Analyzing the impact of home energy systems on the electrical grid

Schlösser, Tim; Stinner, Sebastian; Monti, Antonello; Müller, Dirk

doi:10.1109/pscc.2014.7038378

Cited by 5 publications

(5 citation statements)

References 9 publications

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“…Few impact studies have been carried out pertaining to heat pumps. In [23] the impact of heat pumps, PV and combined heat and power units (CHP) on a German grid was studied, using a rudimentary building model and assuming balanced grid. Akmal et al [24] looked into the effect of heat pump start-up on transient voltages and Bottrell et al [25] investigated the impact on harmonic power quality.…”

Section: Introductionmentioning

confidence: 99%

Heat pump and PV impact on residential low-voltage distribution grids as a function of building and district properties

2017

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Heating electrification powered by distributed renewable energy generation is considered among potential solutions towards mitigation of greenhouse gas emissions. Roadmaps propose a wide deployment of heat pumps and photovoltaics in the residential sector. Since current distribution grids are not designed to accommodate these loads, potential benefits of such policies might be compromised. However, in large-scale analyses, often grid constraints are neglected. On the other hand, grid impact of heat pumps and photovoltaics has been investigated without considering the influence of building characteristics. This paper aims to assess and quantify in a probabilistic way the impact of these technologies on the low-voltage distribution grid, as a function of building and district properties. The Monte Carlo approach is used to simulate an assortment of Belgian residential feeders, with varying size, cable type, heat pump and PV penetration rates, and buildings of different geometry and insulation quality. Modelica-based models simulate the dynamic behavior of both buildings and heating systems, as well as three-phase unbalanced loading of the network. Additionally, stochastic occupant behavior is taken into account. Analysis of neighborhood load profiles puts into perspective the importance of demand diversity in terms of building characteristics and load simultaneity, highlighting the crucial role of back-up electrical loads. It is shown that air-source heat pumps have a greater impact on the studied feeders than PV, in terms of loading and voltage magnitude. Furthermore, rural feeders are more prone to overloading and under-voltage problems than urban ones. For large rural feeders, cable overloading can be expected already from 30% heat pump penetration, depending on the cable, while voltage problems start usually at slightly higher percentages. Additionally, building characteristics show high correlations with the examined grid performance indicators, revealing promising potential for statistical modeling of the studied indicators. Further work will be directed to the assessment of meta-modeling techniques for this purpose. The presented models and methodology can easily incorporate other technologies or scenarios and could be used in support of policy making or network design.

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Section: Introductionmentioning

confidence: 99%

Heat pump and PV impact on residential low-voltage distribution grids as a function of building and district properties

2017

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“…Home energy systems (HESs), namely CHPs and HPs are installed in residential buildings to cover the heat demand for both space heating and warm water. The active and reactive power profiles of the HES are generated, with a time resolution of 15 minutes, following the approach of [17]. The input, needed to generate the profiles, includes the thermal parameters of the building, the storage temperature, the user behavior and the devices (radiators, HES, storage).…”

Section: Generation Of Realistic Power Profiles Of Thermo-electricmentioning

confidence: 99%

“…4 the color code represents the number of observations (over the 25000 cases), the x axis is active power value and the y axis is the time of the day. C. HESs probability distribution CHPs and HPs are modeled to have a nominal power of 5 kW and 8 kW respectively [17]. Some restrictions based on expected economic choices from the customers are that houses cannot have both CHPs and HPs, as that would mean a useless heating apparatus redundancy.…”

Section: B Pv Probability Distributionmentioning

confidence: 99%

Impact of Pseudo-Measurements From New Power Profiles on State Estimation in Low-Voltage Grids

Angioni

Schlösser

Ponci

et al. 2016

IEEE Trans. Instrum. Meas.

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LV State estimation in distribution power system, because of lack of real time measurements, must heavily rely on pseudo-measurements, primarily originating from standard load profiles. Actual load profiles have been recently suspected of deviating significantly from the standard load profiles, and research work is ongoing to quantify and characterize this deviation and to synthesize more realistic profiles. The analysis of the propagation of error and uncertainty of load profiles in state estimation must be investigated, as distribution system state estimation (DSSE) state estimation in distribution is being experimentally deployed, and the use of any available source of data is under consideration. The findings provide hints on the accuracy to be expected and on corrections to be applied to classical pseudo-measurements.

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“…In the past, the medium (MV) and low voltage (LV) grids dealt only with the supply of passive customers with electrical energy. The boundary conditions changed, but the distribution system operators (DSO) still have to guarantee a safe and reliable electrical energy supply for their customers at any time [15]. The concept of 2DSM, explained in the previous chapter, points out that shifting the operation of controllable devices in the heating sector can be used to compensate fluctuations in decentralized renewable generation.…”

Section: Flexibility Demand Of Electrical Distribution Gridsmentioning

confidence: 99%

“…A high penetration level of e.g. PV inside a LV grid can lead to a rising voltage profile along the feeder [15]. Additionally, in times of low electrical power demand and simultaneous high injection of renewable energy, the utilization of lines and cables can reach higher values than in a purely passive grid.…”

Section: Grid Key Performance Indicatorsmentioning

confidence: 99%