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Due to their particular feature, DC Electric Arc Furnace (EAF) installations are peculiar loads that cause moderate to severe Power Quality (PQ) disturbances in the feeding power systems. Among them, voltage fluctuations and waveform distortions are the most impactful ones, and they should be adequately addressed in order to mitigate the detrimental effects. Several types of models have been developed in order to evaluate the effects of EAFs on networks, and chaotic models have been specifically recognized as suitable tools to evaluate the impact of EAFs in terms of PQ disturbances. This paper compares the performance of three chaotic models (Chua, Lorenz and Rssler) aiming at estimating PQ indices values of DC EAFs. The procedure exploits a block diagramming tool of the DC EAF installation and minimizes the deviation of estimated PQ indices from the actual ones through a new Monte Carlo optimization procedure, performed upon the parameters of the three chaotic models. To comply with the time-varying nature of the current and voltage waveforms in a DC EAF installation and with the wide presence of interharmonics, traditional and advanced PQ indices are considered in this paper. Actual data collected at an Italian DC EAF installation are used to conduct a numerical comparative analysis and to validate the effectiveness of the models in estimating the PQ disturbances.
Antonio Bracale; Pierluigi Caramia; Guido Carpinelli; Pasquale Defalco; Angela Russo. Comparison of DC Electric Arc Furnace Chaotic Models for Power Quality Indices Assessment. IEEE Transactions on Industry Applications 2021, PP, 1 -1.
AMA StyleAntonio Bracale, Pierluigi Caramia, Guido Carpinelli, Pasquale Defalco, Angela Russo. Comparison of DC Electric Arc Furnace Chaotic Models for Power Quality Indices Assessment. IEEE Transactions on Industry Applications. 2021; PP (99):1-1.
Chicago/Turabian StyleAntonio Bracale; Pierluigi Caramia; Guido Carpinelli; Pasquale Defalco; Angela Russo. 2021. "Comparison of DC Electric Arc Furnace Chaotic Models for Power Quality Indices Assessment." IEEE Transactions on Industry Applications PP, no. 99: 1-1.
Operating electrical networks by Dynamic Transformer Rating (DTR) unlocks the capacity of grids and allows to increase the exploitation of distributed generation and renewables. However, there is risk associated with the operation of transformers by DTR. Energy dispatch and/or load curtailment must be scheduled before the actual energy delivery, thus DTR and load should be predicted prior the actual transformer loading. Since both are random variables, this problem is prone to be addressed by stress-strength analysis. In this paper, the novel comprehensive probabilistic tool “SmarTrafo” is presented. It allows predicting the probability of the DTR to be greater than the load (i.e., the probability of success) through an exact analytic stress-strength model, and formulating an alarm-setting strategy in order to establish a warning if the expected probability is greater than a threshold. Specifically, the threshold is optimized in a multi-objective formulation, exploiting three different indices which differently evaluate the predictive skill of alarm-setting strategy. Numerical experiments based on actual data confirm the suitability of the proposal in predicting the probability of success and in establishing high-performance alarms based on such predictions.
Antonio Bracale; Pierluigi Caramia; Guido Carpinelli; Pasquale De Falco. SmarTrafo: A Probabilistic Predictive Tool for Dynamic Transformer Rating. IEEE Transactions on Power Delivery 2020, 36, 1619 -1630.
AMA StyleAntonio Bracale, Pierluigi Caramia, Guido Carpinelli, Pasquale De Falco. SmarTrafo: A Probabilistic Predictive Tool for Dynamic Transformer Rating. IEEE Transactions on Power Delivery. 2020; 36 (3):1619-1630.
Chicago/Turabian StyleAntonio Bracale; Pierluigi Caramia; Guido Carpinelli; Pasquale De Falco. 2020. "SmarTrafo: A Probabilistic Predictive Tool for Dynamic Transformer Rating." IEEE Transactions on Power Delivery 36, no. 3: 1619-1630.
