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The energy load requirements demanded to the network operator of the department of Huila are supplied according to corporate guidelines; but under the responsibility of the user, despite his technical-legal ignorance and the absence or inadequate technical advice, with the consequent irregularities in connections and, in fact, with economic and financial affectations. The analysis of this problem, with an exploratory scope, is approached with a quantitative and qualitative focus, which is deepened by means of the multiple case study strategy. In this way, an energy requirements guide and a tool, applicable during the phase prior to the load requisition, which allow to dynamize and improve the decision making process from the project management and the private investor., Los requerimientos de carga energética demandados ante el operador de red del departamento del Huila son suministrados según las pautas corporativas; pero bajo la responsabilidad del usuario, pese a su desconocimiento técnico legal y la ausencia o inadecuada asesoría técnica, con las consecuentes irregularidades en conexiones y, de hecho, con afectaciones económicas y financieras. El análisis de esta problemática, con alcance exploratorio, se aborda con un enfoque cuantitativo y cualitativo, el cual se profundiza mediante la estrategia de estudio de caso múltiple. De este modo se estructura una guía de requerimientos energéticos aplicables durante la fase previa a la requisición de cargas, que permiten dinamizar y mejorar el proceso de toma de decisiones desde la gerencia de proyectos y del inversionista privado.

The energy load requirements demanded to the network operator of the department of Huila are supplied according to corporate guidelines; but under the responsibility of the user, despite his technical-legal ignorance and the absence or inadequate technical advice, with the consequent irregularities in connections and, in fact, with economic and financial affectations. The analysis of this problem, with an exploratory scope, is approached with a quantitative and qualitative focus, which is deepened by means of the multiple case study strategy. In this way, an energy requirements guide and a tool, applicable during the phase prior to the load requisition, which allow to dynamize and improve the decision making process from the project management and the private investor., Los requerimientos de carga energética demandados ante el operador de red del departamento del Huila son suministrados según las pautas corporativas; pero bajo la responsabilidad del usuario, pese a su desconocimiento técnico legal y la ausencia o inadecuada asesoría técnica, con las consecuentes irregularidades en conexiones y, de hecho, con afectaciones económicas y financieras. El análisis de esta problemática, con alcance exploratorio, se aborda con un enfoque cuantitativo y cualitativo, el cual se profundiza mediante la estrategia de estudio de caso múltiple. De este modo se estructura una guía de requerimientos energéticos aplicables durante la fase previa a la requisición de cargas, que permiten dinamizar y mejorar el proceso de toma de decisiones desde la gerencia de proyectos y del inversionista privado.

This paper proposes a step-by-step technique for combining basic models that forecast electricity consumption in an artificial neural network by the method of preliminary selection and further hybridization. The reported experiments were conducted using data on hourly electricity consumption at the metallurgical plant AO ArcelorMittal Temirtau in the period from January 1, 2019, to November 30, 2021. The current research is related to the planned introduction of a balancing electricity market. 96 combinations of basic models were compiled, differing in the type of neural network, the set of initial data, the order of lag, the learning algorithm, and the number of neurons in the hidden layer. It has been determined that the NARX-type network is the most optimal architecture to forecast electricity consumption. Based on experimental studies, the number of hidden neurons needed to form a planned daily profile should equal 3 or 4; it is recommended to use the conjugate gradient method as a learning algorithm. When selecting models from three groups, it was revealed that the conjugate gradient method produces better results compared to the Levenberg-Marquardt algorithm. It is determined that the values of the selected RMSE error indicator take values of 23.17, 22.54, and 22.56, respectively, for the first, second, and third data groups. The adaptive hybridization method has been shown to reduce the RMSE error rate to 21.73. However, the weights of the best models with values of 0.327 for the first group of data, and 0.336 for the second and third ones, show that the individual use of a separate combination of models is also applicable. The devised forecasting electricity consumption model can be integrated into an automated electricity metering system

It systems allow power to be transferred from one electrical network to another electrical network without need for wires or exposed contacts. There has been rapid expansion of WPT in mobile phone chargers and electric bulb and charging electric vehicles and dynamic charging electric vehicles, also called road powered electric vehicles. It is expected that WPT industry will grow  persistently in coming decaded, commonly wireless power transfers are conducted using an inductive coupling and followed by magnetic induction, we use magnetic induction using copper wire with a diameter. The wireless power transfer field would be in high demand for electric power to be supplied in the future.

