Wouter Labeeuw

Residential Electrical Load Model Based on Mixture Model Clustering and Markov Models

Detailed large-scale simulations require a lot of data. Residential electrical load profiles are well protected by privacy laws. Representative residential electrical load generators get around the privacy problem and allow for Monte Carlo simulations. A top-down model of the residential electrical load, based on a dataset of over 1300 load profiles, is presented in this paper. The load profiles are clustered by a Mixed Model to group similar ones. Within the group, a behavior model is constructed with a Markov model. The states of the Markov models are based on the probability distribution of the electrical power. A second Markov model is created to randomize the behavior. A load profile is created by first performing a random-walking of the Markov models to get a sequence of states. The inverse of the probability distribution of the electrical power is used to translate the resulting states into electrical power.

Potential of Active Demand Reduction with Residential Wet Appliances: A Case Study for Belgium

Two problems are tackled in this paper: determining the active demand reduction potential of wet appliances and making time series estimates from project data. The former is an application of the latter. Household groups representative to the average population are defined by applying expectation maximization clustering to a representative measurement set (n = 1363). Attitudes toward active demand are found by conducting a survey (n = 418). Project data (n = 58) containing wet appliance measurements are scaled up by adapting the clustering algorithm, spreading the electricity demand of the wet appliances over the clusters. The potential for active demand reduction with wet appliances is 4% of the total residential power demand, assuming that 29% of the households take part. The potential is in the order of magnitude of the power reserves, but does not fulfill availability and response time requirements.

Communication overlays and agents for dependable smart power grids

Smart grids rely on a dependable information infrastructure for the monitoring and control applications. Two elements can enhance the suitability of the communication and control infrastructure for such smart grid applications. Overlay networks allow to resiliently deal with nodes that appear and disappear, as well as with the dynamic nature of the power values these nodes represent in a smart grid. Agents-based modelling allows to simulate the smart grid applications in a scalable and flexible way before deployment. The paper discusses how both approaches can be combined for simulating a more dependable smart grid.

Framework for Evaluating and Comparing Performance of Power System Reliability Criteria

Evolutions in the power system challenge the manner in which power system reliability is managed. In particular, currently used reliability criteria, typically the deterministic N-1 criterion, are increasingly inadequate. Moving to an alternative approach is difficult as quantifying benefits is hard in a multifaceted environment and system operators are reluctant to move away from the easy and transparent existing criterion. This paper presents a generic framework to evaluate and compare socio-economic and reliability performance of power system reliability criteria, focussing on the short term decision making process of transmission system operators (TSO). The framework can also be used to tune the parameters of reliability criteria. Short term operational planning and real time operation TSO decision making processes are simulated considering various reliability criteria. The framework is applied to a 5 node test system and the 24 node IEEE reliability test system, showing that the applied probabilistic reliability criterion outperforms deterministic N-0 and N-1 approaches in those systems in terms of expected reliability and socio-economic indicator values. The effect is larger in the bigger system with more operational flexibility.

Infrastructure for collaborating data-researchers in a Smart Grid pilot

A large amount of stakeholders are often involved in Smart Grid projects. Each partner has its own way of storing, representing and accessing its data. An integrated data storage and a joint online analytical mining infrastructure is needed to limit the amount of duplicated work and to raise the overall security of the system. The proposed infrastructure is composed of standard application software and an in-house developed data analysis tool that allows researchers to add and share their own functionality without compromising security.

Dealing with an overdose of photovoltaics at distribution level

Injection of large amounts of active power in the highly resistive distribution network by photovoltaic installations causes the voltage to rise along the feeder. This voltage rise is one of the major challenges the distribution network operator has to face. Rising voltage causes generators to trip with a loss of green energy at the most productive moments as a consequence. A technique known as Active Power Curtailment (APC), proposed by Tonkoski et al., is implemented on a part of a typical European distribution grid. The resulting energy yields are compared to the situation in which the inverter switches off. APC results in a serious decrease of production. Therefore, a modified version of APC, called APC-PI is proposed. By transforming APC from a proportional feedback controller to a PI controller, the total energy yield can be increased by as much as 40% in comparison to the production of APC controlled generators.