous models in which constant failure rate model was used for asset management of transformers. The system cost includes operation, repair, and interruption costs. The objective is to determine the hourly loading of the transformer so that the cost of system is minimized. The long-term objective is to determine the loading pattern of the transformer which guaranties the most economical pattern among various options. Results showed that the proposed model is efficiently capable of returning more accurate responses if real-time monitoring data is used. A set of sensitivity analysis studies are also performed to highlight the impact of each factor separately. The contribution of distributed generators to supply the load is also investigated. Results showed that the use of distributed generators reduces the overall cost of the system by diminishing the risk-based element of the system cost. © 2023 University of Mohaghegh Ardabili. All rights reserved.
IET Generation, Transmission and Distribution (17518687)18(8)pp. 1517-1527
Unbalanced operation of distribution networks, as a crucial but inevitable aspect of power quality, brings about economic and technical issues. The increase in active power loss is more concerning due to the economic and technical implications. Economic sustainability of liberalized distribution networks is hugely tied to the availability of transparent and effective approaches to determine the stakeholders of this sort of phenomenon. This is done by awarding/penalizing them accordingly. Studies in the literature have not considered the incremental losses that unbalanced operations cause to distribution systems. Here, a mathematical approach based on vector analysis in the symmetrical components space is introduced. This approach quantifies the contribution of each unbalanced load to unbalanced operation and increased power losses. This technique discriminates between the mutual effects of different unbalanced loads on the power losses of the entire network. By means of the proposed approach, the best candidate unbalanced load(s)/location(s) to perform the corrective balancing actions and their ranking are precisely specified. Vector representation of the developed method simplifies its understanding, utilization, and expansion. For validation, the proposed method is applied to the IEEE 37-bus test distribution network under various scenarios. The results confirm the sound results and practical merits of the developed method. © 2024 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
Dadashzade, A.,
Bagherzadeh, H.,
Mottaghizadeh, M.,
Bolandi, T.G.,
Amirioun, M.H.,
Majidzadeh, M.,
Golshannavaz, S.,
Aminifar, F. Heliyon (24058440)10(16)
Resilience of the power system against natural disasters is a vital need for sustainable energy supply. As a result of global warming, lakes and rivers have dried out, resulting in dust hubs that threaten the normal operation of outdoor power system equipment. Unlike other events like hurricanes and blizzards, the impact of extreme salt dust on power system insulator failures and network resilience in affected areas remains unexamined. In this paper, to avoid power curtailment caused by insulators breakdown in electricity distribution networks, the resiliency assessment and enhancement of these networks against salt dust is investigated. Failure mechanism analysis of insulators and fragility curves extraction of them in face of salt pollution and relative humidity are done using mathematical modelling and experimental tests to extract the breakdown probability; Experimental tests are conducted in the High Voltage Laboratory, University of Tehran (HVLUT) and a novel method is proposed to extract 3-dimensional fragility curves of insulators. A Monte Carlo-based resiliency assessment method is then employed to obtain resiliency curve against the salt dust. Some suitable indicators are introduced for this purpose. In addition, several resiliency enhancement measures are proposed and ranked using a benefit to cost ratio (BCR) index. Numerical simulations are conducted on two real distribution feeders in a distribution grid around Urmia Salt Lake, Iran. Numerical results confirm the effectiveness and applicability of the proposed method. © 2024 The Authors
This article presents a planning framework to improve the weather-related resilience of natural gas–dependent electricity distribution systems. The problem is formulated as a two-stage stochastic mixed integer linear programing model. In the first stage, the measures for distribution line hardening, gas-fired distributed generation (DG) placement, electrical energy storage resource allocation, and tie-switch placement are determined. The second stage minimizes the electricity distribution system load shedding in realized hurricanes to achieve a compromise between operational benefits and investment costs when the dependence of electricity distribution system on the natural gas exists. The proposed stochastic model considers random failures of electricity distribution system lines and random errors in forecasting the load demand. The Monte Carlo simulation is employed to generate multiple scenarios for defining the uncertainties of electricity distribution system. For the sake of simplicity, weather-related outages of natural gas pipelines are considered deterministic. The nonlinear natural gas constraints are linearized and incorporated into the stochastic optimization model. The proposed framework was successfully implemented on an interconnected energy system composed of a 33-bus electricity distribution system and a 14-node natural gas distribution network. Numerical results of the defined case studies and a devised comparative study validate the effectiveness of the proposed framework as well. © 2024 Society for Risk Analysis.
