Edwin Haesen

The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid

Alternative vehicles, such as plug-in hybrid electric vehicles, are becoming more popular. The batteries of these plug-in hybrid electric vehicles are to be charged at home from a standard outlet or on a corporate car park. These extra electrical loads have an impact on the distribution grid which is analyzed in terms of power losses and voltage deviations. Without coordination of the charging, the vehicles are charged instantaneously when they are plugged in or after a fixed start delay. This uncoordinated power consumption on a local scale can lead to grid problems. Therefore, coordinated charging is proposed to minimize the power losses and to maximize the main grid load factor. The optimal charging profile of the plug-in hybrid electric vehicles is computed by minimizing the power losses. As the exact forecasting of household loads is not possible, stochastic programming is introduced. Two main techniques are analyzed: quadratic and dynamic programming.

Coordinated charging of multiple plug-in hybrid electric vehicles in residential distribution grids

Alternative vehicles based on internal combustion engines (ICE), such as the hybrid electric vehicle (HEV), the plug-in hybrid electric vehicle (PHEV) and the fuel-cell electric vehicle (FCEV), are becoming increasingly popular. HEVs are currently commercially available and PHEVs will be the next phase in the evolution of hybrid and electric vehicles. The batteries of the PHEVs are designed to be charged at home, from a standard outlet in the garage, or on a corporate car park. The electrical consumption for charging PHEVs may take up to 5% of the total electrical consumption in Belgium by 2030. These extra electrical loads have an impact on the distribution grid which is analyzed in terms of power losses and voltage deviations. Firstly, the uncoordinated charging is described where the vehicles are charged immediately when they are plugged in or after a fixed start delay. This uncoordinated power consumption on a local scale can lead to grid problems. Therefore coordinated charging is proposed to minimize the power losses and to maximize the main grid load factor. The optimal charge profile of the PHEVs is computed by minimizing the power losses. The exact forecasting of household loads is not possible, so stochastic programming is introduced.

A Probabilistic Formulation of Load Margins in Power Systems With Stochastic Generation

This paper discusses the impact of uncertain power injections in the grid on the load margin. Two common analyses of voltage stability are those aiming for the closest saddle node bifurcation and those assuming a prefixed direction of load and production increase. In the case of large renewable based generation units or a significant degree of dispersed generation, the loading margin has to be interpreted as a stochastic variable itself. This allows to interpret load margins at different levels of probability of voltage collapse with or without corrective actions undertaken. The probabilistic margin is assessed with a minimum number of samples by use of a stochastic response surface method implementation. The method is illustrated on the IEEE 24-bus and 118-bus system considering stochastic wind generation and dispersed generation.

Integration of energy storage in distribution grids

Electrical energy storage services can bring benefit to multiple stakeholders in the distribution grid. Energy storage owners maximize their profit on an external energy market. This can cause a conflict with the distribution system operator because a grid is designed in terms of peak power, not energy. The subject of this paper is a optimization method for the siting and sizing of energy storage in distribution grids. The optimization is implemented multi-objective as to visualize the trade-offs between storage stakeholders and distribution system operators.

Zonal network model of European interconnected electricity network

In this paper the authors discuss the feasibility of a zonal UCTE network model for congestion management. Zonal network model aggregates all nodes within a control zone and substitutes it by one equivalent node; individual cross-border lines are substituted by equivalent one link per border. This model allows derivation of power transfer distribution factors PTDF matrix that could model the interaction between zonal power injections and cross-border flows, and therefore allow for the implementation of flow-based congestion management models

A Long-Term Multi-objective Planning Tool for Distributed Energy Resources

Present changes in the operation of distribution grids call for a new way in which grid modifications are planned. This paper gives an overview of the changes on production and demand side as well as possible ways of planning the integration of distributed energy resources. Multiple objectives are often conflicting. An evolutionary algorithm is used to search for fit topologies of distributed resources and analyze the possible trade-offs

Opportunities for active DER management in deferral of distribution system reinforcements

Power systems worldwide have gone through a transition from vertically integrated into liberalized energy markets. At the same time, increased environmental concerns are promoting the use of renewable and efficient generation technologies. Consequently, a growing number of small-scale Distributed Energy Resources (DER) are being installed in distribution systems. Passive operation of DER can result in severe grid operation problems. In contrast, active DER management can bring mutual benefits for the DER owner as well as Distribution System Operators (DSO). In this article a flexible multi-objective optimization scheme is presented in which DER placement and optimal ancillary services are evaluated and compared with conventional grid reinforcements. This allows assessing the potential of optimal active DER management and evaluating different tariff schemes for DER connection at different levels of DER in the grid. The proposed method uses a hybrid Strength Pareto Evolutionary Algorithm (SPEA2) with a distribution Optimal Power Flow (OPF). Results are analyzed using the UKGDS 355-bus system.

Hosting capacity for motor starting in weak grids

In this article the effect of motor starting on the voltages and currents in weak grids is analyzed. The objective is to find the size of the largest motor that can be started from the grid in an acceptable way, called the hosting capacity for motor starting. An overview of the different types of weak grids is given. Important are the measures that can be taken to improve the grid operation and increase the hosting capacity

Stochastic, Computational and Convergence Aspects of Distribution Power Flow Algorithms

This paper discusses uncertainties in distribution system analysis. Special emphasis lies with distributed generation (DG) units. Both backward-forward sweeps and Newton-Raphson based current injection updates are discussed. A first class of stochastic modeling is of probabilistic nature. In analytic probabilistic methods a linearization of the power flow equations is applied. Non-linearities are respected in numerical Monte Carlo analysis when using the appropriate convergence criteria. The second class uses qualitative uncertainty descriptions in boundary and fuzzy power flow methods. Correlation of loads and DG is always a crucial aspect. These aspects are elaborated with regard to robust methodologies for setting benchmarks of DG performance based on stochastic programming and evolutionary algorithms.

Reliability analysis of a torque estimation model

In this paper a torque estimation model for induction machines is studied. The model requires several machine parameters as input. Since the input parameters are deduced from measurements burdened with inaccuracy, it is necessary to take into account uncertainty in the input of the model. A first order and second order reliability method are performed to evaluate the probability of failure of the system under the uncertain inputs. The system failure is defined through the limit state function and occurs when the calculated value of the torque differs significantly from the rated torque at rated conditions. Monte Carlo simulations are performed for validation and importance sampling is discussed to reduce the Monte Carlo simulation error. The probability of failure is also derived from the torque probability density function by means of a stochastic response surface method. The analysis includes current and speed measurement uncertainties as well.