It is known that Sweden is categorised by being one of the regions that experience low solar radiation because it is located in the northern hemisphere that has a low potential of solar radiation during the colder seasons. The government of Sweden aim to promote a more sustainable future by applying more renewable initiative in the energy sector. One of the initiatives is by applying more renewable energy where PV panels will play a greater role in our society and in the energy sector. However, the produced energy from the PV panels is unpredictable due to changes in radiation throughout the day. One great way to tackle this issue is by combining PV panels with different energy storage system. This thesis evaluates an off-grid rowhouse in Eskilstuna Sweden where the PV panels are combined with a heat pump, thermal storage tank, including batteries and hydrogen system. The yearly electrical demand is met by utilizing PV panels, battery system for short term usage and hydrogen system for long-term usage during the colder seasons. The yearly thermal demand is met by the thermal storage tank. The thermal storage tank is charged by heat losses from the hydrogen system and thermal energy from heat pump.The calculations were simulated in Excel and MATLAB where OPTI-CE is composed with different components in the energy system. Furthermore, the off-grid household was evaluated from an economic outlook with respect to today’s market including the potential price decrease in 2030.The results indicated that the selected household is technically practicable to produce enough energy. The PV panels produces 13 560 kWh annually where the total electrical demand reaches 6 125 kWh yearly (including required electricity for the heat pump). The annual energy demand in terms of electricity and thermal heat reaches 12 500 kWh which is covered by the simulated energy system. The overproduction is stored in the batteries and hydrogen storage for later use. The back-up diesel generator doe

It is known that Sweden is categorised by being one of the regions that experience low solar radiation because it is located in the northern hemisphere that has a low potential of solar radiation during the colder seasons. The government of Sweden aim to promote a more sustainable future by applying more renewable initiative in the energy sector. One of the initiatives is by applying more renewable energy where PV panels will play a greater role in our society and in the energy sector. However, the produced energy from the PV panels is unpredictable due to changes in radiation throughout the day. One great way to tackle this issue is by combining PV panels with different energy storage system. This thesis evaluates an off-grid rowhouse in Eskilstuna Sweden where the PV panels are combined with a heat pump, thermal storage tank, including batteries and hydrogen system. The yearly electrical demand is met by utilizing PV panels, battery system for short term usage and hydrogen system for long-term usage during the colder seasons. The yearly thermal demand is met by the thermal storage tank. The thermal storage tank is charged by heat losses from the hydrogen system and thermal energy from heat pump.The calculations were simulated in Excel and MATLAB where OPTI-CE is composed with different components in the energy system. Furthermore, the off-grid household was evaluated from an economic outlook with respect to today’s market including the potential price decrease in 2030.The results indicated that the selected household is technically practicable to produce enough energy. The PV panels produces 13 560 kWh annually where the total electrical demand reaches 6 125 kWh yearly (including required electricity for the heat pump). The annual energy demand in terms of electricity and thermal heat reaches 12 500 kWh which is covered by the simulated energy system. The overproduction is stored in the batteries and hydrogen storage for later use. The back-up diesel generator doe

It systems allow power to be transferred from one electrical network to another electrical network without need for wires or exposed contacts. There has been rapid expansion of WPT in mobile phone chargers and electric bulb and charging electric vehicles and dynamic charging electric vehicles, also called road powered electric vehicles. It is expected that WPT industry will grow  persistently in coming decaded, commonly wireless power transfers are conducted using an inductive coupling and followed by magnetic induction, we use magnetic induction using copper wire with a diameter. The wireless power transfer field would be in high demand for electric power to be supplied in the future.

It systems allow power to be transferred from one electrical network to another electrical network without need for wires or exposed contacts. There has been rapid expansion of WPT in mobile phone chargers and electric bulb and charging electric vehicles and dynamic charging electric vehicles, also called road powered electric vehicles. It is expected that WPT industry will grow  persistently in coming decaded, commonly wireless power transfers are conducted using an inductive coupling and followed by magnetic induction, we use magnetic induction using copper wire with a diameter. The wireless power transfer field would be in high demand for electric power to be supplied in the future.

