J Johan Morren

Sensing and control challenges for Smart Grids

Due to the adverse impacts of the consumption of fossil fuels on our environment, the quest for a more sustainable energy supply is increasingly intensifying worldwide. Many renewable energy sources, such as wind, solar and tidal power generate electricity. Therefore, the development towards a sustainable energy supply leads to increasing electrification. The decreasing degree of controllability of electricity production and the high, but rare production peaks caused by distributed generation require involving electricity consumption in balancing supply and demand. To this end, electricity networks must develop into “Smart Grids”. One of the consequences of this trend is a vastly increased need to acquire, process and communicate data, both for measurement and control purposes. In the contribution, first the background of the development towards Smart Grids will be studied in more detail. Then, the various functionalities and corresponding architectures and sensing and control requirements will be discussed for different Smart Grid concepts.

Multi-objective optimization techniques and applications in electric power systems

Efficient operation and planning of power systems is important for a reliable and sustainable electricity supply. Therefore, optimization techniques have been applied to several optimization problems in power systems in order to achieve technical and economic efficiency. This paper presents an overview of existing optimization techniques and applications in power systems, with a special focus on multi-objective optimization in power system planning. Power system planning is by its nature a very complex multi-objective optimization problem involving perspectives of different stakeholders. Besides, a single stakeholder can also have various objectives that need to be optimized at the same time. This paper provides a review of the state-of-the-art in multi-objective evolutionary algorithms applied to power systems planning problems.

Practice-oriented optimization of distribution network planning using metaheuristic algorithms

Distribution network operators require more advanced planning tools to deal with the challenges of future network planning. An appropriate planning and optimization tool can identify which option for network extension should be selected from available alternatives. However, many optimization approaches described in the literature are quite theoretical and do not yield results that are practically relevant and feasible. In this paper, a distribution network planning approach is proposed which meets requirements originating from network planning practice to guarantee realistic outcomes. This approach uses a state-of-the-art evolutionary algorithm: Gene-pool Optimal Mixing Evolutionary Algorithm. The performance of this algorithm, as well as the proposed model, is demonstrated using a real-world case study.

Smart integration of distribution automation applications

Future electricity demand will significantly increase, while flexibility in supply will decrease, due to an increase in the use of renewable energy sources. The most effective way to prepare distribution grids for this increase in loading and decrease in supply-flexibility is to apply balancing, load-shifting, peak-shaving and other smart-grid related technologies. Without the implementation of smart grid technologies in distribution networks, it is almost impossible to keep the power supply at the current reliability and quality levels. An important factor in the success of smart grids, is the implementation of distribution automation systems (DAS). The ability to reconfigure networks, divert power flows, isolate faults and prevent overloading of network components all contributes to the optimal operation of self-healing distribution grids, which is necessary for future electricity demands. In this paper, a literature research on the status of distribution automation research is presented and an outlook towards future roles of distribution automation systems is explored. Emphasis is put on the integration of different applications in order to be able to grasp the full potential of DAS. Furthermore an elaborate case study is presented, considering the effects of DAS integration into the live distribution grid.

Investigation of simultaneity in distribution networks for the assessment of DA feasibility

Implementation of distribution automation into medium and low voltage grids is gaining more and more support amongst distribution grid operators. In order to assess the feasibility and usefulness of dynamic network reconfiguration for the purpose of reducing losses and increasing available network capacity, it is necessary to know to what extent simultaneity amongst MV/LV transformers within distribution networks occurs. Measurements have been done in parts of the distribution network of Enexis, one of the largest distribution network operators in the Netherlands. For a full year, in 30 MV/LV substations the transformer and all outgoing low voltage feeders have been measured. In this paper the measurement data is being analyzed in order to determine the degree of simultaneity in low voltage distribution grids, both seen from the low- and the medium-voltage level. The results of this analysis will be used to assess the feasibility of power flow optimization by using distribution automation. Furthermore, an example of a field application will be simulated and discussed.

Evaluating impact of new technologies on low voltage grids using probabilistic data enriched scenarios

In this paper a scenario-based method for long term load forecasting is proposed that incorporates the uncertainty and diversity in adoption of future developments in the evaluation and planning process of low voltage grids and that is able to account for local differences in expected loading. The approach incorporates the influence of local parameters in the scenarios using logistic regression based on data gathered from different sources. The method can be used to assess the resilience of low voltage grids under various different scenarios and assists grid planners in making informed investment decisions under uncertainty. It is designed such that it is open for addition of extra parameters and data to increase its robustness against a changing environment.

Incorporating the smart grid concept in network planning practices

Ongoing developments in the electricity system are changing the requirements for planning and design of distribution networks. Based on field research at several Dutch distribution network operators a conceptual planning process is defined and current practices in distribution network planning in the Netherlands are investigated. Currently mainly traditional deterministic approaches are applied, but the increased focus on efficiency and optimal utilisation of existing grids leads to the exploration of more detailed methods. So far, the uncertainties in costs and benefits and the absence of clear legislation hinder the incorporation of smart grid technologies in routine network planning.

Investigation of grid loss reduction under closed-ring operation of MV distribution grids

This paper describes an alternative scenario for operation of medium voltage (MV) cable distribution grids. Grid losses are one of the largest expenses for distribution system operators (DSOs). In order to achieve a reduction of these losses a closed-ring operation strategy is proposed. By meanwhile introducing distribution automation into the grid, a high reliability can still be guaranteed. The paper starts with a brief description of the technical background of the proposed system. Secondly, an analysis is given of the grid loss reduction and reliability increment that can be achieved. This analysis is based on simulations done with real-life grid topologies, using measurement data and a future load demand prognosis.

Investigation of failures of low voltage grid components

Distribution System Operators (DSOs) in the Netherlands are generally more focused on Medium Voltage (MV) grids than on Low Voltage (LV) grids as higher voltage levels contribute more to the SAIDI. However increasing interruption times, increasing costs and the energy transition on LV level encourage the DSOs to focus on LV grids as well. A first step is the investigation of failures in LV grid components. In this paper a literature review on this topic is presented and the outcomes are discussed. It is concluded that the method of modelling of ageing components on MV level cannot be applied to LV level because of the absence of temperature-related and electric stresses in LV components. In addition the possibilities for diagnostics are limited due to attenuation of electric signals. Although statistical methods are currently used for condition assessment of distribution grids, the LV level remains partly unspoilt terrain. However there remain some challenges related to data availability and quality. The use of statistical methods is investigated in further research in order to be able to perform condition assessment on LV level.

Distribution automation at Enexis: a case study

This chapter will describe in detail the DA concept developed by Enexis, and will explain which steps have been taken. The main lessons learned will be presented. Afterwards the preparation of the large-scale roll-out and the impact of DA on the organisation of the DSO will be described. Finally the findings after automation of more than 1000 substations will be given.