Industrial load takes a big portion of the total electricity demand. Skilled probabilistic industrial load forecasts allow for optimally exploiting energy resources, managing the reserves, and market bidding, which are beneficial to transmission and distribution system operators and their industrial customers. Despite its importance, industrial load forecasting has never been a popular subject in the literature. Most existing methods operate on the active power alone, partially or totally neglecting the reactive power. This paper proposes a multivariate approach to probabilistic industrial load forecasting, which addresses active and reactive power simultaneously. The proposed method is based on a two-level procedure, which consists of generating probabilistic forecasts individually for active and reactive power through univariate probabilistic models, and combining these forecasts in a multivariate approach based on a multivariate quantile regression model. The procedure to estimate the parameters of the multivariate quantile regression model is posed in this paper under a linear programming problem, to facilitate the convergence to the optimal solution. The proposed method is validated using actual load data collected at an Italian factory, under comparison with several probabilistic benchmarks. The proposed multivariate method enhances the skill of forecasts by 6% to 13.5%, with respect to univariate benchmarks.
Antonio Bracale; Pierluigi Caramia; Pasquale De Falco; Tao Hong. A Multivariate Approach to Probabilistic Industrial Load Forecasting. Electric Power Systems Research 2020, 187, 106430 .
AMA StyleAntonio Bracale, Pierluigi Caramia, Pasquale De Falco, Tao Hong. A Multivariate Approach to Probabilistic Industrial Load Forecasting. Electric Power Systems Research. 2020; 187 ():106430.
Chicago/Turabian StyleAntonio Bracale; Pierluigi Caramia; Pasquale De Falco; Tao Hong. 2020. "A Multivariate Approach to Probabilistic Industrial Load Forecasting." Electric Power Systems Research 187, no. : 106430.
The paper investigates the renewal of a hybrid trolley-bus, powered by a 600 V DC overhead electrical grid. The analysis focuses on replacing the on-board internal combustion engine (ICE) with a battery-based power unit. A novel two-step optimization procedure is proposed for this purpose. The procedure compares the solutions in terms of the total cost sustained by the ownership. By means of an iterative method, the optimal size of the battery unit is designed as a function of power and energy requirements, taking into account cycle life, depth of discharge, working temperature, replacement, and the requirements of the transport service operator. Using the real measurements taken on a trolley-bus operating in the city center of Naples (Italy), several numerical simulations are performed. The simulations examine three alternative Lithium high specific power and energy batteries. The comparison of the results allows to select the best solution among the different technologies for the proposed application.
Luisa Alfieri; Antonio Bracale; Pierluigi Caramia; Diego Iannuzzi; Mario Pagano. Optimal battery sizing procedure for hybrid trolley-bus: A real case study. Electric Power Systems Research 2019, 175, 105930 .
AMA StyleLuisa Alfieri, Antonio Bracale, Pierluigi Caramia, Diego Iannuzzi, Mario Pagano. Optimal battery sizing procedure for hybrid trolley-bus: A real case study. Electric Power Systems Research. 2019; 175 ():105930.
Chicago/Turabian StyleLuisa Alfieri; Antonio Bracale; Pierluigi Caramia; Diego Iannuzzi; Mario Pagano. 2019. "Optimal battery sizing procedure for hybrid trolley-bus: A real case study." Electric Power Systems Research 175, no. : 105930.
Photovoltaic systems (PVSs) are among the most diffuse Distributed Generators based on renewable energy sources. PVSs contribute to the short-circuit currents during a fault, modifying the short-circuit capacity of the distribution systems. Then, the contribution of PVSs to the fault current must be adequately modeled to extend the traditional short-circuit analysis to distribution networks with PVSs. In this paper an analytical model based on the phase-coordinates approach is proposed to evaluate the fault contributions of three-phase PVSs connected to unbalanced distribution networks in presence of symmetrical and asymmetrical shunt short-circuits, with and without fault impedance. The model of the PVS takes into account the environmental conditions, the inverter control system, the maximum current that can flow through the inverter switching devices, the filter, the interface transformer and the self-protections imposed by the Standard IEEE 1547. Both a first cycles and a steady-state model of the PVS are developed accounting for inverter control systems equipped with VAr or LVRT control schemes or inverter control system without reactive power regulation. The model of the PVS is applied to a typical North American MV network and the results of the proposed approach are compared with time-domain simulations.
G. Carpinelli; A. Bracale; P. Caramia; A.R. Di Fazio. Three-phase photovoltaic generators modeling in unbalanced short-circuit operating conditions. International Journal of Electrical Power & Energy Systems 2019, 113, 941 -951.
