Optimization the operation of renewable energy
sources in electric power system
1
Martin VOJTEK (1st year)
Supervisor: 2Michal KOLCUN
1,2
Dept. of Electric Power Engineering, FEI TU of Košice, Slovak Republic
1
martin.vojtek@tuke.sk, 2michal.kolcun@tuke.sk
Abstract—Proportion of electricity produced from renewable
energy sources records tremendous growth nowadays. This is
happening in accordance with strategies, which aim on decrease
the production of greenhouse gases and carbon emissions. But, on
the other hand it has resulted in many changes and related
problems in electric power system especially with its optimal
operation control. It can be solved by accumulation of electricity,
which can provide better integration of renewable energy sources
due to its internment power supply and it also helps to prepare
conventional distribution grids to new smart grid concept. In the
light of these facts, this is a big challenge and it is necessary to
create new approaches to the management and control of
renewable sources, energy storages, and also to optimal operation
of whole grids.
Microgrids, also characterized as the “building blocks of smart
grids”, are perhaps the most promising, novel network
structure.
In summary, distribution grids are being transformed from
passive to active networks, in the sense that decision-making
and control are distributed, and power flows bidirectional.
This type of network eases the integration of DG, RES,
demand side integration (DSI) and energy storage
technologies, and creates opportunities for novel types of
equipment and services, all of which would need to conform
to common protocols and standards [3].
II. MICROGRIDS CONCEPT
Keywords—renewable energy sources, energy storage, micro
grid, smart grid, optimal operation control.
I. INTRODUCTION
For a number of years, motivated by economics,
decentralization policies and sustainability concerns, the trend
in the power industry worldwide is to reduce investment and
operation costs and to become environmentally friendly. This
has resulted in an increased share of renewable energy (such
as wind and solar) in the total generation capacity, and an
increased number of small and medium sized geographically
distributed power plants (such as wind turbines, photovoltaic
arrays and district combined heat and power plants) [1].
These types of sources are characteristic with unpredictable
and intermittent production of electricity and this is a major
problem. In order to provide a power quality and reliability,
this unstableness and balancing output power must be firmed
in certain way. The variable, intermittent power output from a
renewable power plant, such as wind or solar, can be
maintained at a committed (firm) level for a period of time
using some type of energy storage technology. The energy
storage systems can smooth the output power, control the
ramp rate (MW/min) to eliminate rapid voltage and power
swings on the electrical grid what improve power quality. In
dependence on technology it can also provide frequency
regulation [2].
All of this causes a rapidly changing network topology and
in order to this some new approaches are needed. This
topological change in the power system landscape is opening
up possibilities to form a new concept called microgrid.
Microgrids are defined as localized groups, which integrate
distributed generators, storages systems such as battery and
also local loads. These devices are coupled together and act as
autonomous power systems with a single point of common
coupling to the main electricity network [1][4][5].
Microgrids meet the power quality and reliability
requirements of the local customers [6], and also shield itself
from issues such as voltage distortion, voltage sag, flicker, and
lightning transients [7]. Apart from the technical benefits,
microgrids have also economic advantages [8] if appropriate
optimal control and management systems are implemented.
To economically operate the microgrid, the central
controller will dispatch controllable distributed energy
resources including batteries [4]. A microgrid can either
operate at the grid connected or autonomous modes [6], [7]
when the grid is suffering blackouts. At autonomous modes,
voltage and frequency should be supported by a microgrid
itself, usually through synchronous generators.
For a microgrid without synchronous generators, the system
voltage and frequency would be difficult to maintain without
the support of the ac grid. One solution is to use a voltage
source converter (VSC) interfaced energy sources to provide
voltage and frequency control [9]. In [9]–[11], battery systems
are employed to restore system voltage and frequency quickly
(several cycles). In practice, applications of battery storage
system for grid frequency regulation have been deployed [12]
with the maximum capacity of 20 MW.
As was mention before, microgrid consists of some basic
parts, which must be operated by intelligent control.
Distributed energy sources based on renewable energy, energy
storages and loads are described below.
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A. Distributed energy sources based on renewable energy
During the past decades, the deployment of distributed
generation has been growing steadily. Distributed generators
are connected typically at distribution networks, mainly at
medium voltage and high voltage level, and these have been
designed under the paradigm that consumer loads are passive
and power flows only from the substations to the consumers
and not in the opposite direction [3]. For this reason, many
studies on the interconnection of distributed generators within
distribution networks have been carried out, ranging from
control and protection to voltage stability and power quality
[13].
