Arne T. Holen

Operation and sizing of energy storage for wind power plants in a market system

This paper presents a method for the scheduling and operation of energy storage for wind power plants in electricity markets. A dynamic programming algorithm is employed to determine the optimal energy exchange with the market for a specified scheduling period, taking into account transmission constraints. During operation, the energy storage is used to smooth variations in wind power production in order to follow the scheduling plan. The method is suitable for any type of energy storage and is also useful for other intermittent energy resources than wind. An application of the method to a case study is also presented, where the impact of energy storage sizing and wind forecasting accuracy on system operation and economics are emphasized. Simulation results show that energy storage makes it possible for owners of wind power plants to take advantage of variations in the spot price, by thus increasing the value of wind power in electricity markets. With present price estimates, energy storage devices such as reversible fuel cells are likely to be a more expensive alternative than grid expansions for the siting of wind farms in weak networks. However, for areas where grid expansions lead to unwanted interference with the local environment, energy storage should be considered as a reasonable way to increase the penetration of wind power.

MULTISTATE RELIABILITY THEORY-A CASE STUDY

Fortunately traditional reliability theory, where the system and the components are always described simply as functioning or failed, is on the way to being replaced by a theory for multistate systems of multistate components. However, there is a need for several convincing case studies demonstrating the practicability of the generalizations introduced. In this paper an electrical power generation system for two nearby oilrigs will be discussed. The amounts of power that may possibly be supplied to the two oilrigs are considered as system states.

A voltage instability predictor using local area measurements (VIP

A smart relay scheme for long term voltage instability phenomena is proposed. The method, called VIP++ is based on local area measurements and seeks to improve observability and robustness of a previously proposed voltage instability predictor (VIP) using measurements only from the bus where the relay is placed. Several strategies can be adopted to deal with the extra set of measurements from neighboring buses, and two such strategies have been explored in the paper. When the system is far from the point of collapse (PoC) the VIP++ gives an approximate distance to PoC and indicate that the distance is quite large. As the system trajectory moves closer to the actual point of collapse the method will become more accurate, and it will be more or less exact at PoC.

Optimal operation of hydrogen storage for energy sources with stochastic input

An operation strategy for hydrogen storage in combination with stochastic energy sources is presented. The hydrogen storage can simultaneously be used for power smoothing and provide clean fuel for vehicles. The method is based on optimization of an objective function that takes into account electricity market conditions and penalties for not providing hydrogen and oxygen to the loads. Three case studies where wind is the primary energy source have been analyzed. Simulation results show that the hydrogen storage makes it possible to reduce wind power fluctuations, and at the same time take advantage of hourly variations in the electricity price. In isolated operation mode, utilization of excess heat from the fuel cell leads to a significant reduction of the usage of back-up generator. The results indicate that it is valuable to use optimization techniques for operation of hydrogen storage in connection with stochastic energy sources.

Adequate interruption cost assessment in a quality based regulation regime

Balancing cost-effectiveness and quality of service is one of the most important tasks for network companies in the deregulated environment. It is widely recognized that interruption costs is a relevant expression for the inconvenience customers feel when service is interrupted and that adequate assessment of such costs is crucial when they are used quantitatively in cost-benefit analyses. In this paper we demonstrate by a distribution system example that typical time variations of component failure rate, repair time, load and specific interruption costs can have a significant impact on the estimated annual interruption cost for delivery points in the system. This observation is possible by a model that can handle such time variations including correlation between the parameters. An interesting application of this model is to quantify the consequence of for example moving planned maintenance to periods when the load and the interruption cost is low.

Reliability and interruption cost prediction using time-dependent failure rates and interruption costs

The main idea presented and discussed in this paper is a model reproducing a time-dependent component failure rate pattern similar to the observed pattern recorded in failure statistics. This pattern includes all types of failures, caused by the weather or by technical and human aspects. Failure causes and mechanisms are not modelled explicitly and the observed pattern is assumed to be representative for the analysis period ahead. Being able to predict and time-tag component failures, the time-dependent variables of load, repair time and customer-specific interruption costs can be adequately combined to calculate annual reliability indices and interruption costs. This fact also permits us to apply an analytical model which will produce expectation values comparable with average values in a Monte Carlo simulation.

Reliability modeling of gas and electric power distribution systems; similarities and differences

Due to the introduction of alternative energy carriers, such as district heating and natural gas, the Norwegian energy system is becoming more complex. Assessing the reliability of electrical distribution systems is a mature field of research, but limited work has been carried out concerning the reliability of distribution systems for alternative energy carriers. This paper proposes a methodology for assessing the reliability of natural gas distribution systems based on experiences drawn from similar analysis of electrical power distribution systems. A simple test case is presented for illustrative purposes and the basic load-point reliability indices of average interruption rate, average outage time and average annual outage time are found

Decision Analysis and Uncertainties in Planning Local Energy Systems

In this paper, we discuss how uncertainties can be represented in two of the most well-known multi-criteria decision analysis (MCDA) methods, the multi-attribute utility theory (MAUT) and the analytical hierarchy process (AHP). There are distinct differences in the treatment of uncertainties in the two methods. MAUT is specially developed for handling uncertainties. In contrast, the AHP method has, in its general form, no systematic approach to integrate uncertainty aspects. However, various procedures for applying AHP in situations involving uncertainties have been proposed in the literature. In a case study, we illustrate how the two methods can be used to assist in decision making under uncertainty in a local energy planning problem. We conclude that MAUT is clearly more suited for handling uncertainties than AHP. However, also many other criteria should be considered when choosing which MCDA method to apply for local energy planning purposes

Impact of Energy End Use and Customer Interruption Cost on Optimal Allocation of Switchgear in Constrained Distribution Networks

The introduction of new energy carriers, such as natural gas and district heating, to energy systems dominated by electrical power will certainly relieve stress on the power system. Some of the end uses initially served by the power system will be gradually decoupled and served by alternative energy carriers. As a result, the specific customer interruption costs and load profiles will change. In this paper, we analyze how the optimal level of switchgear in electric power distribution systems is affected by such changes. The proposed optimization method is based on a genetic algorithm and takes into account the constrained network capacity.