AMA StyleG. Carpinelli, A. Bracale, P. Caramia, A.R. Di Fazio. Three-phase photovoltaic generators modeling in unbalanced short-circuit operating conditions. International Journal of Electrical Power & Energy Systems. 2019; 113 ():941-951.
Chicago/Turabian StyleG. Carpinelli; A. Bracale; P. Caramia; A.R. Di Fazio. 2019. "Three-phase photovoltaic generators modeling in unbalanced short-circuit operating conditions." International Journal of Electrical Power & Energy Systems 113, no. : 941-951.
Short-term probabilistic load forecasting is essential to power systems management and optimization of power flows across transmission networks. Developing forecasting tools capable of providing accurate predictions must comply with their practical implementation in short-term operations, mainly in terms of fast computing and high efficiency. Many data-driven forecasting solutions are often unnecessarily verbose, thus making their practical value limited. This problem occurs more frequently when multiple loads have to be predicted simultaneously, as in power transmission system analysis and optimization. In this paper, we propose a new cooperative forecasting system that refines probabilistic forecasts of individual loads online. The refining procedure is based on a multivariate quantile regression, which is dynamically applied to the individual forecasts as new observations become available. The proposal is validated on the load data published by ISO New England for eight regions, covering six States of the United States. The quality of probabilistic forecasts is assessed in terms of reliability and sharpness, comparing the results to three benchmarks. The proposed method outperforms the best benchmark by up to 6% w.r.t. the reduction in pinball loss.
Antonio Bracale; Pierluigi Caramia; Pasquale De Falco; Tao Hong. Multivariate Quantile Regression for Short-Term Probabilistic Load Forecasting. IEEE Transactions on Power Systems 2019, 35, 628 -638.
AMA StyleAntonio Bracale, Pierluigi Caramia, Pasquale De Falco, Tao Hong. Multivariate Quantile Regression for Short-Term Probabilistic Load Forecasting. IEEE Transactions on Power Systems. 2019; 35 (1):628-638.
Chicago/Turabian StyleAntonio Bracale; Pierluigi Caramia; Pasquale De Falco; Tao Hong. 2019. "Multivariate Quantile Regression for Short-Term Probabilistic Load Forecasting." IEEE Transactions on Power Systems 35, no. 1: 628-638.
This paper presents a probabilistic model for supporting the process of decision making about the value of new lighting systems in existing road tunnels when some data and parameters are affected by uncertainty. The proposed model, which we have called Probabilistic Energy Screening of Tunnel (PrEST), accounts for both the technical performance and the economic objectives of the new lighting systems. The technical performance is described on an adequate (x, y) plane that was defined by two indices. The first index measured the consumption of electricity per kilometre of tunnel lengths; the second index measured the performance of the lighting systems per unit of illuminated area. The economic results were measured by the net present value of the savings and by the payback period. Both the terms account for initial capital investments, energy and maintenance costs. PrEST was applied to two real road tunnels in service in Italy showing that the statistics of the results can support a final decision in function of the business strategy.
Antonio Bracale; Pierluigi Caramia; Pietro Varilone; Paola Verde. Probabilistic Estimation of the Energy Consumption and Performance of the Lighting Systems of Road Tunnels for Investment Decision Making. Energies 2019, 12, 1488 .
AMA StyleAntonio Bracale, Pierluigi Caramia, Pietro Varilone, Paola Verde. Probabilistic Estimation of the Energy Consumption and Performance of the Lighting Systems of Road Tunnels for Investment Decision Making. Energies. 2019; 12 (8):1488.
Chicago/Turabian StyleAntonio Bracale; Pierluigi Caramia; Pietro Varilone; Paola Verde. 2019. "Probabilistic Estimation of the Energy Consumption and Performance of the Lighting Systems of Road Tunnels for Investment Decision Making." Energies 12, no. 8: 1488.
Antonio Bracale; Pierluigi Caramia; Pasquale De Falco; Andrea Michiorri; Angela Russo. Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried Cables. IEEE Access 2018, 7, 4709 -4725.
AMA StyleAntonio Bracale, Pierluigi Caramia, Pasquale De Falco, Andrea Michiorri, Angela Russo. Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried Cables. IEEE Access. 2018; 7 ():4709-4725.
