IEEE Power & Energy Magazine - July/August 2018 - 72

this means that a peak demand increase will have stronger
impacts on local lV grids than high-voltage transmission
lines and wholesale markets. note that on the day when the
systemwide peak heat demand occurs, demand diversity will
be less pronounced than on a typical day because end users
will tend to use heat for longer times and more simultaneously [figure 4(b)].

Data Time Resolution
along with the aggregation level, the time resolution also
impacts the peak load level observed. at higher resolution
load data, the observed peak demand tends to be flatter as
the peak is smoothened over a wider time interval. the optimal temporal granularity of heat data to capture peak demand
also depends on the level of aggregation. However, high-granularity heat data is often not available because many countries lack experience with electric heating. High-resolution
bottom-up models (figure 5) are able to represent the heat
demand while also capturing the probabilistic nature of customer behavior (such as occupancy patterns) and building
characteristics. supported by statistical inputs such as timeof-use surveys, heat demand has been modeled to study the
impact of heat electrification on electricity systems. Depending on the grid-level analyzed and the requirement to capture
diversified peak load, different time resolutions may be necessary, but for most cases 5-10-min resolution data can capture
diversified demand and limit computational cost. High-quality demand data and models are essential building blocks to
properly assess the impact and flexibility of high heat electrification on different levels of the electricity system.

Heat Technologies
the heating system characteristics and level of integration
determine the flexibility of residential heating systems.

Heater
electric heating systems are mostly based on heat pumps
(Hps) and resistance-based heaters. Hps are increasingly

promoted in low-carbon strategies due to their high efficiencies. they make use of the natural temperature difference
between a source (such as underground or ambient air) and
indoor in a condensation/evaporation cycle, which is why
it is often classified as renewable heat. the heat cycle only
requires electricity to run the compressor and other auxiliary equipment, therefore producing two to five units of heat
for air-source Hps (asHps) [and potentially more for ground
source Hps (gsHps)] for each unit of electricity consumed.
the higher efficiency of Hps compared to resistance heaters
(which create one unit of heat for each unit of electricity consumed) results in lower electric loads, which minimizes generation requirements and peak load. It is important to note
that the Hp coefficient of performance (Cop) is dependent
on the temperature difference between source and sink. this
has two implications for electricity demand: 1) the Cop of
asHps is lower during cold temperature spells when heat
is most needed and 2) the Cop is higher if the heat delivery
temperature indoors is low, favoring the use of air-based distribution systems over hydronic systems. In europe, however
most houses use hydronic (water-based) distribution systems
because they are more compact. In modern low-temp heaters or underfloor heaters, delivery temperature can be as
low as 35 °C.
Direct electrical heating solutions include radiators, fan
heaters, panel heaters, and electric storage heaters (discussed
in the next section). the main advantage of these heating
technologies is a low investment cost. However, while the
heaters are highly efficient at point of use (almost 100%
of the electricity is converted to heat), when you consider the
losses incurred in the electricity generation and transmission,
these heaters do not compare favorably in terms of primary
energy use and typical operating costs to, for example, an efficient gas boiler. operating costs tend to be high compared to
other local heating solutions. another disadvantage of direct
electrical heating is that the electrical power demand is closely
coupled with the heating demand, with very limited flexibility
in power scheduling.

Thermal Storage
10
9
8
7
6
5
4
3
2
1
0

2,500

Load (kW)

2,000
1,500
1,000
500

(a)

0
18
0
36
0
54
0
72
0
90
1, 0
08
1, 0
26
1, 0
44
0

0
(b)

figure 5. (a) Individual and (b) aggregated electricity profiles for 1,000 customers
with electric heating and domestic hot water, over 24 h, with 1-min resolution.
72

ieee power & energy magazine

thermal storage in the building enables the optimization of the electricity consumption and charging
based on electricity market conditions while still providing thermal
comfort to the user. temporal decoupling of electrical power demand
from the heating demand can be
achieved when electrical heating
with a sufficient storage capacity
is deployed.
electrical space heaters with
internal storage have been widely
used for decades in many regions
with temperate climates, including
july/august 2018

Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - July/August 2018