Change search
Refine search result
1 - 37 of 37
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Impact of dependencies in risk assessments of power distribution systems2008Licentiate thesis, monograph (Other scientific)
    Abstract [en]

     Society has become increasingly dependent on electricity, so power system reliability is of crucial importance. However, while underinvestment leads to an unacceptable number of power outages, overinvestment will result in costs that are too high for society. The challenge is to find a socioeconomically adequate level of risk. In this risk assessment, not only the probability of power outages, but also the severity of their consequences should be included.

     

    A risk assessment can be performed from either the perspective of customers or the perspective of the grid owner, depending on whether the consequences faced by customers or the grid owner are considered. Consequences of power outages are usually measured through interruption costs. Examples of interruption costs for the grid owner are customer compensations and loss of goodwill. Examples of interruption costs for customers are retail losses for commercial customers and loss of heating and lighting for residential customers. The aim of this thesis is to develop methods for assessing risks in power distribution systems from the customer-oriented perspective. From this perspective realistic assessments of customer interruption costs are essential.

     

    To perform a customer-oriented risk assessment of a distribution system three different models are required: a customer interruption cost model, a load model and a reliability model. The customer interruption cost model describes the consequences, or costs, of power outages that customers face. The load model predicts the loss of load and the energy not supplied due to power outages. The reliability model describes component failures, which are the root causes of power outages, and the restoration processes that follow. The three models can be used together in a cost-benefit analysis to investigate the consequences for customers due to different investment alternatives.

     

    In this thesis a set of new models is developed that incorporates time dependencies in customer interruption costs, load and component failures. The timing of the outage has an impact on the consequences customers face. Severe weather, which is a main contributor to component failures, is generally more common during certain seasons. These facts imply that there may be a correlation between high customer interruption costs and an increased risk for power outages. In Sweden the frequency of storms is higher during the cold period of the year when the demanded load and customer interruption costs are also high. By taking time dependencies into account, the correlation between high interruption costs and elevated risk for power outages is captured.

     

    Results from the risk assessments of two test distribution systems using the models developed in this thesis show that taking time dependencies into account has a considerable impact on the estimation of customer interruption costs and energy not supplied due to outages. To evaluate the risks of extreme costs, the tools Value-at-Risk and Conditional Value-at-Risk which are commonly used in the finance industry are applied. A conclusion that can be drawn from the simulation results is that taking time dependencies into account is especially important when considering extreme outage events that give rise to extreme costs.

  • 2.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Quality regulation of Distribution Networks2009Report (Other academic)
  • 3.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Risk-based methods for reliability investments in electric power distribution systems2011Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Society relies more and more on a continuous supply of electricity. However, while underinvestments in reliability lead to an unacceptable number of power interruptions, overinvestments result in too high costs for society. To give incentives for a socioeconomically optimal level of reliability, quality regulations have been adopted in many European countries. These quality regulations imply new financial risks for the distribution system operator (DSO) since poor reliability can reduce the allowed revenue for the DSO and compensation may have to be paid to affected customers.This thesis develops a method for evaluating the incentives for reliability investments implied by different quality regulation designs. The method can be used to investigate whether socioeconomically beneficial projects are also beneficial for a profit-maximizing DSO subject to a particular quality regulation design. To investigate which reinvestment projects are preferable for society and a DSO, risk-based methods are developed. With these methods, the probability of power interruptions and the consequences of these can be simulated. The consequences of interruptions for the DSO will to a large extent depend on the quality regulation. The consequences for the customers, and hence also society, will depend on factors such as the interruption duration and time of occurrence. The proposed risk-based methods consider extreme outage events in the risk assessments by incorporating the impact of severe weather, estimating the full probability distribution of the total reliability cost, and formulating a risk-averse strategy. Results from case studies performed show that quality regulation design has a significant impact on reinvestment project profitability for a DSO. In order to adequately capture the financial risk that the DSO is exposed to, detailed risk-based methods, such as the ones developed in this thesis, are needed. Furthermore, when making investment decisions, a risk-averse strategy may clarify the benefits or drawbacks of a project that are hard to discover by looking only at the expected net present value.

  • 4.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Awodele, Kehinde
    Impact of Reward and Penalty Scheme on the Incentives for Distribution System Reliability2014In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 29, no 1, p. 386-394Article in journal (Refereed)
    Abstract [en]

    Performance-based regulations accompanied by quality regulations are gaining ground in the electricity distribution business. Several European countries apply quality regulations with reward and penalty schemes (RPSs), where the distribution system operator (DSO) is rewarded (or penalized) when fulfilling (or not fulfilling) an adequate level of reliability to its customers. This paper develops a method that the regulator can use before enforcing a regulation to get an understanding of the impact different RPS design solutions have on the DSO's financial risk and incentives to invest in reliability. The proposed method also includes a sensitivity analysis to identify which are the most important parameters in an RPS. The new method is applied to three regulatory challenges to evaluate their RPS design solutions. Results show that the choice of scheme design and cost model used to decide the incentive rate have a large impact on the DSO's financial risk and incentive to invest.

