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Proceedings ArticleDOI

A Novel Approach to DG Curtailment in Rural Distribution Networks – A Case Study of the Avacon Grid as Part of the InterFlex Field Trial

18 Jul 2018-pp 667-672
TL;DR: A novel control algorithm for emergency curtailments that takes advantage of technological improvements and describes the architecture for a successful deployment at the example of Avacon’s network and SCADA is developed.
Abstract: Distribution system operators in rural areas of Germany are frequently facing imminent equipment overloading caused by the feed-in of local renewable Distributed Generation (DG). A grid operator’s last resort to maintain system stability and avoid protection tripping is to temporarily curtail local feed-in until hosting capacity in the network has caught up with the demand. Due to technological limitations in today’s networks the volume of curtailed energy can be greater than what would strictly be necessary. This paper presents a case study of a 110 kV overhead line in Avacon’s network and demonstrates the limitations of today’s approach to DG curtailments, especially the relative coarse granularity of control steps. The authors develop a novel control algorithm for emergency curtailments that takes advantage of technological improvements and describes the architecture for a successful deployment at the example of Avacon’s network and SCADA. The authors compare the amount of curtailed energy under today’s best practice with the theoretical optimum and the novel approach.

Summary (2 min read)

I. INTRODUCTION

  • Distribution System Operators (DSOs) in Germany with a large share of installed DG and long feeders in their networks experience frequent voltage limit violations and the risk of equipment overload in their networks [1] .
  • Therefore, innovative grid congestion management strategies are needed to enable the DSO to deal with the new energy landscape [3] .
  • 3) The limited number of receiver assignments, as in many areas the DGs are often placed in medium voltage and low voltage networks, where they are clustered under one radio frequency.
  • The SGH specifically target these challenges, making use of the widespread smart meter infrastructure rollout in Germany in combination with the increased data processing capabilities of latest supervisory control and data acquisition systems.
  • Section V shows some simulation results and compares both approaches to curtailment.

II. THE SMART GRID HUB

  • The SGH acts as an extension of the distribution network SCADA and -in combination with smart meters and next generation signal receivers that connect to the smart meter gateway -allows grid operation engineers on duty to control small scale DG individually.
  • As a result, the SGH enables advanced curtailment algorithms that respect the limitations of day-to-day grid operation while taking advantage of advanced control options.
  • Automatic control of a large number of small scale DG can be fully automated to require only minimal input from the grid operation engineer.
  • Outbound, it has interfaces to the highly secured public smart meter gateway administration service, which provides access to smart meters in private households.
  • Currently, three communication possibilities between SGH and smart meter gateways are supported: A key benefit from the DSO perspective in this modular approach is that there is no need to alter the mission critical SCADA system to provide the desired additional functionality.

III. DG CURTAILMENT IN CRITICAL SITUATIONS

  • As mentioned, DG capacity and generation may vastly exceed demand in a region, to the point where the capacity limits of the power lines would be exceeded.
  • This logically leads to the situation that the grid operator is forced to curtail the regional feed-in on several occasions to avoid equipment overload and tripping of protections.
  • 3) Ensuring that all curtailment actions are carried out in a non-discriminatory manner to guarantee equal treatment of all customers.
  • These are located at lower voltage levels, together with the system's loads and collectively connected to the HV system via HV/MV-substations.
  • The following additional assumptions are made for the system: Generators only contribute active power to the line load.

A. Best Practice Approach

  • Based on the regulatory framework the DSOs in Germany are fully unbundled from all generation assets, while private companies usually operate DGs.
  • The options to control these units however are limited.
  • Large generation plants such as WFs are connected directly to the DSO SCADA, whereas most smaller units, like PVs and CHPs, are oftentimes only equipped with a long wave radio receiver, which are usually clustered per substation.
  • This can result in an over-curtailment of regional DG production with the intention of avoiding equipment overload.
  • Finally, 𝑃𝑃 𝐿𝐿𝐿𝐿𝑎𝑎𝐿𝐿 is the summed-up system load.