Offered systematization of statistical methods for clusterization the graphs of electrical loads based on wavelet-coefficients. With the wavelet-analysis can not only reveal the characteristic frequency of the signal, but also obtain information about specific local coordinates at which these frequencies occur. In terms of nonlinearity and apperiodically initial information wavelet-transformed the graphs of electrical loads is treated by applying known statistical clustering methods. Systematization of clustering methods optimizes the transformed data selection decisions. Depending on the goals we choose that method of calculation, which will provide the necessary level of information content of the resulting data, the applicability for further processing, speed and reversibility of computation., Пропонується систематизація статистичних методів кластеризації графіків електричних навантажень на основі вейвлет-коефіцієнтів. За допомогою вейвлет-аналізу можна не тільки виявити характерні частоти сигналу, але й отримати відомості про конкретні локальні координати, при яких проявляються ці частоти. В умовах нелінійності та аперіодичності вихідної інформації вейвлет-перетворені графіки електричних навантажень опрацьовують, застосовуючи відомі статистичні методи кластеризації. Систематизація статистичних методів кластеризації перетворених даних оптимізує вибір найбільш ефективного методу вирішення. Залежно від поставлених задач визначається такий метод розрахунку, який забезпечить необхідний рівень інформативності результатних даних, застосовність розрахункових даних для подальшої обробки, високу швидкість і відновленість обчислень.

Short-term electrical load forecasting is an important part in the management of electrical power because electrical load is an extreme, complex non-linear system. To obtain parameter values that provide better performances with high precision, this paper proposes a new hybrid electrical load forecasting model, which combines ensemble empirical mode decomposition, extreme learning machine, and grasshopper optimization algorithm for short-term load forecasting. The most important difference that distinguishes this electrical load forecasting model from other models is that grasshopper optimization can search suitable parameters (weight values and threshold values) of extreme learning machine, while traditional parameters are selected randomly. It is applied in Australia electrical load prediction to show its superiority and applicability. The simulation studies are carried out using a data set collected from five main states (New South Wales, Queensland, Tasmania, South Australia and Victoria) in Australia from February 1 to February 27, 2018. Compared with all considered basic models, the proposed hybrid model has the best performance in predicting electrical load.

Much of the existing electricity supply system equipment was put into operation in 60 - 80s of the twentieth century. It is therefore important to be able to properly assess the condition of power transformers, to determine the admissibility of certain modes of operation, determine their resource isolation and predict the allowable lifetime. In this paper we consider the power oil transformers selection problem using stochastic models based on different criteria – namely, oil and most heated point temperature of transformer and it’s insulation wear. For this task, simulation of transformer oil and most heated point temperature and the relative deterioration of its insulation was performed to provide their statistical characteristics primarily determined by quantile functions for corresponding probabilities.

Unlike deterministic selection models, which often leads to significant errors, stochastic selection models can use more adequate model of electrical load as a random process that can be both periodic and non-periodic. In this paper presented the method of oil transformers power selection according to the criteria of their heating and acceptable insulation wear from thermal model according MGOST 14209-97 using statistical characteristics of the electric load as a non-periodic random process. This simulation was carried out by modelling oil and most heated point temperature of the transformer and the relative deterioration of its insulation to provide their statistical characteristics primarily determined by the quantile function with corresponding probabilities. Also presented a comparison of this approach with a selection in which the load is considered as stationary random process.

The topic of this dissertation is a short-term load forecasting using artificial intelligence methods. Three new models with least squares support vector machines for nonlinear regression are proposed. First proposed model is a model with forecasting in two stages. This model use additioal feature, maximum daily load which is not known for day ahead. Forecating of maximum daily load is obtained in the first stage. This forecasted value is used in second stage, where forecasting of hourly load is done. Model with feature selection, using mutual information for selection criteria, is a second proposed model. This model tries to find an optimal feature set for a given problem. Forecasting model based on an incremental update scheme is a third proposed model. This model is based on the incremental update of the initial training set by adding new instances into it as soon as they become available and throwing out the old ones. Then the model is trained with new training set. By this approach the evolving nature of the load pattern is followed and the model performance is preserved and improved. For models evaluation, the forecasting of hourly loads for one year is done. Electrical consumption data for the City of Niš, which have about 260000 habitans and average daily demand of 182 MW, is used for testing. Double sesonal ARIMA and Holt-Winters as representatives of clasical models and artificial neural networks, least squares support vector machines and relevance vector machines as representatives of artificial models, are used for models evaluation. For a measure of accuracy, mean absolute percentage error, symetrical mean absolute percentage error, square root mean error and absolute percentage error are used. Obtained results show that the best model is model with incremental update scheme, followed by double sesonal ARIMA and artificial neural networks models. The worst results are obtained by relevance vector machines and double sesonal Holt-Winters models. It has b