Mohseni, M.,
Eajal, A.A.,
Amirioun, M.H.,
Al-durra, A.,
El-saadany, E. International Journal of Electrical Power and Energy Systems (01420615)147
This paper presents a proactive operation scheme for improving distribution system resiliency against natural hazards, specifically windstorms. In this context, important attributes associated with the windstorm consisting the distance from the windstorm route, the wind speed, the distance from tall trees and buildings, and cable type are used in a deep neural network (DNN) engine to identify the vulnerable branches and predict their failure during the windstorm. The DNN predictive model is integrated in the proposed scheme. Afterwards, a power flow-based optimization engine is employed to proactively enhance the grid resiliency. Grid resiliency is measured by the inevitable action of load shedding. For minimum load shedding, the optimization engine reconfigures the network topology, optimizes the droop parameter settings, and allocates mobile energy storage systems (ESSs) before the arrival of the windstorm. This optimization engine is integrated in the proposed scheme. To validate its performance, the proposed proactive scheme is tested on a 33-bus test system with a mix of diesel units (DUs), wind turbines (WTs), and photovoltaic units (PVs). The simulation results demonstrate that without the proposed learning mechanism, the load shedding can reach up to 36% for the system under study, while the learning-based scheme can reduce the load shedding to 13%. The proposed learning-based proactive operation scheme would substantially improve the distribution system resiliency during windstorms. © 2022
IET Generation, Transmission and Distribution (17518687)17(23)pp. 5223-5239
This paper presents a multi-objective restoration scheme for improving the resilience of integrated electricity and natural gas distribution systems against extreme weather events. The coupling constraints of electricity and gas networks are tackled properly using a linearized optimal power flow (OPF). Distributed generators, power-to-gas facility, rescheduling of generation/storage units, and microgrid formation are employed as operational resources/measures for restoring the integrated energy system after the event landfall. An adaptable directed multi-commodity flow-based microgrid formation is utilized, that is, the network configuration is dynamically changed in accordance with time-variant load priority weights. The proposed method was successfully examined on an integrated electricity and natural gas distribution system comprised of the modified IEEE 33-bus distribution network and a 14-node natural gas distribution network. Numerical results showed that using microgrid formation increased the supplied critical load of integrated electricity and natural gas distribution system by about 16%. Moreover, due to making benefit of the power-to-gas unit, the supplied critical load increased by about 12.3%. respectively. While utilizing energy storage systems along with the power-to-gas unit facilitated the exchange of energy between the power distribution network and natural gas distribution network regarding time-variant load priority weights, the supplied critical load increased by about 13%. © 2023 The Authors. IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.
Journal of Advanced Transportation (01976729)2023
As autonomous electric vehicles and car-sharing services are becoming more popular, the contribution of shared autonomous electric vehicles (SAEVs) to the future of urban transportation is getting more achievable. Like conventional electric vehicles, SAEVs can provide power grids with ancillary services. This article proposes a new scheduling scheme for SAEV fleets within a cooperative plan to let power distribution networks benefit from the energy storage of vehicle batteries in recovering critical loads after a predictable extreme event. According to a long-term contract, the detailed request of the distribution system operator (DSO), together with desired constraints and perquisites, is sent to the SAEVs aggregator (SA) prior to the landfall of a predictable extreme event. Afterward, SA runs a targeted algorithm to schedule trip assignments and charging cycles of SAEVs so that the required constraints of DSO are satisfied. The SAEV participants will continue carrying passengers within the scheduled time horizon in addition to delivering energy to the distribution network at the scheduling deadline declared by DSO. This deadline is the time instant when the capacity of the SAEV fleet may be no more applicable to enhance the system preparedness against the approaching event. Numerical results illustrated that the proposed scheme helps improve the power grid resilience by delivering 2396.1 kWh of energy to the distribution network in addition to increasing the total income of each participant SAEV by about 130%. Thus, it is implied that the proposed method offers a win-win situation for both entities. © 2023 Mohammad Hassan Amirioun et al.