Different microgeneration technologies, such as microturbines, photovoltaics, fuel cells and wind turbines with a
rated power ranging up to 100 kW can be directly connected
to the LV networks. These units, typically located at users’
sites, have emerged as a promising option to meet growing
customer needs for electric power with an emphasis on
reliability and power quality, providing different economic,
environmental and technical benefits. Clearly, a change of
interconnection philosophy is needed to achieve optimal
integration of such units [3].
Most importantly, it has to be recognized that with
increased levels of microgeneration penetration, the LV
distribution network can no longer be considered as a passive
appendage to the transmission network. On the contrary, the
impact of micro sources on power balance and grid frequency
may become much more significant over the years.
Controllability of intermittent renewable sources units is
limited by the physical nature of the primary energy source
[6]. Moreover, limiting renewable energy sources production
is clearly undesirable due to the high investment and low
operating costs of these units and their environmental benefits
over carbon emission. Consequently, it is generally not
advisable to curtail intermittent renewable energy sources
units, unless they cause line overloads or overvoltage
problems [3][6].
The operation strategy for intermittent renewable energy
sources units can therefore be described as “priority dispatch”.
It means that intermittent renewable energy sources units are
generally excluded from the unit commitment schedule, as
long as they do not violate system constraints. Units with
independent reactive power interfaces (decoupled from the
active power output) can be included in reactive power
dispatch to improve the technical performance of the total
microgrid [3][14].
B. Energy storage systems
Accumulation or energy storage systems are irreplaceable in
terms of production and consumption of electricity. Electric
energy is very problematic commodity in principle and any
efforts to its distribution face the problem of immediate supply
and demand. Energy storages are still in development
nowadays. However, there are some options how to store
electricity with relatively good efficiency [15].
Energy storage systems can be divided into primary and
secondary. Primary storages may supply immediately,
secondary after polarization of electrodes (initially must be
charged). Energy storages can be also divided into many
categories, for example in dependence by the output power,
accumulation capacity, number of cycles and others.
Technological division is described by the block diagram (Fig.
1.).
Fig. 1 Block diagram of energy storage technologies
The energy storage device can be installed for each microsource, or as a shared resource for more microsources, or in
some cases one storage devices for the entire microgrid. The
criteria to decide the ratio of energy storage device to
microsource and also the size of energy storage device is
mainly based on the microgrid characteristics, especially the
dynamic response of the microsources and the power quality
required by the loads [13] [15].
The dynamic response of microsources cannot be seen
independently to design energy storage devices, but it should
be considered relative to the rate of change of the loads. For
instances, a slow-response microsource will just need a small
size energy storage device or no energy storage device at all if
the microgrid loads have slow rate of change. However, it will
require a big size energy storage if the microgrid loads have
fast rate of change. Similarly, a fast-response microsource
depending on the rate of change of the microgrid loads just
requires small size energy storage or no energy storage at all.
The idea here is to balance the dynamic response of the
microsource and the rate of change of loads in order to have
smooth load following or load-generation balancing in
transient [16].
Technically, a storage unit could behave either under a
load-following paradigm (i.e. balancing applications) or under
a price-following paradigm (i.e. arbitrager applications)
depending on the purpose of its operation. At the same time,
storage units can provide balancing reserves ranging from
short-term (milliseconds to minute-level) to long-term (hourly
to daily scale) applications. Specifically, for DC-based storage
technologies (battery, super-capacitor etc.), a properly
designed power electronic interface could contribute to the
reactive power balance of the system without incurring
significant operational costs [3][15][16].
C. Loads
Demand side integration is also referred to as demand side
management (DSM) or demand side response (DSR). It is
based on the concept [17] that customers are able to choose
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from a range of products that suit their preferences. The
innovative products packaged by energy suppliers will deliver
– provided that end-user price regulation is removed powerful
messages to consumers about the value of shifting their
electricity consumption. Examples of such offers include [16]:
1. time-of-use - higher “on-peak” prices during daytime
hours and lower “off-peak” prices during the night
and at weekends (already offered in some EU
member states)
2. dynamic pricing (including real-time pricing) - prices
fluctuate to reflect changes in the wholesale prices
3. critical peak prices - same rate structure as for Time of
use, but with much higher prices when wholesale
electricity prices are high or system reliability is
compromised.
The control of customers load can either be [3][16][17][18]:
1. manual - customers are informed about prices, for
example on a display, and decide on their own to shift
their consumption, perhaps remotely through a
mobile phone
2. automated - customers' consumption is shifted
automatically through automated appliances, which
can be pre-programmed and can be activated by
either technical or price signals (as agreed for
instance in the supply contract).
