Karin Alvehag

A Reliability Model for Distribution Systems Incorporating Seasonal Variations in Severe Weather

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.

PHEV Utilization Model Considering Type-of-Trip and Recharging Flexibility

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.

Impact of Reward and Penalty Scheme on the Incentives for Distribution System Reliability

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 DSOs 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 DSOs financial risk and incentive to invest.

A method for evaluating the impact of electric vehicle charging on transformer hotspot temperature

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.

Plug-in-vehicle mobility and charging flexibility Markov model based on driving behavior

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.

An Activity-based Interruption Cost Model for Households to be Used in Cost-Benefit Analysis

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.

Financial risk assessment for distribution system operators regulated by quality regulation

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.

Distribution network expansion planning considering distributed generation using probabilistic voltage constraints

A novel optimization model for network expansion planning, including distributed generation is proposed. The model considers the stochastic natures of distributed generation and load in the power systems. More importantly, this model addresses the probabilistic voltage constraints in the network expansion planning stage. The proposed model is employed to obtain the decisions for new wind power plant connections and reinforcements in the existing distribution network.

Influence of Ambient Temperature on Transformer Overloading During Cold Load Pickup

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.

State-of-art review on regulation for distributed generation integration in distribution systems

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.