Chicago/Turabian StyleAntonio Bracale; Pierluigi Caramia; Pasquale De Falco; Andrea Michiorri; Angela Russo. 2018. "Day-Ahead and Intraday Forecasts of the Dynamic Line Rating for Buried Cables." IEEE Access 7, no. : 4709-4725.
This chapter focuses on the optimal sizing of BESSs in end-user applications in the frame of time-varying energy pricing structures by adopting a probabilistic approach. More in detail, the proposed procedure focuses on one of the most used time-varying tariff structures (i.e. the ToU tariff) but it can be easily extended to other structures. In this chapter, starting from the procedure proposed, the probabilistic optimal sizing is performed applying the point estimate method (PEM), an algorithm that guarantees accuracy of the results with computational effort significantly lower than that implied by the Monte Carlo procedure.
Guido Carpinelli; Pierluigi Caramia; Fabio Mottola; Daniela Proto. Sizing of battery energy storage for end-user applications under time of use pricing. Energy Storage at Different Voltage Levels: Technology, integration, and market aspects 2018, 147 -172.
AMA StyleGuido Carpinelli, Pierluigi Caramia, Fabio Mottola, Daniela Proto. Sizing of battery energy storage for end-user applications under time of use pricing. Energy Storage at Different Voltage Levels: Technology, integration, and market aspects. 2018; ():147-172.
Chicago/Turabian StyleGuido Carpinelli; Pierluigi Caramia; Fabio Mottola; Daniela Proto. 2018. "Sizing of battery energy storage for end-user applications under time of use pricing." Energy Storage at Different Voltage Levels: Technology, integration, and market aspects , no. : 147-172.
Appropriate forecasts of the dynamic rating of buried cables can be exploited by networks operators to significantly increase the power transport capacity of medium voltage and low voltage distribution systems, without sacrificing the normal life of the cables. However, forecasting the effects of the soil conditions on the dynamic rating of the buried cable is not an easy task. In this paper, a detailed procedure is proposed to deal with this problem. The proposed procedure handles the changing environmental conditions by exploiting a thermal-hydraulic model of the soil and a model for the thermal exchange between the buried cable and the surrounding soil. The forecasts of external influencing variables, such as precipitations and soil temperature, and of cable currents, needed as inputs of the proposed procedure, are obtained by means of a Support Vector Regression technique. Numerical applications based on actual load and weather data confirmed the suitability of the procedure, encouraging for further research on the topic.
Antonio Bracale; Pierluigi Caramia; Pasquale De Falco; Angela Russo. A New Procedure to Forecast the Dynamic Rating of Buried Cables. 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) 2018, 1190 -1195.
AMA StyleAntonio Bracale, Pierluigi Caramia, Pasquale De Falco, Angela Russo. A New Procedure to Forecast the Dynamic Rating of Buried Cables. 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM). 2018; ():1190-1195.
Chicago/Turabian StyleAntonio Bracale; Pierluigi Caramia; Pasquale De Falco; Angela Russo. 2018. "A New Procedure to Forecast the Dynamic Rating of Buried Cables." 2018 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM) , no. : 1190-1195.
In this paper, a probabilistic method is proposed to analyze the very short-term steady-state performance of an unbalanced distribution electrical system characterized by the presence of wind farms. This method, which can take into account the uncertainties of loads and wind productions, is based on a Monte Carlo simulation procedure applied to the non-linear three-phase load flow equations, including wind farm models. Bayesian time series models are used to predict the next hour's wind speed probability density functions, making possible a predictive evaluation of the very short-term system steady-state behavior. Numerical applications are presented and discussed with reference to the three-phase unbalanced IEEE 34-bus test distribution system in the presence of wind farms connected at different busbars.
Antonio Bracale; Pierluigi Caramia; Guido Carpinelli; Pietro Varilone. A Probability Method for Very Short-Term Steady State Analysis of a Distribution System with Wind Farms. ENERGYO 2018, 1 .
AMA StyleAntonio Bracale, Pierluigi Caramia, Guido Carpinelli, Pietro Varilone. A Probability Method for Very Short-Term Steady State Analysis of a Distribution System with Wind Farms. ENERGYO. 2018; ():1.
Chicago/Turabian StyleAntonio Bracale; Pierluigi Caramia; Guido Carpinelli; Pietro Varilone. 2018. "A Probability Method for Very Short-Term Steady State Analysis of a Distribution System with Wind Farms." ENERGYO , no. : 1.