Gilani, M.A.,
Dashti, R.,
Ghasemi, M.,
Amirioun, M.H.,
Shafie-khah, M. Sustainable Cities and Society (22106715)83
In recent years, resilience enhancement of electricity distribution systems has attracted much attention due to the significant rise in high-impact rare (HR) natural event outages. The performance of the post-event restoration after an HR event is an effective measure for a resilient distribution network. In this paper, a multi-objective restoration model is presented for improving the resilience of an electricity distribution network. In the first objective function, the load shedding in the restoration process is minimized. As the second objective function, the restoration cost is minimized which contradicts the first objective function. Microgrid (MG) formation, distributed energy resources (DERs), and demand response (DR) programs are employed to create the necessary flexibility in distribution network restoration. In the proposed model, DERs include fossil-fueled generators, renewable wind-based and PV units, and energy storage system while demand response programs include transferable, curtailable, and shiftable loads. The proposed multi-objective model is solved using ɛ-constraint method and the optimal solution is selected using the fuzzy satisfying method. Finally, the proposed model was successfully examined on 37-bus and 118-bus distribution networks. Numerical results verified the efficacy of the proposed method as well. © 2022
International Transactions on Electrical Energy Systems (20507038)31(12)
In each regulatory period, the parameters of the reward and penalty scheme (RPS) vary based on the investment made by electricity distribution companies (EDCs) and imposed costs. In this paper, a novel dynamic model for determining the RPS parameters for each EDC is presented. This new model has three stages: (i) determination of the RPS parameters for the first regulatory period, (ii) the RPS decision-making model, and (iii) determination of the RPS parameters for the subsequent regulatory period. The proposed model was implemented for Iranian EDCs. Results verified the effectiveness of the proposed model in enhancing distribution system reliability. © 2021 John Wiley & Sons Ltd.
Utilities Policy (09571787)64
Public-lighting is a prominent subsector of the electricity distribution network. Removing upcoming challenges of the public-lighting system is an important necessity in network expansion planning. The public-lighting management structure is composed of three main participants: the regulatory unit, lighting managers, and private contractors. Each participant faces challenges in achieving its aims. This study investigates challenges in the areas of human resource management, cost estimation, price assignment, and time scheduling for private-sector contracting. Applying the reliability model of public-lighting lamps, the health status of lamps during the system operation is forecasted. In addition, to give a comprehensive solution for the mentioned challenges, the proposed strategies are optimized in terms of cost and risk. The results of this case study of the public-lighting system demonstrate the efficiency of the proposed method in alleviating the challenges of public-lighting managers, including optimal assignment of price and duration of contracts. In addition, the operating cost of the public-lighting system, an important challenge for lighting contractors, is minimized via a human resource management scheme. © 2020 Elsevier Ltd
International Journal of Electrical Power and Energy Systems (01420615)104pp. 716-723
Recent extreme weather events have emphasized the need for new methods and metrics to assess the power system resilience in response to high-impact low-probability (HILP) events. Microgrids (MGs) have been instrumental in such occasions for maintaining the power supply continuity to local customers. This paper provides a quantitative framework for assessing the MG resilience in response to HILP windstorms. The proposed framework jointly employs fragility curves of overhead distribution branches and windstorm profile to quantify the degradation in the MG performance (particularly supplied load in this work). The proposed analytical method is simple and computationally efficient which offers a quick means for getting knowledge about adverse impacts of an approaching windstorm and taking preventive measures accordingly. A set of normalized metrics is defined which provides a comparable tool for assessing the resilience in various operating conditions and power systems. The impacts of restorative actions, the system reinforcement, and the event severity on resilience curves and metrics are also investigated. The effectiveness of the proposed approach in response to an extreme windstorm is examined on a real-scale MG test bed. © 2018 Elsevier Ltd