  • 5.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Martin, Clyde
    Texas Tech University.
    The Feedback Control of Glucose: On the road to type II diabetes2006In: Proceedings of the 45th IEEE Conference on Decision & Control, 2006, p. 685-690Conference paper (Refereed)
    Abstract [en]

    This paper develops a mathematical model for the feedback control of glucose regulation in the healthy human being and is based on the work of Sorensen (1985). The proposed model serves as a starting point for modeling type H diabetes. Four agents - glucose and the three hormones insulin, glucagon, and incretins - are assumed to have an effect on glucose metabolism. By letting compartments represent anatomical organs, the model has a close resemblance to a real human body. Mass balance equations that account for blood flows, exchange between compartments, and metabolic sinks and sources are written, and these result in simultaneous differential equations that are solved numerically. The metabolic sinks and sources - removing or adding glucose, insulin, glucagon, and incretins - describe physiological processes in the body. These processes function as feedback control systems and have nonlinear behaviors. The results of simulations performed for three different clinical test types indicate that the model is successful in simulating intravenous glucose, oral glucose, and meals containing mainly carbohydrates.

  • 6.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    A Reliability Model for Distribution Systems Incorporating Seasonal Variations in Severe Weather2011In: IEEE Transactions on Power Delivery, ISSN 0885-8977, E-ISSN 1937-4208, Vol. 26, no 2, p. 910-919Article in journal (Refereed)
    Abstract [en]

    In distribution system planning and operation, accurate assessment of reliability performance is essential for making informed decisions. Also, performance-based regulation, accompanied by quality regulation, increases the need to understand and quantify differences in reliability performance between networks. Distribution system reliability performance indices exhibit stochastic behavior due to the impact of severe weather. In this paper, a new reliability model is presented which incorporates the stochastic nature of the severe weather intensity and duration to model variations in failure rate and restoration time. The model considers the impact of high winds and lightning and can be expanded to account for more types of severe weather. Furthermore, the modeling approach considers when severe weather is likely to occur during the year by using a nonhomogeneous Poisson process (NHPP). The proposed model is validated and applied to a test system to estimate reliability indices. Results show that the stochasticity in weather has a great impact on the variance in the reliability indices.

  • 7.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES).
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    A stochastic approach for modeling residential interruption costs2008In: 16th Power Systems Computation Conference, PSCC 2008, Power Systems Computation Conference (PSCC) , 2008Conference paper (Refereed)
    Abstract [en]

    In power system planning and operation, accurate assessment of reliability worth is essential for making informed decisions. The accuracy of the reliability worth estimation is directly affected by the interruption cost model used in the analysis. Residential interruption costs vary with season, day of week and time of day, and can be difficult to handle because of their intangible characteristics. This paper develops a cost model for residential customers that includes the timing of the outage by modeling the underlying factors that give rise to the temporal variations in residential interruption costs. By considering the stochastic nature of the underlying factors, as for example outdoor temperature, the proposed model makes it possible to estimate the costs for an event that is extreme in other senses than having a long duration. Time sequential Monte Carlo simulations were applied to a test system in order to assess reliability worth. The results show that the commonly used customer damage function overestimates the reliability worth. By accounting for the timing of the outages a more realistic estimation of the interruption costs can be obtained.

  • 8.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    A Stochastic Weather Dependent Reliability Model for Distribution Systems2008In: 2008 10TH INTERNATIONAL CONFERENCE ON PROBABILISTIC METHODS APPLIED TO POWER SYSTEMS, New York, USA: IEEE , 2008, p. 243-250Conference paper (Refereed)
    Abstract [en]

    In power system planning and operation, accurate assessment of reliability worth is essential for making informed decisions. One common simplification when modeling power system reliability is assuming constant failure rates and non time-varying restoration times. However, historical outages show differently; failure rates and restoration times for especially overhead lines are dependent upon time-varying factors as, for instance, weather conditions. When modeling this time dependence a two or three-state weather model is often used. The reliability model proposed in this paper does in contrast use the stochastic nature of the severe weather intensity and duration to model variations in failure rate and restoration time. Further, the model also considers when severe weather is likely to occur during the year by using a non-homogeneous Poisson process (NHPP). A time-sequential Monte Carlo technique is applied to a radial distribution system. By combining the proposed reliability model with a time-dependent interruption cost model, the effect of the inclusion of time-varying failure rates and restoration times is investigated and found to be of importance when assessing reliability worth.