Guido Carpinelli; Renato Rizzo; Pierluigi Caramia; Pietro Varilone. Taguchi's method for probabilistic three-phase power flow of unbalanced distribution systems with correlated Wind and Photovoltaic Generation Systems. Renewable Energy 2018, 117, 227 -241.
AMA StyleGuido Carpinelli, Renato Rizzo, Pierluigi Caramia, Pietro Varilone. Taguchi's method for probabilistic three-phase power flow of unbalanced distribution systems with correlated Wind and Photovoltaic Generation Systems. Renewable Energy. 2018; 117 ():227-241.
Chicago/Turabian StyleGuido Carpinelli; Renato Rizzo; Pierluigi Caramia; Pietro Varilone. 2018. "Taguchi's method for probabilistic three-phase power flow of unbalanced distribution systems with correlated Wind and Photovoltaic Generation Systems." Renewable Energy 117, no. : 227-241.
In this paper, we analysed the growing penetration of generating units from renewable energy sources in transmission power systems. Among the possible effects of the interaction of distributed generation (DG) with transmission systems, we considered the abnormal operating conditions caused by short circuits in the transmission systems and the resulting voltage sags that occur in the network. A systematic method is presented for analysing the voltage sag behaviour of any transmission system in which large DG units are connected to the transmission system by means of High Voltage/Medium Voltage (HV/MV) stations. The method proposed for obtaining the voltage sags is the fault position method (FPM), from which we derived a graphical visualization of the during-fault voltage (DFV) matrix as a valuable tool to obtain an immediate measure of the propagation of voltage sags in the network. The results obtained were based on a portion of a real transmission system. The system that we considered is an actual portion of the Italian transmission system, and all of the quantities we used were obtained from the data of the Transmission system operator (TSO).
Pierluigi Caramia; Enrica Di Mambro; Pietro Varilone; Paola Verde. Impact of Distributed Generation on the Voltage Sag Performance of Transmission Systems. Energies 2017, 10, 959 .
AMA StylePierluigi Caramia, Enrica Di Mambro, Pietro Varilone, Paola Verde. Impact of Distributed Generation on the Voltage Sag Performance of Transmission Systems. Energies. 2017; 10 (7):959.
Chicago/Turabian StylePierluigi Caramia; Enrica Di Mambro; Pietro Varilone; Paola Verde. 2017. "Impact of Distributed Generation on the Voltage Sag Performance of Transmission Systems." Energies 10, no. 7: 959.
Voltage stability (VS) has become a fundamental issue in the new, liberalised markets due to the fact that the new power systems are approaching more and more the stability limits. Then, several approaches were proposed in the relevant literature to find the critical conditions and recently the problem was faced also with reference to unbalanced three-phase power systems. The unbalances, in fact, can be responsible of more critical stability conditions than in balanced power systems. Continuation power flow and optimal power flows were applied to analyse such conditions. This study deals with VS analysis in unbalanced power systems and proposes a new optimisation model to determine the critical point based on the use of complementarity constraints. In particular, the maximum stability margin is calculated by a single-stage or a multistage procedure that accounts for the relationship between the actual operating point and the maximum loading point. In addition, the multistage maximum stability margin problem is formulated also in a probabilistic framework to account for the uncertainties affecting the input data (e.g. load powers). An application is presented on a test system highlighting the feasibility and the goodness of the proposed technique.
Guido Carpinelli; Pierluigi Caramia; Angela Russo; Pietro Varilone. Voltage stability in unbalanced power systems: a new complementarity constraints‐based approach. IET Generation, Transmission & Distribution 2015, 9, 2014 -2023.
AMA StyleGuido Carpinelli, Pierluigi Caramia, Angela Russo, Pietro Varilone. Voltage stability in unbalanced power systems: a new complementarity constraints‐based approach. IET Generation, Transmission & Distribution. 2015; 9 (14):2014-2023.
Chicago/Turabian StyleGuido Carpinelli; Pierluigi Caramia; Angela Russo; Pietro Varilone. 2015. "Voltage stability in unbalanced power systems: a new complementarity constraints‐based approach." IET Generation, Transmission & Distribution 9, no. 14: 2014-2023.