In this paper we propose a novel approach to schedule electric loads with the aim of reducing households' energy cost or CO2 emission with acceptable change in comfort. The approach involves both shifting households' electrical loads to times when the electricity prices or CO2 intensities are low, and reducing households' electrical loads at times when electricity prices or CO2 intensities are high. This approach assumes availability of day ahead hourly data of CO2 emissions and/or electricity cost from the external service provider. We categorize energy loads in two groups; constant and one-shot loads. Constant loads ensure environmental comfort for a consumer (e.g., heating, ventilation), while one-shot loads have a more dynamic nature (e.g., smart appliances, EV charging). Our approach is a best effort approach suitable for resource constrained embedded systems., QC 20160210

All electrical loads need a power grid that delivers electricity with good quality. Current harmonics are a measure of how the electrical loads affect the power quality. Voltage harmonics are a measure on how the electrical loads are affected by the power quality and depend on both the power grid's strength and the current harmonics.This study examines and maps the harmonic voltages and currents in the low voltage grid by analysing 61 measurements which were done in Vattenfall’s electricity distribution grid during 2013. The study compiles guidelines and recommended levels for voltage harmonics in the low voltage grid from government agencies (Energimarknadsinspektionen), industry associations (CENELEC, Svensk Energi), companies (STRI) and Vattenfall’s planning levels and levels for good power quality . The study covers the guidelines and the recommended levels for current harmonics from government agencies (Elsäkerhetsverket), American and German engineering practices and from power grid companies (EON, Fortum and Öresundskraft). How the harmonic content in the 61 measurements relates to different values of voltage and current is also studied.The study suggests that there is reason to set requirements for the harmonics emission in customer agreements. The customers' current harmonics can be used in power quality analysis and in dialogue with customers. The trend among the recommended levels is that emission limit for current harmonics is based on the subscription's size alternatively maximum electrical load but also on network strength.The measurements indicate that the relationship between network strength and voltage harmonics is affected by the current harmonics such that a reduction of network strength does not increase the harmonic content of the voltage, which would have been expected. The relationship can be explained when voltage harmonics from a higher voltage levels dominate the voltage distortion in the low-voltage grid.The study indicates that the limit, Validerat; 20151016 (global_studentproject_submitter)

Knivsta municipality is planning a new climate-friendly and environmentally sustainable district called Nydal. The vision is to create a residential area that is minimally dependent on outside sources of electricity. The aim of this research is to evaluate the efficiency and electricity demand of a residential house in Knivsta. A model for the power demand of an apartment house has been constructed, using data for the electricity consumption of one household from Kiruna during a week in April. Data from the Swedish Energy Agency has been used to identify the distribution of electricity for the different loads. This study has focused on the electricity consumption of a family that consist of two adults and one child and their use of home appliances. A comparison between standard appliances and energy efficiency appliances has been made to find out how much the power and their load peaks can be reduced. The total amount of electricity consumption for the residential building’s households is about 93 MWh during a year. By selecting energy efficient appliances in the apartments the total household electricity consumption of the residential building can be reduced by about 55 MWh, which is almost a 60 % reduction per year. The residential buildings load peaks can be reduced. This can be achieved by installing energy efficient products by using Top Ten’s list over the most energy saving household appliances available on the market. Installing LED lamps and HWC driven products also reduces the power demand significantly. By installing HWC driven products in the common washhouse, the residential electricity can be reduced by 29 %. A more environment-friendly lifestyle affects the electric load. The power demand can decrease if buying less power demanding products, but also by using the power demanding products in a more energy efficient way. Knivsta municipality is able to help the tenants in Nydal to increase their knowledge. By increasing the individuals’ knowledge about

Knivsta municipality is planning a new climate-friendly and environmentally sustainable district called Nydal. The vision is to create a residential area that is minimally dependent on outside sources of electricity. The aim of this research is to evaluate the efficiency and electricity demand of a residential house in Knivsta. A model for the power demand of an apartment house has been constructed, using data for the electricity consumption of one household from Kiruna during a week in April. Data from the Swedish Energy Agency has been used to identify the distribution of electricity for the different loads. This study has focused on the electricity consumption of a family that consist of two adults and one child and their use of home appliances. A comparison between standard appliances and energy efficiency appliances has been made to find out how much the power and their load peaks can be reduced. The total amount of electricity consumption for the residential building’s households is about 93 MWh during a year. By selecting energy efficient appliances in the apartments the total household electricity consumption of the residential building can be reduced by about 55 MWh, which is almost a 60 % reduction per year. The residential buildings load peaks can be reduced. This can be achieved by installing energy efficient products by using Top Ten’s list over the most energy saving household appliances available on the market. Installing LED lamps and HWC driven products also reduces the power demand significantly. By installing HWC driven products in the common washhouse, the residential electricity can be reduced by 29 %. A more environment-friendly lifestyle affects the electric load. The power demand can decrease if buying less power demanding products, but also by using the power demanding products in a more energy efficient way. Knivsta municipality is able to help the tenants in Nydal to increase their knowledge. By increasing the individuals’ knowledge about