IEEE Transactions on Power Systems (08858950)34(3)pp. 2160-2168
Proactive preparedness is the key necessity of power systems to successfully cope with high-impact rare (HR) events. A resilience-oriented proactive methodology is proposed in this paper, which aims at enhancing the preparedness of multiple energy carrier microgrids (MECMs) against an approaching hurricane. First, the hurricane-originated contingency chain of MECM is characterized, which is different from that of single energy carrier distribution networks. The contingency chain includes natural gas interruption within the MECM, islanding event, and hurricane landfall on MECM. The pre-event scheduling horizon is then defined from the first alert declaration of hurricane to the worst-case (the earliest instant) of hurricane landfall on MECM. The preparedness index is defined as the sum of electric and thermal energy storage at the end of the scheduling horizon. Enhancing the proposed preparedness index will be at the expense of additional load curtailment during the scheduling horizon. Thus, a compromise is made between the two conflicting objectives (preparedness index and load supply) via a multi-objective optimization problem. An integrated gas and electricity power flow is proposed in a linear computationally efficient fashion capable of modeling gas interruption and islanding event. The effectiveness of the proposed methodology is examined on a real-scale MECM. © 1969-2012 IEEE.
IEEE Transactions on Power Systems (08858950)33(4)pp. 4275-4284
This paper presents a microgrid (MG) proactive management framework to cope with adverse impacts of extreme windstorms. Upon receiving alerts for the forecasted windstorm, the framework finds a conservative schedule of MG with the minimum number of vulnerable branches in service while total load is served. The schedule ensures the MG normal operation prior to the windstorm while reducing the MG vulnerability at the event onset. The proposed method makes benefit of network reconfiguration, generation reschedule, conservation voltage regulation, optimal parameter settings of droop-controlled units, demand-side resources, and backup generation capacity. A vulnerability index is defined to assess the effectiveness of the proposed proactive management in reducing the MG vulnerability at the event onset. The proposed model is linearized that guarantees simplicity, robustness, and computational efficiency of the solution. The effectiveness of the proposed method is tested on a real-scale MG against a windstorm. © 1969-2012 IEEE.
Gholami, A.,
Shekari, T.,
Amirioun, M.H.,
Aminifar, F.,
Amini, M.H.,
Sargolzaei, A. IEEE Access (21693536)6pp. 32035-32053
This paper analyzes the notion of resilience in power systems from a fundamental viewpoint and thoroughly examines its practical implications. This paper aims to describe and classify different high-impact rare (HR) events, provide a more technical definition of power system resilience, and discuss linkages between resilience and other well-established concepts, such as security and reliability. Most relevant decisions of system operators in the face of HR events involve a significant level of stress and strain. In order to make informed decisions within this context, it is crucial to have an all-inclusive picture of the state of the system. This paper provides an appropriate framework that not only characterizes the various states of the system but also derives informed decisions from a resilience-oriented perspective. It also describes and analyzes diverse resilience improvement strategies. Comprehensive models and classifications are provided to clearly capture various aspects of power system resilience. © 2013 IEEE.
IEEE Transactions on Smart Grid (19493053)9(4)pp. 3900-3902
This letter proposes a proactive scheduling for resilience enhancement of microgrids (MGs). Just ahead of the flood arrival, the MG is shifted to a state less impacted and stressed by the upcoming event. To do this, vulnerable components are first recognized. Tripping out all vulnerable components, proactive measures are employed to minimize the preventive load curtailment. The solution is then applied as the proactive schedule of MG which is robust against the flood threat. The effectiveness of the proposed method is examined on a real-scale MG. © 2010-2012 IEEE.