Antonio Bracale; Pierluigi Caramia; Guido Carpinelli; E. Mancini; F. Mottola. Optimal control strategy of a DC micro grid. International Journal of Electrical Power & Energy Systems 2015, 67, 25 -38.
AMA StyleAntonio Bracale, Pierluigi Caramia, Guido Carpinelli, E. Mancini, F. Mottola. Optimal control strategy of a DC micro grid. International Journal of Electrical Power & Energy Systems. 2015; 67 ():25-38.
Chicago/Turabian StyleAntonio Bracale; Pierluigi Caramia; Guido Carpinelli; E. Mancini; F. Mottola. 2015. "Optimal control strategy of a DC micro grid." International Journal of Electrical Power & Energy Systems 67, no. : 25-38.
Guido Carpinelli; Pierluigi Caramia; Pietro Varilone. Multi-linear Monte Carlo simulation method for probabilistic load flow of distribution systems with wind and photovoltaic generation systems. Renewable Energy 2015, 76, 283 -295.
AMA StyleGuido Carpinelli, Pierluigi Caramia, Pietro Varilone. Multi-linear Monte Carlo simulation method for probabilistic load flow of distribution systems with wind and photovoltaic generation systems. Renewable Energy. 2015; 76 ():283-295.
Chicago/Turabian StyleGuido Carpinelli; Pierluigi Caramia; Pietro Varilone. 2015. "Multi-linear Monte Carlo simulation method for probabilistic load flow of distribution systems with wind and photovoltaic generation systems." Renewable Energy 76, no. : 283-295.
There is an increasing interest in standards and technical literature to the probabilistic characterization of voltage and current harmonics in multi-convertor power systems. The characterization requires to express the input data of the harmonic penetration modelling by random variables and to apply probabilistic techniques of analysis. Among probabilistic approaches, Monte Carlo simulation is widely applied even if it requires high computational efforts. This paper describes a probabilistic approach for harmonic analysis of a multi-convertor power system which takes into account the interactions among the grid voltage distortions and the converter current harmonics. In order to reduce the computational efforts, the Point Estimate Method (PEM) is applied as an alternative to Monte Carlo simulation. PEM permits to account for the uncertainties that affect the evaluation of the steady state operating conditions in the presence of non linear loads and allows us to obtain the first moments of the output random variables of interest through the solution of only few deterministic harmonic power flows. Numerical applications to a test system are presented to demonstrate the accuracy and speed of the proposed method.
Angela Russo; P. Varilone; Pierluigi Caramia. Point estimate schemes for probabilistic harmonic power flow. 2014 16th International Conference on Harmonics and Quality of Power (ICHQP) 2014, 19 -23.
AMA StyleAngela Russo, P. Varilone, Pierluigi Caramia. Point estimate schemes for probabilistic harmonic power flow. 2014 16th International Conference on Harmonics and Quality of Power (ICHQP). 2014; ():19-23.
Chicago/Turabian StyleAngela Russo; P. Varilone; Pierluigi Caramia. 2014. "Point estimate schemes for probabilistic harmonic power flow." 2014 16th International Conference on Harmonics and Quality of Power (ICHQP) , no. : 19-23.
Distribution networks are undergoing radical changes due to the high level of penetration of dispersed\ud generation and storage systems. This trend is strongly modifying the structure as well as the management\ud of distribution networks, which are progressively approaching the new concept of microgrids\ud (MGs). Also, the level of penetration of storage systems for plug-in electric vehicles (PEVs) is increasing\ud significantly due to the significant potential that PEVs have for reducing both emission levels and transportation\ud costs. The inclusion of these vehicles in MGs leads to a series of challenges in grid operation,\ud especially ensuring the provision of services that can improve the operation of distribution networks.\ud This paper deals with MGs, including renewable generation plants and aggregators of PEV fleets\ud connected to the grid through power electronic devices. A multi-objective optimization model is\ud presented for obtaining optimal, coordinated operation of MGs. A multi-objective model was solved using\ud two different methods, i.e., the exponential weighted criterion method and a compromise programming\ud method. Both of these methods appeared to be particularly suitable when computational time is an\ud important issue, as it is in the case of optimal control. The effectiveness of the multi-objective approach\ud was demonstrated with numerical applications to a low-voltage microgrid; other multi-objective\ud model-solving algorithms also were assessed in order to compare their programming complexity and\ud the computational efforts required
Guido Carpinelli; Pierluigi Caramia; Fabio Mottola; Daniela Proto. Exponential weighted method and a compromise programming method for multi-objective operation of plug-in vehicle aggregators in microgrids. International Journal of Electrical Power & Energy Systems 2014, 56, 374 -384.