The assessment of failure mechanisms in electrical systems due to electrical connector in a vibrating media often relies on only one type of electrical environment, i.e. resistive load. However, these are not capable of digging out the behavior of connectors when the electrical system includes other electrical environments, for instance inductive load. The aim of the thesis is to fill this gap, by studying how the damages of electrical contacts in a vibrating environment depend on the electrical environments, in heavy vehicles. The purpose is to investigate, what effects current and voltage have in each electrical environment related to connector’s lifespan and reliability. The main failure mechanism in the connector with tin coated cable terminals are fretting corrosion which is induced by micro oscillatory motion due to vibration and thermal fluctuation. To do so a serie of experimental studies has been conducted for different samples of electrical connectors.

The assessment of failure mechanisms in electrical systems due to electrical connector in a vibrating media often relies on only one type of electrical environment, i.e. resistive load. However, these are not capable of digging out the behavior of connectors when the electrical system includes other electrical environments, for instance inductive load. The aim of the thesis is to fill this gap, by studying how the damages of electrical contacts in a vibrating environment depend on the electrical environments, in heavy vehicles. The purpose is to investigate, what effects current and voltage have in each electrical environment related to connector’s lifespan and reliability. The main failure mechanism in the connector with tin coated cable terminals are fretting corrosion which is induced by micro oscillatory motion due to vibration and thermal fluctuation. To do so a serie of experimental studies has been conducted for different samples of electrical connectors.

The assessment of failure mechanisms in electrical systems due to electrical connector in a vibrating media often relies on only one type of electrical environment, i.e. resistive load. However, these are not capable of digging out the behavior of connectors when the electrical system includes other electrical environments, for instance inductive load. The aim of the thesis is to fill this gap, by studying how the damages of electrical contacts in a vibrating environment depend on the electrical environments, in heavy vehicles. The purpose is to investigate, what effects current and voltage have in each electrical environment related to connector’s lifespan and reliability. The main failure mechanism in the connector with tin coated cable terminals are fretting corrosion which is induced by micro oscillatory motion due to vibration and thermal fluctuation. To do so a serie of experimental studies has been conducted for different samples of electrical connectors.

The assessment of failure mechanisms in electrical systems due to electrical connector in a vibrating media often relies on only one type of electrical environment, i.e. resistive load. However, these are not capable of digging out the behavior of connectors when the electrical system includes other electrical environments, for instance inductive load. The aim of the thesis is to fill this gap, by studying how the damages of electrical contacts in a vibrating environment depend on the electrical environments, in heavy vehicles. The purpose is to investigate, what effects current and voltage have in each electrical environment related to connector’s lifespan and reliability. The main failure mechanism in the connector with tin coated cable terminals are fretting corrosion which is induced by micro oscillatory motion due to vibration and thermal fluctuation. To do so a serie of experimental studies has been conducted for different samples of electrical connectors.

The assessment of failure mechanisms in electrical systems due to electrical connector in a vibrating media often relies on only one type of electrical environment, i.e. resistive load. However, these are not capable of digging out the behavior of connectors when the electrical system includes other electrical environments, for instance inductive load. The aim of the thesis is to fill this gap, by studying how the damages of electrical contacts in a vibrating environment depend on the electrical environments, in heavy vehicles. The purpose is to investigate, what effects current and voltage have in each electrical environment related to connector’s lifespan and reliability. The main failure mechanism in the connector with tin coated cable terminals are fretting corrosion which is induced by micro oscillatory motion due to vibration and thermal fluctuation. To do so a serie of experimental studies has been conducted for different samples of electrical connectors.