B. SGH with fine granularity control

  • The SGH enables the DSO to leverage the smart meter infrastructure, which will become standard in Germany in the upcoming years.
  • This enables the possibility to control small DG individually and directly, which did not exist up to now.
  • The DSO will have a substantial number of additional options to shape the curtailment action and track the technical limits of stressed equipment more closely.
  • The operating engineers can control smaller units, increasing the granularity and therefore reducing the overcompensation of the curtailment.
  • Their respective curtailed powers 𝑃𝑃 𝑃𝑃𝑃𝑃,𝑐𝑐𝑐𝑐𝑐𝑐 𝑗𝑗 and 𝑃𝑃 𝐶𝐶𝐶𝐶𝑃𝑃,𝑐𝑐𝑐𝑐𝑐𝑐 𝑘𝑘 are therefore given by: EQUATION EQUATION Again, an optimization problem can be formulated to minimize the curtailed power: (5).

IV. TESTCASE SYSTEM

  • The considered HV lines connect two small cities over a distance of 29 km.
  • Fig. 3 depicts the history of curtailed power magnitude, while Fig. 4 illustrates the duration of the requests, sorted descending from large to small values respectively.
  • The reference time series for single wind generators is the normalized time series of one the regional windfarms.
  • The maximum line overload would have amounted to 68.285 MW while the average power overload would have been 21.702 MW.
  • Analysis showed that the best practice approach to DG curtailments enabled the DSO to reach a solution which was very close to the technical optimum, at 100,002 % of the lower boundary of required curtailments.

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A Novel Approach to DG Curtailment in Rural
Distribution Networks – A Case Study of the Avacon
Grid as Part of the InterFlex Field Trial
Thorsten Gross, Sven Reese, Benjamin Petters
Avacon Netz GmbH
Salzgitter, Germany
{thorsten.gross, sven.reese, benjamin-georg.petters}@avacon.de
Marco Cupelli, Dominik Mildt, Antonello Monti
Institute for Automation of Complex Power Systems
E.ON Energy Research Center RWTH Aachen University
Aachen, Germany
{mcupelli, dmildt, amonti}@eonerc.rwth-aachen.de
Abstract Distribution system operators in rural areas of
Germany are frequently facing imminent equipment overloading
caused by the feed-in of local renewable Distributed Generation
(DG). A grid operator’s last resort to maintain system stability and
avoid protection tripping is to temporarily curtail local feed-in
until hosting capacity in the network has caught up with the
demand. Due to technological limitations in today’s networks the
volume of curtailed energy can be greater than what would strictly
be necessary. This paper presents a case study of a 110 kV
overhead line in Avacon´s network and demonstrates the
limitations of today’s approach to DG curtailments, especially the
relative coarse granularity of control steps. The authors develop a
novel control algorithm for emergency curtailments that takes
advantage of technological improvements and describes the
architecture for a successful deployment at the example of
Avacon´s network and SCADA. The authors compare the amount
of curtailed energy under today´s best practice with the theoretical
optimum and the novel approach.
Keywords—Generation curtailment, distribution network,
renewable energy sources, optimization, distributed generation,
thermal overloading
I. INTRODUCTION
D
istribution System Operators (DSOs) in Germany with a
large share of installed DG and long feeders in their networks
experience frequent voltage limit violations and the risk of
equipment overload in their networks [1]. Moreover, congestion
is becoming a critical issue in densely clustered grids network
[2]. Therefore, innovative grid congestion management
strategies are needed to enable the DSO to deal with the new
energy landscape [3]. Consequently, the topic of congestion
management and curtailment lately received notable attention in
research [4]-[10].
Over the past decade Germany has seen a significant growth
in decentralized renewable energy sources (RES). According to
the renewable energy act grid operators have a legal obligation
to connect all DGs to their network and accommodate all energy
that is being produced by renewable DGs [11]. To comply with
this regulation, the challenges that German DSOs are facing are
twofold: First, the DGs are often located in rural areas where the
hosting capacity of the network is not traditionally designed to
deal with their presence. Second, the volatility and
unpredictability of RES puts additional operational burden on
the DSO.
If the DGs’ feed-in exceed the network’s nominal capacity,
there exists the risk of violating voltage limits or the equipment’s
thermal limits. In such situations, the grid operators have the
option to temporarily curtail local feed-in to maintain system
stability and avoid protection tripping. Curtailment options of
DG come with the obligation to increase the network’s hosting
capacity as soon as possible [12]. However, grid operators had
difficulties catching up with the growth of renewable energy in
recent years, which resulted in a total annual cost for curtailment
actions of 373 M€ in 2016 [13].
For many grid operators it is best practice to control small
scale DGs via long wave radio signals. With these signals grid
operators can limit the generators output to 100%, 60%, 30% or
0% of its nominal power. While this technology has proven to
be simple, robust and cost-effective it also comes with several
drawbacks:
1) The lack of communication backchannel, making i
t
im
possible to confirm whether the signal has bee
n
r
eceived and acted upon.
2) The limitation of only four discrete setpoints.
3) The limited number of receiver assignments, as
in
m
any areas the DGs are often placed in medium voltage
and low voltage networks, where they are clustere
d
un
der one radio frequency. The motivation for this
approach was that on the one hand earlier SCADA
could not automate the process of receiver assignment.
On the other hand, it was OPEX driven as the service
provider charges per signal address.
The combination of 2) and 3) means that in practice
curtailment actions can only be carried out in comparably large
discrete steps. As a result, it is very difficult to adjust the output
precisely to the required technical limits and oftentimes DSOs
are forced to curtail more energy than theoretically needed.
Hence, a novel approach for DG curtailment, which features
finer granularity and dedicated bi-directional communication
channels is required, leveraging on the advancements in data
transmission and communication technology.
(c) 2018 IEEE. Personal use
of this material is permitted.
Permission from IEEE must be obtained for all other users.
DOI: 10.1109/INDIN.2018.8472095.
Publisher version: https://ieeexplore.ieee.org/document/8472095