  • 9.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    An activity-based interruption cost model for households to be used in cost-benefit analysis2007In: Proceedings of Power Tech 2007, 2007, p. 1611-1616Conference paper (Refereed)
    Abstract [en]

    This paper develops an interruption cost model for households that, as well as outage duration uses activity patterns, outdoor temperature and daylight to describe the impact of different electrical power outages. For households the interruption costs usually measure the inconvenience associated with interrupted activities and uncomfortable indoor temperature due to the outage. Further, the model also captures the large variations in interruption costs for identical outages among households. The model is applied to a test system, and using a Monte Carlo technique the total interruption cost is studied. The results imply that both the time of occurrence and the distributed nature of residential interruption costs have a significant impact on ECOST.

  • 10.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Comparison of cost models for estimating customer interruption costs2012In: Proceedings in Probabilistic Methods Applied to Power Systems (PMAPS), 2012Conference paper (Refereed)
    Abstract [en]

    Customer interruption costs are functions of many different factors such as interruption duration, timing and customer sector. Various cost models with different number of outage and customer characteristics included have been proposed during the years. This paper compares the customer interruption cost assessments of seven different cost models in a case study.Time sequential Monte Carlo simulations are used to simulate the customers’ benefits of increased reliability in a test system. The investigated cost models’ estimations of the Expected Customer Interruption Cost (ECOST) are compared and used in a costbenefitanalysis. Results show that the ECOST results are so different that the cost model choice affects the outcome of the cost-benefit analysis. Only when using some of the cost models the investigated reinvestments are estimated to be socioeconomically beneficial.

  • 11.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Considering extreme outage events in cost-benefit analysis of distribution systems2008In: Proceedings of Australasian Universities Power Engineering Conference (AUPEC), 2008Conference paper (Refereed)
    Abstract [en]

    To find an acceptable level of reliability in distribution systems, cost-benefit analysis using customer interruption costs can be applied. In a case study of a test distribution system, investment in cables instead of overhead lines, aimed to increase reliability, is investigated. In addition to considering average values of reliability indices, tools for risk analysis in the financial industry, value-at-risk (VaR) and conditional value-at-risk (CVaR), are also used for the evaluation. Applying these tools allows for extreme events to be given more weight in the investment decision-making process. Even though these kind of events are very infrequent, the consequences are devastating and extreme cases should be included in cost-benefit analysis. By the help of VaR and CVaR the case study shows that cables can cause higher customer interruption costs for some load points in the system during extreme years.

  • 12.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Evaluation of quality regulation incentives for distribution system reliability investments2011In: Utilities Policy, ISSN 0957-1787, E-ISSN 1878-4356Article in journal (Other academic)
    Abstract [en]

    Designing a quality regulation that results in an adequate level of reliability in a distribution system is indeed a challenging task for the regulator. If the regulation is not well designed a socioeconomically beneficial reinvestment project is not beneficial for the DSO, and hence is not selected. This paper proposes an evaluation method for quality regulation designs. The proposed method is applied in a case study to evaluate what incentives for investments in distribution system reliability two different quality regulation designs give. One design is similar to the Swedish quality regulation that will apply from 2012 and the other design is similar to the current Norwegian quality regulation. The effect on network investment decisions when the two designs are modified to give optimal incentives for reliability on system level is also investigated. The case study result shows that even though the quality regulation on system level is designed to give incentives for socioeconomically beneficial investments, these investments may not be beneficial for the regulated DSO if the reward/penalty on the system level is capped too low.

  • 13.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Financial risk assessment for distribution system operators regulated by quality regulation2010In: Proceedings of Probabilistic Methods Applied to Power Systems (PMAPS), 2010Conference paper (Refereed)
    Abstract [en]

    In the reregulated electricity market, performance-based regulations accompanied by quality regulations are gaining ground. The quality regulation results in new financial risks for the distribution system operators (DSOs) which calls for risk assessment methods that can simulate what costs a certain regulation implies for the DSO. When, for example, guaranteed standards for worst-served customers is combined with a reward and penalty scheme the methods must be able to predict both customer and system reliability. This paper presents a new risk assessment methodology based on time sequential Monte Carlo simulations that can handle both of these levels of reliability to simulate the total regulation cost due to an arbitrary quality regulation. Since most quality regulations are corrected ex-post for each year, variations in yearly reliability can cause large variations in the total regulation cost. Instead of only considering the average total regulation cost the developed methodology uses risk tools from the financial industry to also measure the costs of more extreme years. Doing so gives the DSOs a better understanding of the financial risks they are exposed to. The developed risk assessment methodology is used to evaluate different investment alternatives in a case study.