AMA StyleGuido Carpinelli, Pierluigi Caramia, Fabio Mottola, Daniela Proto. Exponential weighted method and a compromise programming method for multi-objective operation of plug-in vehicle aggregators in microgrids. International Journal of Electrical Power & Energy Systems. 2014; 56 ():374-384.
Chicago/Turabian StyleGuido Carpinelli; Pierluigi Caramia; Fabio Mottola; Daniela Proto. 2014. "Exponential weighted method and a compromise programming method for multi-objective operation of plug-in vehicle aggregators in microgrids." International Journal of Electrical Power & Energy Systems 56, no. : 374-384.
Future distribution networks are undergoing radical changes, due to the high level of penetration of dispersed generation and information/communication technologies, evolving into the new concept of the Smart Grid. Dispersed generation systems, such as wind farms and photovoltaic power plants, require particular attention due to their incorporation of uncertain energy sources. Further and significant well-known uncertainties are introduced by the load demands. In this case, many new technical considerations must be addressed to take into account the impacts of these uncertainties on the planning and operation of distribution networks. This paper proposes novel Bayesian-based approaches to forecast the power production of wind and photovoltaic generators and phase load demands. These approaches are used in a probabilistic short-term steady-state analysis of a Smart Grid obtained by means of a probabilistic load flow performed using the Point Estimate Method. Numerical applications on a 30-busbar, low-voltage distribution test system with wind farms and photovoltaic power plants connected at different busbars are presented and discussed.
Antonio Bracale; Pierluigi Caramia; Guido Carpinelli; Anna Rita Di Fazio; Pietro Varilone. A Bayesian-Based Approach for a Short-Term Steady-State Forecast of a Smart Grid. IEEE Transactions on Smart Grid 2013, 4, 1760 -1771.
AMA StyleAntonio Bracale, Pierluigi Caramia, Guido Carpinelli, Anna Rita Di Fazio, Pietro Varilone. A Bayesian-Based Approach for a Short-Term Steady-State Forecast of a Smart Grid. IEEE Transactions on Smart Grid. 2013; 4 (4):1760-1771.
Chicago/Turabian StyleAntonio Bracale; Pierluigi Caramia; Guido Carpinelli; Anna Rita Di Fazio; Pietro Varilone. 2013. "A Bayesian-Based Approach for a Short-Term Steady-State Forecast of a Smart Grid." IEEE Transactions on Smart Grid 4, no. 4: 1760-1771.
Voltage stability has become a fundamental issue in the new, liberalized markets due to the fact that the new power systems are approaching more and more the stability limits. Then, several approaches were proposed in the relevant literature to find the critical conditions and the problem was faced also with reference to unbalanced three phase power systems. The unbalances, in fact, can be responsible of more critical stability conditions than in balanced power systems. Continuation power flow and optimal power flows were applied to analyze such conditions. In this paper a new three-phase optimal power flow is proposed that makes use of complementarity constraints to take into account the effect of reactive generation limits on voltage stability in unbalanced power systems. An application is presented on a test system highlighting the feasibility and the goodness of the proposed technique. Both load and line unbalances are taken into account to capture the dependence of voltage stability on the level of unbalances.
Guido Carpinelli; Pierluigi Caramia; Pietro Varilone. Voltage stability analysis in unbalanced three-phase power systems with complementarity constraints. 2013 13th International Conference on Environment and Electrical Engineering (EEEIC) 2013, 12 -17.
AMA StyleGuido Carpinelli, Pierluigi Caramia, Pietro Varilone. Voltage stability analysis in unbalanced three-phase power systems with complementarity constraints. 2013 13th International Conference on Environment and Electrical Engineering (EEEIC). 2013; ():12-17.
Chicago/Turabian StyleGuido Carpinelli; Pierluigi Caramia; Pietro Varilone. 2013. "Voltage stability analysis in unbalanced three-phase power systems with complementarity constraints." 2013 13th International Conference on Environment and Electrical Engineering (EEEIC) , no. : 12-17.