This paper presents the Smart Grid Hub (SGH), which is
developed by Avacon as part of the H2020 InterFlex
Project [15]. The SGH specifically target these challenges,
making use of the widespread smart meter infrastructure rollout
in Germany in combination with the increased data processing
capabilities of latest supervisory control and data acquisition
(SCADA) systems. A case study proposes its application to
assist DSOs with an optimized curtailment strategy that enables
an increasing share of RES in the grid, which could not be
achieved with the best practice approach.
The remainder of this paper is organized as follows.
Section II briefly explains the SGH architecture and how it
integrates with existing SCADA and other legacy systems.
Section III then introduces the best practice approach to
curtailment, as well as a novel algorithm that makes use of the
increased communication capabilities. Section IV presents one
of Avacons’s most frequently congested high voltage (HV)
systems as a case study for simulation. Section V shows some
simulation results and compares both approaches to curtailment.
Finally, section VI gives a short conclusion.
II. T
HE SMART GRID HUB
T
he SGH acts as an extension of the distribution network
SCADA and in combination with smart meters and next
generation signal receivers that connect to the smart meter
gateway allows grid operation engineers on duty to control
small scale DG individually. As a result, the SGH enables
advanced curtailment algorithms that respect the limitations of
day-to-day grid operation while taking advantage of advanced
control options. For instance, automatic control of a large
number of small scale DG can be fully automated to require only
minimal input from the grid operation engineer.
In order to comply with the unbundling regulations and
obligations derived from the renewable energy act, the SGH
approach has been developed and is currently implemented and
tested within the InterFlex project. The SGH approach consists
of a grid management system, which acts as an
aggregation/disaggregation platform interfacing the DSO
SCADA system with the residential smart meter infrastructure.
The SGH depicted in Fig. 1 is located within the DSO
SCADA environment and connects to it via a
IEC60870-6 TASE.2 interface. Outbound, it has interfaces to the
highly secured public smart meter gateway administration
service, which provides access to smart meters in private
households. The smart meter gateway administration and
integration is defined in the technical guideline TR-03109-01
and regulated by the federal agency for cyber security,
Bundesamt für Sicherheit in der Informationstechnik (BSI).
Currently, three communication possibilities between SGH and
smart meter gateways are supported:
1) Communication via webservices
2) Communication via LTE
3) Communication via powerline
The core functionality of the SGH is to disaggregate a singl
e
c
urtailment request from the grid operation engineer in charge
into a set of individual control signals actuated on the DGs. It
features an optimization engine, which determines the optimal
set of control signals and handles the communication to the DGs
in the field. The optimization engine enables dynamic clustering
based on location, connection, or type of DG. A key benefit from
the DSO perspective in this modular approach is that there is no
need to alter the mission critical SCADA system to provide the
desired additional functionality.
III. DG
CURTAILMENT IN CRITICAL SITUATIONS
As
mentioned, DG capacity and generation may vastly
exceed demand in a region, to the point where the capacity limits
of the power lines would be exceeded. This logically leads to the
situation that the grid operator is forced to curtail the regional
feed-in on several occasions to avoid equipment overload and
tripping of protections. The operator has to determine the
curtailment schedule while taking the following three criteria
into account:
1) Ensuring safe operation of all equipment withi
n
t
echnical limits at all times.
2) Limiting curtailments to a practical minimum.
3) Ensuring that all curtailment actions are carried out in
a non-discriminatory manner to guarantee equal
treatment of all customers.
Rural areas present themselves to be specifically challenging, as
their spatial expansion allows a multitude of RES connected to a
comparatively weak superordinate grid system, that is tasked
with exporting excess power. This paper assumes a HV system
to which encompasses several wind farms (WFs) are either
directly connected to the HV lines or bundled at the medium
voltage (MV) level and then connected via a HV/MV-substation.
Figure 1: SGH Architecture and Flow of Commands