  • 14.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Quality regulation impact on investment decisions in distribution system reliability2012In: 9th International Conference on the European Energy Market, EEM 12, IEEE , 2012, p. 6254646-Conference paper (Refereed)
    Abstract [en]

    Performance-based regulations accompanied by quality regulations are gaining ground. Quality regulations imply new financial risks for the distribution system operator (DSO). In fact, the development of the regulatory model has been identified as a key factor in operations planning for a DSO. Lifetimes of distribution system components are very long and how the quality regulation might develop in the future is unknown. This paper develops a method - the regulation impact method - that can be used to investigate how changes in the quality regulation parameters affect the economic performance of an investment strategy. The proposed regulation impact method is based on net present value calculations of the total reliability cost. The new method is applied to the current Swedish quality regulation in a case study. In the case study, possible future parameter changes and their effect on the DSO's financial risk when adopting different investment strategies are investigated. With the new method it is possible to analyze how robust an investment strategy is to changes in quality regulation design.

  • 15.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Risk-based method for distribution system reliability investment decisions under performance-based regulation2011In: IET Generation, Transmission & Distribution, ISSN 1751-8687, Vol. 5, no 10, p. 1062-1072Article in journal (Refereed)
    Abstract [en]

    In the reregulated electricity market there is a growing interest in performance-based regulation accompanied by quality regulation for electric distribution networks. This paper develops a new risk-based method for reliability investment decisions when the distribution system operator (DSO) is exposed to financial risks defined by a quality regulation. As quality regulation design becomes more complex, more detailed risk management methods are needed in order to adequately capture the financial risk the DSO is exposed to. The proposed method applies a Monte Carlo simulation technique in order to assess the risks of the considered reinvestment projects. By using the proposed method the impacts that different risk strategies (risk-neutral/risk-averse) and risk models (non-time-varying/time-varying) have on which reinvestment project is selected is investigated in a case study. This is investigated for two different quality regulation designs. The result show that primarily the quality regulation design but also the risk model formulation and risk strategy have a major impact on which reinvestment project is selected.

  • 16.
    Alvehag, Karin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    The impact of risk modeling accuracy on cost-benefit analysis of distribution system reliability2011In: Proceedings of the 17th Power System Computational Conference (PSCC), Power Systems Computation Conference ( PSCC ) , 2011Conference paper (Refereed)
    Abstract [en]

    This paper develops a new risk-based cost-benefit analysis method for distribution system reliability applications. In the conventional cost-benefit analysis, decisions are based on expected values which correspond to assuming that society is risk-neutral. Furthermore, input variables are assumed to be uncorrelated. In contrast to previous work this paper incorporates risk into the analysis by using time-sequential Monte Carlo simulations. By using the proposed method the impact that different risk strategies (risk-neutral/risk-averse) and risk models (non-time-varying/time-varying) have on the result of a cost-benefit analysis is investigated in a case study. Results show that when incorporating time-dependent failure rates, restoration times, customer interruption costs, and loads (correlated input data) a different reinvestment project is selected compared to when these time dependencies are ignored. This result holds regardless if decisions are made based on a risk-averse or a risk-neutral strategy.

  • 17. Bartusch, C.
    et al.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Further exploring the potential of residential demand response programs in electricity distribution2014In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 125, p. 39-59Article in journal (Refereed)
    Abstract [en]

    Smart grids play a key role in realizing climate ambitions. Boosting consumption flexibility is an essential measure in bringing the potential gains of smart grids to fruition. The collective scientific understanding of demand response programs argues that time-of-use tariffs have proven its merits. The findings upon which this conclusion rests are, however, primarily derived from studies covering energy-based time-of-use rates over fairly short periods of time. Hence, this empirical study set out with the intention of estimating the extent of response to a demand-based time-of-use electricity distribution tariff among Swedish single-family homes in the long term. The results show that six years after the implementation households still respond to the price signals of the tariff by cutting demand in peak hours and shifting electricity consumption from peak to off-peak hours. Studies conducted in the Nordic countries commonly include only homeowners and so another aim of the study was to explore the potential of demand response programs among households living in apartment buildings. The demand-based tariff proved to bring about similar, but not as marked, effects in rental apartments, whereas there are virtually no corresponding evidences of demand response in condominium apartments.

  • 18. Brostrom, Elin
    et al.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Calculation of Residential Interruption Costs caused by Adverse Weather using Monte Carlo Methods2008Conference paper (Refereed)
    Abstract [en]

    The main contribution of this paper is a residential interruption cost model that aims to capture households? inconvenience due to power outages caused by adverse weather. Commonly, the customer interruption cost is modelled to be a function of the outage duration. However, other factors also affect the interruption cost. For example, the cost for a household increases if public services also are affected by the outage. The number of public services that a household cannot use is often correlated to the total number of customers affected by the outage. This relationship is explored in the proposed cost model in order to consider the impact of widespread and long-lasting outages caused by, for example, adverse weather. An adverse weather model gives wind and ice loads. These loads in combination with a vulnerability model for components in a transmission system and a restoration time model give the outage duration. In a case study, the impact of adverse weather on a meshed test system with residential customers is studied using Monte Carlo simulations. It is concluded that more surveys investigating the increased costs for households due to long-lasting and widespread outages are needed.