Utilities Policy (09571787)32pp. 19-28
In this paper, an asset-management model is proposed to address challenges facing regulators, managers, and operators of public-lighting systems and suggest optimal performance strategies. A new method is presented to estimate the failure rate of lamps based on the normal distribution function. The impact of technology improvement in lamp manufacturing as well as the growth and extension of lighting systems on the failure rate are investigated. In order to achieve satisfaction of customers and risk reduction, a method for establishing a performance standard for lamp failure rates is presented. Considering technical and economic issues, a procedure for selecting the best lamp in the market and then estimating costs associated with system operation is described. Finally, a methodology is proposed for evaluating performance in public-lighting systems. Results of a case study for the public-lighting system of the newly constructed suburb of the city of Isfahan, Iran, show the efficacy of the proposed method. © 2014 Elsevier Ltd.
Energy (18736785)69pp. 186-198
As electric vehicles offer a promising choice to deal with the growing air pollution and the global consumption of fossil fuels in the future smart grids, integrating their full benefit in the power system should be of a high priority. Numerous studies surveyed the possibility of charging/discharging modes of vehicles such as vehicle-to-grid, grid-to vehicle and vehicle-to-building and one introduced a new mode as vehicle-to-vehicle. However, none of them considered all available modes in a study. In the future smart grids, electric vehicles will be integrated with other generation or consumption parts such as distributed energy resources, smart homes and the external grid. As a result, a comprehensive perspective toward the simultaneous scheduling of combined energy exchange modes should be established. In this paper, advantages of 18 energy exchange modes are integrated. The presented model facilitates the participation of sub-aggregators in the aggregation of electric vehicles in a residential complex. The complex consists of a smart building and a smart parking lot. The proposed model promises higher income for sub-aggregators and less energy not charged for vehicles while ensuring the convenience for residents. This will result in more incentive for both sub-aggregators and residents to cooperate. © 2014 Elsevier Ltd.
This paper evaluates the effect of possible energy policy changes on multi-objective optimal design and planning of a hybrid energy system. The study was performed for a remote area near Esfarjan, a village located in Shahreza, Iran. In the main scenario, the current energy policy is examined, while the sensitivity analysis scenario applies the near future condition that is gradually taking place by reducing the energy subsidies. Simulations have been done on six different system configurations for the both scenarios considering the two mentioned policies for electricity price, fuel price and environmental issues. Results show that in sensitivity scenario, in contrast with the main scenario, the renewable-grid configuration is more economical than the grid-only dependent system, which in turn will result in more interest in investing on renewable resources. Finally, the energy modeling software for hybrid renewable energy systems, HOMER is used in this study. © 2013 IEEE.
This paper studies the optimal planning of a renewable based energy supply plan for a residential building. It has been assumed tha the building involves a platform equipped with smart communication and metering infrastructures, recalling the smart home (SH) concept. The best economically optimal model is choosed in each case based on the net present cost (NPC) and the cost of energy (COE) criteria. Mutual effects of the inflation rate uncertainty, project life-time span and a comparative model to study the use of combined heat and power (CHP) technology on the objective function have been modelled. An economic index related to environmental issues and one related to the thermal load supply have been defined and analysed. Finally a conclusion has been done according to results achieved throughout the study. © 2013 IAEEE.
This paper investigates the optimal management of a renewable based energy supply design for a residential building equipped with smart communication and metering infrastructures, approaching the smart home (SH) concept. The best economically optimal model is selected in each case based on the net present cost (NPC) and the cost of energy (COE) criteria. Mutual effects of the inflation rate uncertainty, project lifetime span and a comparative model to study the use of combined heat and power (CHP) technology on the objective function have been modelled. An economic index related to environmental issues and one related to the thermal load supply have been defined and analysed. Finally a conclusion has been done according to results achieved throughout the study. © 2013 IEEE.