The assessment of failure mechanisms in electrical systems due to electrical connector in a vibrating media often relies on only one type of electrical environment, i.e. resistive load. However, these are not capable of digging out the behavior of connectors when the electrical system includes other electrical environments, for instance inductive load. The aim of the thesis is to fill this gap, by studying how the damages of electrical contacts in a vibrating environment depend on the electrical environments, in heavy vehicles. The purpose is to investigate, what effects current and voltage have in each electrical environment related to connector’s lifespan and reliability. The main failure mechanism in the connector with tin coated cable terminals are fretting corrosion which is induced by micro oscillatory motion due to vibration and thermal fluctuation. To do so a serie of experimental studies has been conducted for different samples of electrical connectors.

Central utility services are increasingly networked systems that use an interconnection of sensors and programmable logic controllers, and feed data to servers and human-machine interfaces. These systems are connected to the Internet so that they can be accessed remotely, and the network in these plants is structured according to the SCADA model. Although the physical systems themselves are generally designed with high degrees of safety in mind, and designers of computer systems are well advised to incorporate computer security principles, a combined framework for supervisory control of the physical and cyber architectures in these systems is still lacking. Often absent are provisions to defend against external and internal attacks, and even operator errors that might bypass currently standalone security measures to cause undesirable consequences. In this paper we examine a prototypical instance of SCADA network in the distribution network that handles central cooling and heating for a set of buildings. The electrical loads are networked through programmable logic controllers (PLCs), electrical meters, and networks that deliver data to and from servers that are part of a SCADA system, which has grown in size and complexity over many years.

Central utility services are increasingly networked systems that use an interconnection of sensors and programmable logic controllers, and feed data to servers and human-machine interfaces. These systems are connected to the Internet so that they can be accessed remotely, and the network in these plants is structured according to the SCADA model. Although the physical systems themselves are generally designed with high degrees of safety in mind, and designers of computer systems are well advised to incorporate computer security principles, a combined framework for supervisory control of the physical and cyber architectures in these systems is still lacking. Often absent are provisions to defend against external and internal attacks, and even operator errors that might bypass currently standalone security measures to cause undesirable consequences. In this paper we examine a prototypical instance of SCADA network in the distribution network that handles central cooling and heating for a set of buildings. The electrical loads are networked through programmable logic controllers (PLCs), electrical meters, and networks that deliver data to and from servers that are part of a SCADA system, which has grown in size and complexity over many years.

In a boundaries of hydro – electroelastic tasks the perspective research of directional properties many-modes electroelastic systems was showed. The solution of this task to give a chance for the regulating the directional characteristics this transducers system by traditional waves methods and methods of superdirective antennas, with put together properties coupled modes many-modes electroelastic cylindrical transducers

We consider convex stochastic programs with an (approximate) initial probability distribution P having finite support supp P, i.e., finitely many scenarios. Such stochastic programs behave stable with respect to perturbations of P measured in terms of a Fortet-Mourier probability metric. The problem of optimal scenario reduction consists in determining a probability measure which is supported by a subset of supp P of prescribed cardinality and is closest to P in terms of such a probability metric. Two new versions of forward and backward type algorithms are presented for computing such optimally reduced probability measures approximately. Compared to earlier versions, the computational performance (accuracy, running time) of the new algorithms is considerably improved. Numerical experience is reported for different instances of scenario trees with computable optimal lower bounds. The test examples also include a ternary scenario tree representing the weekly electrical load process in a power management model.

We consider convex stochastic programs with an (approximate) initial probability distribution P having finite support supp P, i.e., finitely many scenarios. Such stochastic programs behave stable with respect to perturbations of P measured in terms of a Fortet-Mourier probability metric. The problem of optimal scenario reduction consists in determining a probability measure which is supported by a subset of supp P of prescribed cardinality and is closest to P in terms of such a probability metric. Two new versions of forward and backward type algorithms are presented for computing such optimally reduced probability measures approximately. Compared to earlier versions, the computational performance (accuracy, running time) of the new algorithms is considerably improved. Numerical experience is reported for different instances of scenario trees with computable optimal lower bounds. The test examples also include a ternary scenario tree representing the weekly electrical load process in a power management model.

Many time series forecasting problems require the estimation of possibly inaccurate, but longterm, trends, rather than accurate short-term prediction. In this paper, a double use of the Self-Organizing Map algorithm makes it possible to build a model for longterm prediction, which is proven to be stable. The method uses the information on the structure of the series when available, by predicting blocs instead of scalar values. It is illustrated on real time series for both scalar and bloc predictions.