  • 19. Dzobo, O.
    et al.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Gaunt, C. T.
    Herman, R.
    Multi-dimensional customer segmentation model for power system reliability-worth analysis2014In: International Journal of Electrical Power & Energy Systems, ISSN 0142-0615, E-ISSN 1879-3517, Vol. 62, p. 532-539Article in journal (Refereed)
    Abstract [en]

    Accurate assessment of customer interruption costs is essential for making informed decisions in power system planning and operation. This paper presents a multi-dimensional customer segmentation model for reliability-worth analysis of power systems. The proposed model uses a hierarchical clustering technique to cluster electricity customers into customer segments of similar cost characteristics. Three customer parameters - economic size, economic activity and energy consumption are used in the proposed model. The proposed model is examined on two case studies from South Africa and Sweden, and results are compared to the conventional customer segmentation models. The effectiveness of the proposed model is determined based on the coefficient of variation of the final CIC estimates for different duration and time of occurrence of power interruptions. The results show a reduction in the dispersion of the final CIC estimates and thus allow CICs to be estimated from smaller survey samples.

  • 20. Edimu, M.
    et al.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Gaunt, C. T.
    Herman, R.
    Analyzing the performance of a time-dependent probabilistic approach for bulk network reliability assessment2013In: Electric power systems research, ISSN 0378-7796, E-ISSN 1873-2046, Vol. 104, p. 156-163Article in journal (Refereed)
    Abstract [en]

    The conventional sequential Monte Carlo Simulation (MCS) considers states in which a component is both in and out of service. Sequential MCS has been applied in different analyses whilst considering both symmetrical and asymmetrical probability distributions. The Beta distribution is however not one of the commonly recommended distributions for use in sequential MCS due to the complexity in deriving its inverse transform. A new sequential MCS technique that applies the Beta distribution is proposed in this paper. The technique is a time-dependent probabilistic approach (TDPA) that uses probability density functions (PDFs) to characterize stochastic network parameters in terms of their season- and time-dependency and simulates the component down (failure) states. The effect of this simulation approach on reliability calculations is analyzed using a published test network. The impact of dispersion and skewness in PDF based input models on a reliability analysis is also investigated. The results show that the TDPA can replicate the conventional sequential MCS analysis. The TDPA computation is also significantly faster. The simulation results of the TDPA also show that dispersion and skewness of component failure rate PDFs significantly influence a reliability analysis.

  • 21.
    Edström, Fredrik
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Rosenlind, Johanna
    KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Hilber, Patrik
    KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Influence of Ambient Temperature on Transformer Overloading During Cold Load Pickup2013In: IEEE Transactions on Power Delivery, ISSN 0885-8977, E-ISSN 1937-4208, Vol. 28, no 1, p. 153-161Article in journal (Refereed)
    Abstract [en]

    This paper proposes a method to investigate the socioeconomical aspects of transformer overloading during a cold load pickup (CLPU) in residential areas. The method uses customer damage functions to estimate the cost for their power interruption and a deterioration model to estimate the cost for transformer wear due to the CLPU. A thermodynamic model is implemented to estimate the peak and the duration of cold residential load. A stochastic differential equation is used to capture the volatility of the load and to estimate the probability for transformer overloading. In a numerical example, an optimal cold load pickup for a two-area system is demonstrated where transformer overloading is allowed. In this example, an ambient temperature threshold is identified, where transformer overloading is socioeconomically beneficial.

  • 22. Gebro, P.
    et al.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Hansson, O.
    National scale impact of the stockholm royal seaport project2013In: IET Conference Publications, 2013, no 615 CPConference paper (Refereed)
    Abstract [en]

    This paper investigates how results from limited pilot studies concerning Smart Grids can be extrapolated to a Swedish national scale. The paper investigates the challenges with a national scale implementation of a proposed price model for electricity that combines the cost of energy with the cost of distribution that aims to encourage end-consumer Demand Response (DR). The estimated change in the national scale load-curve that may be achieved given high customer DR participation is analysed as well. Numerous challenges of a national scale implementation are identified, mainly regarding the suggested price model's economic incentive and the Swedish apartment configuration of white goods that differs from that of the pilot studies. The estimated change in the national scale load-curve may also pose problems since the endconsumer behaviour that is desirable from a distribution grid point of view may differ from that of an optimal production capacity point of view.