Other DGs include photovoltaics (PVs) and combined heat and
power plants (CHPs), which are of a noticeably smaller scale.
These are located at lower voltage levels, together with the
system’s loads and collectively connected to the HV system via
HV/MV-substations. The following additional assumptions are
made for the system:
Generators only contribute active power to the line
load.
A single line or a combination of lines that share the
load perfectly symmetrical is regarded, which allows to
plan for a single overall capacity limit.
Large scale WFs can accept four setpoints, limiting
their output 100%, 60%, 30% or 0% of their nominal
power. Small scale PVs and CHPs can accept one of
two signals at a time, on or off.
All generators can accept one control signal at the
beginning of each 15-minute registration period.
A. Best Practice Approach
Based on the regulatory framework the DSOs in Germany
are fully unbundled from all generation assets, while private
companies usually operate DGs. The options to control these
units however are limited. Large generation plants such as WFs
are connected directly to the DSO SCADA, whereas most
smaller units, like PVs and CHPs, are oftentimes only equipped
with a long wave radio receiver, which are usually clustered per
substation. Therefore, in best practice, control can only be
exerted over the larger scale WFs. Historically, these units can
accept setpoints to limit their momentary output to 100%, 60%,
30% or 0% of their nominal power. When considering

WFs, where

is the set of all WFs in the system, their
curtailed power is given as:
,
=
0  
,
,

,
{0, 0.3, 0.6, 1}
.
(1)
Here,
,
is the curtailed of WF ,
,
is its
momentary uncurtailed generation,
,
is its nominal power
and
defines the actual setpoint. This limits a grid operator to
a few discrete steps to curtail the DG feed-in. Consequently, this
can result in an over-curtailment of regional DG production with
the intention of avoiding equipment overload. The best practice
curtailment algorithm can be stated as an optimization problem
that aims to minimize the curtailed power.
min
,
∈

s.t. (1),
(
,
,
)
∈

+
,
∈

+
,
∈

−

,
.
(2)
The nominal line capacity is given by
,
, while
,
states the uncurtailed generation of the PV generator

,
where

is the set of all connected PV generators. Similarly,
,
is the uncurtailed generation of the CHP

and

is the set of all connected CHPs. Finally,

is the
summed-up system load.
B. SGH with fine granularity control
The SGH enables the DSO to leverage the smart meter
infrastructure, which will become standard in Germany in the
upcoming years. This enables the possibility to control small DG
individually and directly, which did not exist up to now.
Consequently, the DSO will have a substantial number of
additional options to shape the curtailment action and track the
technical limits of stressed equipment more closely. The
operating engineers can control smaller units, increasing the
granularity and therefore reducing the overcompensation of the
curtailment.
As stated previously, small scale PV and CHP applications
can only be regulated to an on or off state. Their respective
curtailed powers
,
and
,
are therefore given by:
,
=
,
,
{0,1}
,
(3)
,
=
,
,
{0,1}
.
(4)
The setpoints are defined by the binary indicators
and
.
Again, an optimization problem can be formulated to minimize
the curtailed power:
min
,
+
,
∈

+
∈

+
,
∈

s.t. (1), (3), (4)
(
,
,
)
∈

+
(
,
,
)
∈

+
(
,
,
)
∈

−

,
.
(5)
IV. TESTCASE SYSTEM
The focus of the case study is the system depicted in Fig. 2,
which consists of two 110 kV overhead lines in northern
Germany. The considered HV lines connect two small cities over
a distance of 29 km. Each line system is equipped with three
phase Al/St conductors of the type 1*3*1*150/25 mm² Al/St. At
standard conditions, the conductor is rated for 465 A, which
corresponds to 90 MW of total transmission capacity per system
at 110 kV. As stated previously, HV lines are treated as a single
system with the summed capacity of the single conductors. This
results in a thermal limit of 930 A or
,
180MW at
standard operating conditions.

Currently, a total of 7 windfarms are connected directly to
the 110 kV lines, where four of those are connected to system 1
and the other three are connected to system 2. Another three
windfarms are connected at lower voltage levels. The total
nominal power of these windfarms amounts to 321.4 MW.
Additionally, a total of 73 MW of small scale DGs are installed
in the underlying MV and low voltage (LV) networks. DSO
operation is challenged by the fact that the total installed capacity
of DGs amounts to almost 400 MW, which is more than twice
the amount of power that the line can transport. At the same time,
the annual net peak load is approximately 80 MW. This
corresponds to only 20.26 % of installed DG and currently leaves
curtailment as the only option in case of high RES generation.
To underline the necessity of analyzing and improving
curtailment behavior, Fig. 3 and 4 show historical data of the
curtailment requests within 2016 and 2017 for the example
system. Fig. 3 depicts the history of curtailed power magnitude,
while Fig. 4 illustrates the duration of the requests, sorted
descending from large to small values respectively. Clearly, the
previous hold true, as within these two years significant
curtailment efforts were made. In total, the network operated
under curtailment for more than 26300 min, which corresponds
to about 2.5 % of the whole timeframe.
In our example, a week in summer 2017 is analyzed. A
combination of high wind production and low consumption lead
to imminent equipment overload at several occasions during this
week. Power output time series for small scale generators are
represented by synthetical data, multiplying their nominal power
with a reference time series. The reference time series for PV is
the PV forecast of regional transmission system operator (TSO),
50Hertz Transmission. The reference time series for single wind
generators is the normalized time series of one the regional
windfarms. CHPs are assumed to run at full capacity all the time.
Fig. 5 shows the combined load on the two HV-lines.
Positive values correspond to net power exports and negative
values to net power imports. During the observed interval
several curtailments were carried out at the request of the
connected TSO. An interpolation between the last value before
the curtailment action took place and the first value after the end
of the curtailment action was performed to show the hypothetical
overhead line utilization without external interference, i.e.
Figure 2: Grid Section
Figure 3: Sorted history of the requested curtailment power in 2016/17
Figure 4: Sorted history of the curtailment request durations in 2016/17
Figure 5: Combined Load on HV lines Before Curtailments

curtailment requests. The grey line indicates the maximum line
capacity and the red boxes highlight time periods during which
significant curtailment was needed.
Without curtailment, the static thermal limit of the conductor
would have been violated for a total 1305 mins which
correspond 87 of the 15-minute registration periods in the
regarded week. The maximum line overload would have
amounted to 68.285 MW while the average power overload
would have been 21.702 MW. Total surplus energy beyond the
conductors´ capacity would have amounted to 472.009 MWh.
This also represents the lower boundary for the curtailed energy.
V. T
ESTCASE SIMULATION
The test system was modeled in MATLAB [16] to compare
best practice and SGH-based curtailment for the presented week.
Optimization problems were created using the free YALMIP
toolbox [17], using a mixed integer formulation to map binary
and logic constraints in (1), (3) and (4). The commercial Gurobi
solver [18] was employed in the actual calculation. As explained
previously, todays best practice only made use of the flexibility
from large windfarms and limiting the available setpoints to four
discrete steps of 100%, 60%, 30% and 0% of nominal power. In
the SGH-based approach small scale generator control was
introduced to increase the granularity of curtailment actions.
Tab. I provides indicators of the resulting power and energy
curtailment.
Fig. 6 and 7 show an enlarged view of the active power
exported during the highlighted regions of Fig. 5 under the two
different curtailment algorithms. Evidently, the finer granularity
of the SGH-based approach allows operation closer to the actual
conductor capacity limit in many cases. In most cases, the
remaining deviation from the conductor limit becomes
indiscernible on the MW scale. Fig. 8 additionally shows the
propagation of curtailed energy by its cumulative amount over
the past time. Although differences seem minor, the best practice
approach consistently required curtailment of additional energy.
Including the smaller generators in the set of potential
curtailments expanded the space of possible actions and hence
increased the granularity of curtailment commands. As a result,
the grid’s ability to accommodate local generation could be
increased and the amount of curtailed energy required to ensure
a safe and secure operation of the grid was reduced. The new
approach reduced the excess curtailments to virtually zero,
saving 1.739 MWh or 3.67 % of the energy in this scenario.
Analysis showed that the best practice approach to DG
curtailments enabled the DSO to reach a solution which was very
close to the technical optimum, at 100,002 % of the lower
boundary of required curtailments. This worse-than-optimal
solution was caused by the small modulation option. We may
recall that the grid operator had to achieve the target value on
curtailments being able to control a limited number of DGs and
with only a small number of discrete setpoints.
Figure 6: Enlarged view of the resulting power flowing through the HV
line for the first period highlighted in Fig. 5
Figure 7: Enlarged view of the resulting power flowing through the HV
line for the second period highlighted in Fig. 5
Figure 8: Cumulative curtailed energy over the regarded week
TABLE I. OVERVIEW OF CURTAILMENT EVENTS
Best practice
min
max
Ø
Σ
0.413
68.292
21.781
-
0.103 17.073 5.446 473.755
SGH-based
min
max
Ø
Σ
0.400
68.285
21.702
-
0.100 17.071 5.425 472.016

Citations
More filters
Proceedings ArticleDOI
19 Mar 2019
TL;DR: In this paper, a convolutional long short-term recurrent neural network (convLSTM) was proposed to predict wind power output time-series by including wind speed and direction from neighboring points in the vicinity of the wind turbine or wind farm in question.
Abstract: Forecasting wind power production using machine learning techniques proves difficult in practice due to the high stochasticity of the wind power time-series. To improve these forecasts, we include wind speed and wind direction from neighboring points in the vicinity of the wind turbine or wind farm in question. We assume that this additional information can improve the wind power forecast as the wind speed and direction at the wind turbine is influenced by the distributed wind speeds and directions scattered over the topology.To make best use of these additional inputs, we propose using convolutional long-short term recurrent neural networks (convLSTM). Their advantage is the property of including temporal dependencies arising from the (wind) time-series as well as spatial dependencies obtained from geographically scattered wind forecasts. convLSTM shows promising results to modulate both temporal as well as spatial dependencies on wind power output time-series.

13 citations


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  • ...Feature reshaping of the GEFCom data set into [4, 5, 2] shape...

    [...]

  • ...0001, 0] Gradient clip [7, 10, 15, 20] Kernel dimension 1 [2, 3, 4] Kernel dimension 2 [2, 3, 4]...

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Journal ArticleDOI
12 Aug 2020-Energies
TL;DR: A framework to simulate the incidental amount of renewable energy curtailment based on load flow analysis of the network and the extension of the n-1 security criterion offers significant potential to reduce curtailment by up to 94.8% through a more efficient utilization of grid capacities.
Abstract: Power system security is increasingly endangered due to novel power flow situations caused by the growing integration of distributed generation. Consequently, grid operators are forced to request the curtailment of distributed generators to ensure the compliance with operational limits more often. This research proposes a framework to simulate the incidental amount of renewable energy curtailment based on load flow analysis of the network. Real data from a 110 kV distribution network located in Germany are used to validate the proposed framework by implementing best practice curtailment approaches. Furthermore, novel operational concepts are investigated to improve the practical implementation of distributed generation curtailment. Specifically, smaller curtailment level increments, coordinated selection methods, and an extension of the n-1 security criterion are analyzed. Moreover, combinations of these concepts are considered to depict interdependencies between several operational aspects. The results quantify the potential of the proposed concepts to improve established grid operation practices by minimizing distributed generation curtailment and, thus, maximizing power system integration of renewable energies. In particular, the extension of the n-1 criterion offers significant potential to reduce curtailment by up to 94.8% through a more efficient utilization of grid capacities.

12 citations


Cites background from "A Novel Approach to DG Curtailment ..."

  • ...One of the main contributions of this paper is thus the development of a curtailment simulation framework and its application to the model of a real 110 kV distribution network from a region located in Germany....

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  • ...In Germany, particularly in rural areas, the increasing installation of DG systems coincides with low hosting capacities due to the historical dimensioning of the network [1]....

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  • ...The optimization objective is thus adapted as follows: min f(x) = ∆P ⋅ c ⋅ ∆t + p (∆P ) with p = 0 if ∆P = 0c else (7) The variable costs cvar are estimated based on the total amount of curtailed energy in Germany in 2017 and the respective amount of financial reimbursements, which amount to 610 M€ for 5518 GWh of curtailed energy [11], resulting in variable costs of 110 €/MWh....

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  • ...Although DG curtailment can only be exploited as a last resort in Germany [1], a significant historical increase of these measures can be observed....

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  • ...The model of a real 110 kV high voltage (HV) distribution system with 100 nodes and a ring topology located in Germany is used as a case study in this paper....

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Journal ArticleDOI
TL;DR: In this paper, a short-term curtailment prediction model for distribution grids is proposed, which takes different operational security criteria into account, whereas the models for the node-injections are adjusted to the characteristic of each grid node specifically.
Abstract: Renewable energies curtailment induced by grid congestions increase due to grown renewable energies integration and the resulting mismatch of grid expansion. Short-term predictions for curtailment can help to increase the efficiency of its management. This paper proposes a novel, holistic approach of a short-term curtailment prediction for distribution grids. The load flow calculations for congestion detection are realized by taking different operational security criteria into account, whereas the models for the node-injections are adjusted to the characteristic of each grid node specifically. The determination of required curtailment based on the resulting congestions considers uncertainties of component loading and its corresponding probability. The forecast model is validated using an actual 110 kV distribution grid located in Germany. In order to meet the requirements of a forecast model designed for operational business, prediction accuracy, and its greatest source of error are analyzed. Furthermore, a suitable length of training data is investigated. Results indicate that a six month time period for maintenance gains the highest accuracy. Curtailment prediction accuracy is better for transmission system operator components than for distribution system operator components, but the Sorensen Dice factor for the aggregated grid shows a high match of historic and predicted curtailment with a value of 0.84 and a low error for curtailed energy, which makes 2.23% of the historic curtailed energy. The model is a promising approach, which can contribute to improvement of curtailment strategies and enable valuable insight into distribution grids.

9 citations

01 Jan 2016
TL;DR: In this article, a decentralized approach to enable demand response for managing the congestions more efficiently is presented, which is validated with simulations for representative Dutch lowvoltage (LV) networks.
Abstract: Electrical distribution networks worldwide are facing frequent capacity challenges due to the widespread roll out of various distributed energy resources (DERs). A number of demand response (DR) mechanisms have been developed in order to circumvent the problems and enhance the flexibility of the distribution network. While the existing centralized control system remains its crucial role for reliable and secure grid operation, distributed intelligence is a complement technology with a focus on dividing the control task into a number of simpler problems and solve them with minimum exchange of information. Based on the recent developments of distributed intelligence, this paper discusses a decentralized approach to enable demand response for managing the congestions more efficiently. The approach is validated with simulations for representative Dutch low-voltage (LV) networks.

1 citations

References
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02 Sep 2004
TL;DR: Free MATLAB toolbox YALMIP is introduced, developed initially to model SDPs and solve these by interfacing eternal solvers by making development of optimization problems in general, and control oriented SDP problems in particular, extremely simple.
Abstract: The MATLAB toolbox YALMIP is introduced. It is described how YALMIP can be used to model and solve optimization problems typically occurring in systems and control theory. In this paper, free MATLAB toolbox YALMIP, developed initially to model SDPs and solve these by interfacing eternal solvers. The toolbox makes development of optimization problems in general, and control oriented SDP problems in particular, extremely simple. In fact, learning 3 YALMIP commands is enough for most users to model and solve the optimization problems

7,676 citations


"A Novel Approach to DG Curtailment ..." refers methods in this paper

  • ...Optimization problems were created using the free YALMIP toolbox [17], using a mixed integer formulation to map binary and logic constraints in (1), (3) and (4)....

    [...]

Journal ArticleDOI
TL;DR: Possible congestion management mechanisms for price-responsive electric vehicle demand in electricity distribution networks are investigated and grid tariffs that are fixed ex ante, based on network load, were found to make the problem worse compared to the base-case scenario of flat tariffs.
Abstract: Possible congestion management mechanisms for price-responsive electric vehicle demand in electricity distribution networks are investigated. Because a high penetration of renewable energy sources weakens the correlation between wholesale electricity prices and network demand, cost-minimizing electric vehicles may cause high peaks in network load. Managing congestion is not costly in theory but difficult to implement efficiently. Grid tariffs that are fixed ex ante, based on network load, were found to make the problem worse compared to the base-case scenario of flat tariffs. An optimal dynamic grid tariff yields desirable outcomes but is difficult to determine in case of realistic forecasting uncertainties. An iterative approach of a distribution grid capacity market has practical barriers related to IT infrastructure and computational requirements. Advance capacity allocation is more straightforward to implement, but the inter-temporal constraints of the electric vehicles continue to pose a challenge.

179 citations


"A Novel Approach to DG Curtailment ..." refers background in this paper

  • ...Therefore, innovative grid congestion management strategies are needed to enable the DSO to deal with the new energy landscape [3]....

    [...]

Journal ArticleDOI
TL;DR: The results demonstrate that taking an active approach to managing power flows can significantly increase the output of DG units in a thermally constrained network.
Abstract: This paper presents an evaluation of the main characteristics of two power flow management (PFM) methodologies against a traditional inter-trip approach typically used by distribution network operators. The two PFM algorithms were developed, by the authors, for real-time operation with an aim to implement them in distribution networks with growing penetrations of renewable DG. The first PFM approach is modelled as a constraint satisfaction problem (CSP), while the second is based on an optimal power flow (OPF) approach. These PFM algorithms are deployed on real substation hardware to simulate the monitoring and control of MV distribution network power flows through DG real power regulation. Multiple scenarios are presented to the closed-loop PFM test environment to demonstrate the algorithms ability of detecting and alleviating thermal overloads and recognizing when the constraint has passed. The main objective of this paper is the quantification of the resultant curtailment levels, for the two approaches, which are compared to that of a traditional inter-trip scheme for the same circuit overload duration. The results demonstrate that taking an active approach to managing power flows can significantly increase the output of DG units in a thermally constrained network.

43 citations

Proceedings ArticleDOI
17 Jul 2016
TL;DR: In this paper, the authors proposed a mixed-integer programming (MILP) based active power curtailment (OPF) method for congestion management in lowvoltage distribution networks.
Abstract: The rapid proliferation of distributed energy resources (DERs) leads to capacity challenges, i.e. network congestions, in the low-voltage (LV) distribution networks. A number of strategies are being widely studied to tackle the challenges with direct switching actions such as load shedding or power curtailment. On the other hand, various market-based demand response (DR) programs have been developed to influence the large number of DERs to use their flexibility to deal with network congestions. However, most of the market-based solutions rely on the flexibilities of the DERs, thus cannot solve the congestion when flexibility is not available in the network. To complement the market-based solutions, a smart active power curtailment based mechanism is necessary for managing the congestions in the distribution network. In this paper, we propose a novel method for congestion management by active power curtailment based on a Mixed-Integer Programming technique. In addition, two greedy selection methods together with fair power curtailment and security constrained OPF methods have been developed for the sake of comparison. The overall performance of the proposed approach and the comparison with other methods have been verified by a simulation with a typical LV network of the Netherlands.

35 citations


"A Novel Approach to DG Curtailment ..." refers background in this paper

  • ...Distribution System Operators (DSOs) in Germany with a large share of installed DG and long feeders in their networks experience frequent voltage limit violations and the risk of equipment overload in their networks [1]....

    [...]

Proceedings ArticleDOI
01 Nov 2015
TL;DR: In this article, an online optimal power management problem for microgrid energy market considering electric vehicle (EV) charging/discharging, load curtailment and grid power transactions is considered by the microgrid central controller for the dispatch.
Abstract: This paper proposes an online optimal power management problem for microgrid energy market considering electric vehicle (EV) charging/discharging, load curtailment and grid power transactions. Fuel and emission costs of conventional sources, hourly profits, incentives for load curtailment, revenue/cost of grid power trade and charging/discharging price of electric vehicles (EV) are considered by the microgrid central controller (MGCC) for the dispatch. A realistic model for EV is considered with its state of charge (SOC), age/life, charging/discharging rate limits, trip period and number of switching. Two different objectives of the MGCC viz. operational cost minimization and overall profit maximization are compared in the CIGRE LV benchmark microgrid in terms of revenue, expense, node voltage, curtailed load, EV power, grid trade and overall execution time. Particle swarm optimization with time varying acceleration co-efficient (PSO-TVAC) and modified backward forward sweep (BFS) based optimal power flow (OPF) method is used to optimize the benefits.

10 citations

Frequently Asked Questions (1)
Q1. What contributions have the authors mentioned in the paper "A novel approach to dg curtailment in rural distribution networks – a case study of the avacon grid as part of the interflex field trial" ?

This paper presents a case study of a 110 kV overhead line in Avacon ́s network and demonstrates the limitations of today ’ s approach to DG curtailments, especially the relative coarse granularity of control steps. The authors develop a novel control algorithm for emergency curtailments that takes advantage of technological improvements and describes the architecture for a successful deployment at the example of Avacon ́s network and SCADA. The authors compare the amount of curtailed energy under today ́s best practice with the theoretical optimum and the novel approach.