Demand side integration measures in a microgrid are based
on forecasts of load and source outputs and will very probably
vary from day to day. A requirement for the successful
application of microgrid DSI measures is the adoption of
smart metering and smart control of household, commercial
and agricultural loads within the microgrid. Depending on the
criticality of the target load, DSI measures can generally be
divided into shiftable loads and interruptible loads. The
integration of DSI measures is expected to maximize their
benefits in potential “smart homes”, “smart offices” and
“smart farms” within microgrids [3][18].
A. Upstream network interface
The core interaction with the upstream network is related to
market participation, more specifically the microgrid actions
to import or export energy following the decisions of the
energy service provider/company. Owing to the relatively
small size of a microgrid, the service provider can manage a
larger number of microgrids, in order to maximize its profit
and provide ancillary services to the upstream network.
B. Internal microgrid control
This level includes all the functionalities within the
microgrid that require the collaboration of more than two
actors. Functions within this level are:
• load and renewable energy sources forecast,
• load shedding/management,
• unit commitment/dispatch,
• secondary voltage/frequency control,
• secondary active/reactive power control,
• security monitoring,
• black start.
C. Local control
This level includes all the functionalities that are local and
performed by a single DG, storage or controllable load, that is:
• protection functions,
• primary voltage/frequency control,
• primary active/reactive power control,
• battery management.
It should be noted that these functionalities are relevant to
the normal state of operation. They might need to change in
critical or emergency states. The normal state covers both
islanded and interconnected mode and does not deal with
transition to island mode. The role of information and
communication technology is critical for the relevant control
functions [3].
IV. CURRENT STATUS AND FUTURE DIRECTION OF MICROGRID
III. MICROGRIDS CONTROL FUNCTIONS
RESEARCH IN THE WORLD
Main control functionalities of microgrid are presented in
this section. These functionalities can be distinguished in three
groups, as shown in Fig. 2. The lower level is closely related
to the individual components and local control (micro sources,
storage, loads and electronic interfaces), the medium level to
the overall microgrid control and the upper level to the
interface to the upstream network.
Current research in planning and designing for microgrid
mainly focuses on the following aspects: 1) Models and
algorithms. 2) Optimal configuration for energy storage
system. 3) Distribution network planning containing
microgrid. 4) Software development [14]. For example, Basu,
A. K. et al. [19] proposed an optimization method using
differential evolution technique under real power demand
equality constraint, heat balance inequality constraint, and
distributed generators capacity limits constraint at the planning
of combined heat and power based microgrid, Chen, S. X. et
al. [20] presented a new method for optimal sizing of an
energy storage system in a microgrid for storing renewable
energy at the time of surplus and for rescheduling, Kirthiga,
M. V. et al. [21] proposed an approach transforming an
existing radial distribution network into an autonomous
microgrid using novel sizing and siting strategies for
distributed generators and structural modifications for
autonomous microgrids, the Distributed Energy Resources
Customer Adoption Model (DER-CAM) developed at
Berkeley Laboratory is a fully technology-neutral optimizing
model of economic DER adoption. Its objective is to minimize
the operating cost of on-site generation and CHP systems, for
Fig. 2 Microgrid control functionalities [3]
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either an individual customer site or a microgrid, and Hybrid
Optimization Model for Electric Renewable (HOMER)
developed at the National Renewable Energy Laboratory
(NREL), USA, designs the most optimized and cost effective
hybrid generation system component configuration after a
significant amount of simulations for offgrid or grid-connected
power systems.
Numbers of research work have been reported related to
energy management and control of microgrid with renewable
energy and energy storage [22]. Hierarchal control was
addressed in [22] and planning based operation discussed in
[23]. Intelligent approaches have been presented in
[24],[25].Two-layered control architecture for stabilizing
microgrid in islanded mode has been discussed in [26] and
generation capacity design of microgrid to maintain power
quality and energy surety in both grid-connected and islanded
modes has been discussed in [27].
As was mentioned above, microgrid has three levels of
control functionalities. My future research aims to the lowest
control level named Local control and protection, especially
on battery or other technology independent energy storage
management. This includes optimal operational control in
order to decrease environmental impact and operational costs,
and on the other hand to increase reliability and power quality.
I estimate that to achieve these goals, it will be needed to
create a computer model of microgrid including renewable
energy sources, energy storages, and loads. After creating a
model some optimization methods or algorithm will be
proposed and result will be presented.
ACKNOWLEDGMENT
This work was supported by Slovak Research Agency No.
VEGA 1/0388/13 project.
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