  • 23.
    Grahn, Pia
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    PHEV Utilization Model Considering Type-of-Trip and Recharging Flexibility2014In: IEEE Transactions on Smart Grid, ISSN 1949-3053, E-ISSN 1949-3061, Vol. 5, no 1, p. 139-148Article in journal (Refereed)
    Abstract [en]

    Electric vehicles (EVs) may soon enter the vehicle market in large numbers and change the overall fuel usage within the passenger transport sector. With increased variable consumption from EVs together with anticipated increased production from variable sources, due to renewable wind and solar power, also the balancing of the electric power system incur increased attention. This emphasizes the importance of developing models to estimate and investigate the stochasticity of personal car travel behavior and induced EV charging load. Several studies have been made in order to model the stochasticity of passenger car travel behavior but none have captured the charging behavior dependence of the type-of-trip conducted. This paper proposes a new model for plug-in-hybrid electric vehicle (PHEV) utilization and recharging price sensitivity, to determine charging load profiles based on driving patterns due to the type-of-trip and corresponding charging need. This approach makes it possible to relate the type-of-trip with the consumption level, the parking location, and the charging opportunity. The proposed model is applied in a case study using Swedish car travel data. The results show the charging load impact and variation due to the stochastic PHEV type-of-trip mobility, allowing quantification of the PHEV charging impact on the system.

  • 24.
    Grahn, Pia
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Plug-in-vehicle mobility and charging flexibility Markov model based on driving behavior2012In: 9th International Conference on the European Energy Market, EEM 12, IEEE , 2012Conference paper (Refereed)
    Abstract [en]

    Climate targets around the globe are enforcing new strategies for reducing climate impacts, which encourage automobile and electricity companies to consider an electrified vehicle market. Furthermore, the variable electricity production in the electric power system is increasing, with higher levels of wind and solar power. Due to the increased variability in the system, the need to meet fluctuations with flexible consumption is intensified. Electric vehicles with rechargeable batteries seem to become an increasingly common feature in the car fleet. Plugin vehicles (PIVs), may therefore become valuable as flexible consumers. If so, flexible PIV owners could, if they are flexible enough, increase the value of owning an electric vehicle. This paper introduces a new PIV Mobility and Charging Flexibility Markov Model, based on driving behavior for private cars. By using the new model, it is possible to simulate the potential flexibility in a future system with many PIVs. The results from a case study indicate a potential need for usage of the batteries as flexible loads to reduce the grid power fluctuations and load peaks.

  • 25.
    Grahn, Pia
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Static and Dynamic Electric Vehicle Charging Impact on Load Profile with Electrified RoadsManuscript (preprint) (Other academic)
  • 26.
    Grahn, Pia
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Munkhammar, Joakim
    Widén, Joakim
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    PHEV Home-Charging Model Based on Residential Activity Patterns2013In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 28, no 3, p. 2507-2515Article in journal (Refereed)
    Abstract [en]

    Plug-in hybrid electric vehicles (PHEVs) have received an increased interest lately since they provide an opportunity to reduce greenhouse gas emissions. Based on the PHEV introduction level in the car park, the charging behaviors in an area will induce changes in the load profiles of the power system. Hence, it becomes important to investigate what impact a given PHEV introduction level has on load profiles due to expected charging behavior of residents.

  • 27.
    Grahn, Pia
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Rosenlind, Johanna
    KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.
    Hilber, Patrik
    KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    A method for evaluating the impact of electric vehicle charging on transformer hotspot temperature2011In: 2011 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe), 2011Conference paper (Refereed)
    Abstract [en]

    The expected increasing market share of electric vehicles is a response to the combination of new technological developments, governmental financial control, and an attitude shift of residents to a more environmentally friendly lifestyle. The expected capacity required for charging, imposes changes in the load to the already existing components in the electric power grid. In order to continue managing these existing assets efficiently during this load change, it is important to evaluate the impact imposed by the battery charging.

  • 28.
    Huang, Yalin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Distribution network expansion planning considering distributed generation using probabilistic constraints2014Conference paper (Other (popular science, discussion, etc.))
    Abstract [en]

    A novel optimization model for network expansionplanning, including distributed generation is proposed. Themodel considers the stochastic natures of distributed generationand load in the power systems. More importantly, this modeladdresses the probabilistic voltage constraints in the networkexpansion planning stage. The proposed model is employed toobtain the decisions for new wind power plant connections andreinforcements in the existing distribution network.

  • 29.
    Huang, Yalin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Regulation impact on distribution systems with distributed generation2012In: 9th International Conference on the European Energy Market, EEM 12, IEEE conference proceedings, 2012, p. 6254721-Conference paper (Refereed)
    Abstract [en]

    Distribution system operators (DSOs) are facing new challenges when more distributed generation (DG) is connected to the network. In this new operating environment the DSO has to be able to plan an efficient network topology, which consists of reinforcement and extensions. In addition, the DSO has to finance the investment from tariffs. The methods to solve network planning problems are reviewed in this paper. The studied network planning problem is the case when the DSO has no influence on the location of DG due to the unbundling between DSOs and production. Furthermore, the regulation for how the DSOs are allowed to design the tariffs in systems with DG vary between countries, a comparison of how the DSOs design their tariffs under different regulations is presented. This paper ends with a case study on methods that Swedish DSOs use to plan the networks when considering the uncertainties caused by wind power and the regulation impact on distribution network planning and network tariffs in Sweden.

  • 30.
    Huang, Yalin
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Hagström, E.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Martínez, Alberto Fernández
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    He, Y.
    Short-term network planning of distribution system with photovoltaic2013In: 22nd International Conference and Exhibition on Electricity Distribution, CIRED 2013, 2013, no 615 CP, p. 0989-Conference paper (Refereed)
    Abstract [en]

    The number of connections of photovoltaic (PV) to distribution network is increasing. Very few PV connection guidelines that distribution system operators (DSOs) can refer to have been found. This paper deals with network planning guidelines for distribution networks with PV. The paper aims to identify planning rules that are relatively easy to implement.

  • 31.
    Ibrahim, Hany
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Skillbäck, Mikael
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Hansson, O.
    Evaluation methods for market models used in smart grids2013In: 22nd International Conference and Exhibition on Electricity Distribution, CIRED 2013, 2013, no 615 CP, p. 0937-Conference paper (Refereed)
    Abstract [en]

    This paper investigates how demand response pilot projects for the residential sector can be evaluated. A simplified framework for how demand response pilot projects carried out for the residential sector can be designed has been developed. A review of 135 international pilot projects has been made. Interesting findings were that bill savings is the most common reason for participating and that customers tend to respond to blocks of prices instead of sudden increases in a certain hour. Also, customers tend to reduce their use of electricity when peak to off-peak price ratio is above three. Another finding concerning evaluation methods for DR smart grid projects is that a control group should be used to ensure the validity of a pilot project. The control group should be monitored simultaneously as the treatment group. This can facilitate determination of the true cause and effect relationship between variables and indicators.

  • 32.
    Jakobsson Ueda, Mari
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems. Svenska Kraftnät, Sweden .
    Engblom, Oskar
    Fortum Distribution AB, Sweden.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Representative test systems for Swedish distribution networks2009In: Proceedings of CIRED2009, 2009, p. 837-837Conference paper (Refereed)
    Abstract [en]

    This paper describes two electrical distribution systems, Swedish Urban Reliability Test System (SURTS) and Swedish Rural Reliability Test System (SRRTS), which are representative of actual Swedish distribution networks. These test systems aim to serve as a basis for reliability and cost analyses of Swedish distribution networks and for studies of regulation policies. The project was conducted within a research programme of Elforsk, a Swedish industry research association. The challenge has been to make the test systems representative in terms of load, component and customer data as well as network topology. To ensure the similarity of the test systems to actual networks, industry representatives of major Swedish power distribution companies have been an integral part of the development process. This paper shows the result of a validation of the test systems against data compiled by the Swedish Energy Markets Inspectorate. The validation was performed for the reliability indices SAIDI and SAIFI. It was confirmed that the developed test systems are good representatives of actual distribution networks, and thus suitable for further research of distribution networks and for studies of regulation policies.

  • 33.
    Picciariello, Angela
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Impact of Network Regulation on the Incentive for DG Integration for the DSO: Opportunities for a Transition Toward a Smart Grid2015In: IEEE Transactions on Smart Grid, ISSN 1949-3053, E-ISSN 1949-3061, Vol. 6, no 4, p. 1730-1739Article in journal (Refereed)
    Abstract [en]

    The integration of distributed generation (DG) in distribution grids is one of the pillars of smart grid deployment. However, an increasing amount of DG connected to distribution grids is likely to affect the operation of the grids themselves, e.g., changing the magnitude, and in some cases the direction, of power flows. In order to perform the transition to a smart grid, it is therefore essential to have the distribution system operators (DSOs) involved in the process. However, being that the DSOs' business is controlled by regulators, regulation has a fundamental impact on the speed and the actual performance of DSOs' involvement in the transition toward a smart grid. Therefore, a method is needed to assess network regulation impact on DSOs' incentive to integrate DG into their grids. This paper proposes a new method for the calculation of such incentive, and the method has been applied on a case study to the Portuguese, Danish, and Swedish regulations for different scenarios of DG penetration. The focus is on DSOs' operational costs and revenues. The analyses indicate that DG has a different impact on DSOs business, depending on the different regulations, the most relevant aspects being the structure of customer tariffs and the regulatory treatment of network losses.

  • 34.
    Picciariello, Angela
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Incentive from network regulation for distribution system operators to integrate distributed generation: The Portuguese case2013In: European Energy Market (EEM), 2013 10th International Conference on the, IEEE , 2013, p. 6607376-Conference paper (Refereed)
    Abstract [en]

    Increasing amount of distributed generation (DG) connected to distribution grids is likely to affect the operation of the grids themselves, for example by changing the magnitude and, in some cases also the directions, of the power flows in the networks. This can have different economic consequences on the Distribution System Operators (DSOs) depending on the different enforced network regulations. This paper proposes a method for how to calculate the incentive for DSOs to integrate DG into their grids. The calculation of this incentive is carried out for the Portuguese case. Only the operational aspects are considered to calculate costs and benefits for the DSO, including network tariffs, ancillary services costs, Operation and Maintenance (O&M) costs, and economic treatment of losses. The IEEE 34 Node Test Feeder is used to perform power flow analyses under different scenarios of DG penetration. The analysis shows that the Portuguese DSO would have an incentive to integrate a low level of DG penetration; in case of a higher level of DG penetration, however, this incentive would turn into a small disadvantage for the DSO. In both cases, the regulatory treatment of network losses turns out to be the relevant factor to determine such a result.

  • 35.
    Picciariello, Angela
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    State-of-art review on regulation for distributed generation integration in distribution systems2012Conference paper (Refereed)
    Abstract [en]

    Integration of distributed generation (DG) into distribution networks may affect many different factors, such as network reliability, voltage quality and network planning. Network regulation, therefore, is needed to provide the distribution system operators (DSOs) with fair business, meanwhile protecting the consumers and producers from any potential exploitation by the DSOs because of their monopoly situation. EU Member States have implemented different regulations, but there is no consensus yet as to what is the most appropriate mechanism for a successful and efficient integration of DG in distribution grids. This paper reviews the state-of-art of the regulatory frameworks for the integration of DG in some EU countries, and methods to model the regulation impact on DG integration in distribution systems. For each regulatory scheme, the main critical issues concerning DG integration are identified.

  • 36.
    Simab, Mohsen
    et al.
    Tarbiat Modares University, Tehran.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Söder, Lennart
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Haghifam, Mahmoud-Reza
    Tarbiat Modares University, Tehran.
    Designing reward and penalty scheme in performance-based regulation for electric distribution companies2012In: IET Generation, Transmission & Distribution, ISSN 1751-8687, E-ISSN 1751-8695, Vol. 6, no 9, p. 893-901Article in journal (Refereed)
    Abstract [en]

    A reward and penalty scheme (RPS) in performance-based regulation (PBR) penalises companies for providing poor reliability and rewards them for providing good reliability. In this study, an algorithm is presented to obtain the parameters of RPS for each electric company by using data envelopment analysis (DEA) and fuzzy c-means clustering (FCM). This algorithm is based on system average interruption duration index (SAIDI) and customers' value of interruptions. FCM algorithm is applied to find similar distribution companies and cluster companies into different clusters. The best performer in each cluster is utilised as a benchmark for other companies and DEA is used to set a quality target for each electric distribution company. The performance of the proposed algorithm is demonstrated in a case study to design RPS for Iranian electricity distribution companies. The results of the algorithm include DEA efficiency score, parameters of RPS and financial risk assessment.

  • 37.
    Song, Meng
    et al.
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Alvehag, Karin
    KTH, School of Electrical Engineering (EES), Electric Power Systems.
    Widén, Joakim
    Parisio, Alessandra
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Estimating the impacts of demand response by simulating household behaviours under price and CO2 signals2014In: Electric power systems research, ISSN 0378-7796, E-ISSN 1873-2046, Vol. 111, p. 103-114Article in journal (Refereed)
    Abstract [en]

    To facilitate the implementation of demand response (DR), it is necessary to establish proper methods to estimate and verify the load impacts of it. This paper develops a simulation model to investigate the joint influence of price and CO2 signals in a DR program in the ex ante evaluation. It consists of a Markov-chain load model for forecasting the power demands of residential consumers and a scheduling program for providing optimal schedules for smart appliances. A case study of the Stockholm Royal Seaport project is analysed to demonstrate how to apply the simulation model to assess a DR program by simulating consumers' behaviour change in response to the DR signals. The results show that consumers' attitude to the signals and willingness to change (expressed by weight), and time preference) largely affect the load shift, bill saving and emission reduction. Moreover, by observing the load shifts over different lengths of the testing period, the model could also provide suggestions on the required testing period to get sufficient load data to distinguish the load patterns between consumers in different testing groups.

1 - 37 of 37
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf