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   This part of the project represents central and the most important part. It is a software model for the simulation of the many different scenarios related to the power system operation. Main focus is on testing optimal SCADA implementation regarding reliability and security of power system with integrated smart grid features, distributed generation and deregulated market environment.

The goal is to have a data acquisition system which will be constantly gathering data from all hardware components installed. This system has a task to organize all the input data into frames and then forward the organized and converted data to the various simulation programs described previously. Various calculations are done there. Risk based analysis, physical constraints analysis, optimal power flow and agent based and dynamical modelling are also included.

   The database on server is in charge of data storage  and is proposed to be developed in Microsoft SQL and the connection between the data acquisition and data management and storage will be created using LabVIEW.

   LabVIEW has the possibility to collect the data from the hardware and instruments installed. In the same time through predefined set of its VIs (Virtual Instruments) in the DCT kit (Database Connectivity Toolkit) it can communicate with the database. This part of the server will be gathering the data from variables that represent the measured values. After that it will store the data in created database where it will be accessible for further data mining and revision.

   The advantage of this approach is the possibility to monitor all the processes over the distance whether using local intranet on which all the components will be connected or global internet. The combination can enable the inclusion of remote alarming and command via the smart mobile phones or personal computers.

   It is planned to design a web service which will be used to easily read the status of all the components of the system.

   With the help of LabVIEW Web server, VI-s can be deployed as individual web services which can be called upon using HTTP protocol. These protocols do not require installation of standalone run-time mechanisms which means they can be run using just HTML or JavaScript.

   The interface can be most simply designed using the LabVIEW Web UI Builder.

   The extended use of this proposed testbed for microgrid is for educational purposes. Since the testbed will include the real data gathering from the sun and wind resource, measure the production from wind aggregate and PV array, measure the power quality and demand, it can be used to educate and demonstrate the nature and impact of distributed renewable sources. Furthermore all the analysis which the testbed will be able to conduct can provide even more detailed information to students and even have the weight to center a certain laboratory project around it.

 

Testbed construction

   The testbed platform consists of many different components. To simplify the development the proposed concept is divided into 3 layers. As it can be seen in Figure 3, under layers are Physical, SCADA and Workflow.

 

Figure 3  Conceptual layering of the testbed

 

 

1Physical layer

   All the physical components installed come under the physical layer which is directly connected to the server and database. The operating status of all the components will be visible in LabVIEW developed interface and in web. From there, depending on the simulation results and user requirements, remote control can also be established.

2. SCADA layer

   The SCADA layer can be represented by the LabVIEW interface. On the server the proposed LabVIEW interface can be developed which will gather all the data and store it into the database. From there the information about the status of all the components can be sent to personal notebooks or phones via email notification or through access to the web-service of the LabVIEW interface. The calculations would be done in the background in the workflow layer, but the statuses and reports would also be visible in LabVIEW interface.

 

Figure 4 Web Service can communicate with the Application through

3. Workflow layer

   In the workflow layer the most important parts are simulation software PowerWorld, AnyLogic and ANYSIS.

   The data gathered by the server is used as input for the simulations in PW. PW can use the provided data to conduct more precise calculations since the real data is used. PW will also be used to conduct calculations on a wider scale. The built LV grid on FER that includes renewables and smart metering will become one part of the grid. Using AnyLogic this part can be changed stochastically and multiplied through different developed algorithms similarly like it has been done with the model of the house in the present AnyLogic model.

   The great advantage PW has is the inbuilt script language which enables a uniform and simple change of components. This can be used to, for example, determine a new grid configuration under some specific conditions and add new parts or change already present ones. 

   There are several examples of connecting JADE (Java Agent Development Framework) with PW through EZJcom interface.  Instead of using the JADE interface AnyLogic can be used. 

SCRIPT Edit
{

                EnterMode(Edit);
                }
...
                DATA AddGen(GEN, [busnum, GenID, GENAGCAble, GenParFac, GenFixedCost, GenFuelCost,
                                          GenMWMin, GenMWMax, GenEnforceMWLimits...])
                {

Figure 5 An example of the script command inside edit mode in PW

 

 

Detailed scheme of the server network connections

   Complete scheme of the project is shown on the figure below (Figure 6). On the figure (Figure 6) the detailed connections between physical, SCADA and workflow layer can be seen.

   The physical layer contains PV system on the top of the D building and the hybrid system situated on the top of the C building. Parts of the physical layer are also the resources, both sun and wind, the consumption and the power quality measurement achieved with installed smart meters. All mentioned produces information which is collected and processed on the server.

   The workflow layer has been represented by the AnyLogic, PowerWorld and ANYSIS. Communication between different software tools can be established using the EZJCOM environment as mentioned before.

Figure 6 Detailed scheme of the server

 

Example case of use

   Model for evaluation and analysis of the certainty process control system can be defined as a recorded current situation of the IT system to the risk model . To be able to perceive risks of the process ordinary risk model must be expanded by the business model as it is shown on the figure below (Figure 7). Business model gives opportunities to monitor the current state of the grid, safety of the operation andenable the work of auxiliary services incoordination with the grid.

In this situation there are several issues:

·         is the data transferred correctly;

·         how is synchronization of changes in IT system done;

·         does the model provide enough information;

PCS system of the new generation has the extension which provides other functions:

·         initial export of the architecture of the system in the risk model (arrow 2),

·         modification of the risk model in response to some change in the IT system,

·         sending the status of the IT system components in the risk model to allow dynamicrisk monitoring and risk assessment,

·         notification of the changes in the IT system,

·         possibility to change the functionality in the critical situations in order to limiti the consequences of an assault on the system

Figure 7 Model for evaluation and analysis of the certainty process control system

   PCS system contains both physical and logical structures. The physical structure defines a physical position of the computers and the LAN connections between them. PCS system Extension allows dynamic reading of the physical structure and real time comparing with the logical structure. The logical structure defines program modules and communication between them.  The program modules are connected by client-server connector independent form their physical position. Both structures are shown on the figure below (Figure 8).

Figure 8 Physical and logical structure of PCS system

 

 

Implementation of PowerWorld for microgrid simulation

   PowerWorld Simulator is a power system simulation package designed from the ground up to be user-friendly and highly interactive. Simulator has the power for serious engineering analysis, but it is also so interactive and graphical that it can be used to explain power system operations to non-technical audiences.

Microgrid modeling

   Configuration of the microgrid was chosen with help of the program called HOMER. Main factor in choosing configuration was not economy, but it was the liability that the microgrid can work both in the island operation as well as when it is connected to the grid.

The chosen microgrid is composed of:

·         500 kW of PV (2000 PV modules with power of 0,25 kW per unit)

·         4 wind turbines with power of 2 MW per unit

·         1000 diesel aggregates with power of 4,5 kW per unit

·         250 batteries with capacity of 7,6 kWh per unit and cumulative power of 0,51 MW

·         industry and households demand, scaled on 30 MWh/d and 51 MWh/d

   Important thing to notice is the simple way the simulation components can be added or modified. More of this procedure, which will be found as very valuable for the integration into the testbed, will be described later. As it can be seen from above only the active power is observed in the simulation. The idea was to simulate the grid which consists of few microgrids and observe what happens with the current and voltages in the grid. What  is called microgrid in the simulation could also represent the Smart House or Building if the power of the components is reduced. The microgrid is shown in the Figure 9.

Figure 9 Model of the microgrid developed in PowerWorld

   As it is shown (Figure 9) the microgrid contains two buses named K7 (10,5 kV) and N8 (0,4 kV). Four wind turbines, photovoltaic modules and the demand are all connected to the bus K7. A generator and a load connected to the bus N8 represent diesel aggregate and a battery. The load is needed to simulate the battery discharging, that is to say, giving the power to the microgrid in the moment of a lack of energy from distributed sources. Generator on the bus N8 has a range of output power from -0,5 MW (maximum power which can be charging the battery) to 5 MW (maximum power which can both the battery and the diesel aggregate send to the grid). Parameters of the line and the transformer are typical values for distribution network. Capacity of the line and the nominal power of the transformer are both 10 MVA.

   First model is built of four microgrids and the goal of the model was to show what happens on the connection between the distribution network consisting of microgrids and the transmission network. Real data for insolation, wind speed and load are used in the model. One year is shown through four characteristic days (one for each season).  The result of the simulation indicated that distribution network built from the modeled microgrids can be independent part of the system for most of the year (except winter). Thing which is more important than the mentioned result is that fact that PowerWorld can simulate behavior of as much as you need microgrids working in parallel. For this simulation Time Step Simulator add-on was used which allows the usage of time series of data as the input data.

Second model is more oriented on the connection between the microgrids. It consist of three microgrids and is shown on the figure below (Figure 10).

Figure 10 Grid consisted of three microgrids

 

 

AnyLogic model

   The purpose of the model is to simulate a city that has implemented smart grid and demand response paradigm. 

   The city model is modeled in software AnyLogic

   The city model consists of two levels. The lower level are buildings, and the higher level is the main level which controls the city and manages demand response by having direct control over buildings level. 

   The buildings are modeled as an agent and they act as smart buildings which means that automation system controls all loads and also utility can control the building. There are 1030 buildings in the city model. The agent building’s behavior is defined by the system dynamics modeling and a state chart. Each building agent acts independently so there are 1030 buildings behaving differently which corresponds to the real city where human behavior is irregular. Buildings consumption is based on average Europe home building consumption. Each building has 7 specific loads modeled using the system dynamics modeling. The most common loads are modeled. Parameters of the loads are shown in Table 1. Also, each load starts at different time in each building which makes 7210 modeled loads act independently.

Table 1 Parameters of the loads in the building – data for one day

Load

On time (min)

Off time (min)

Power (W)

Water heater

30

70

800-900

Dishwasher

60

1380

1300-1450

Washing machine

60

1380

1000-1200

Refrigerator

15

35

400-470

TV and PC

480

960

500-600

A/C

15

35

900-1100

Lightning

480

960

200-300

 

   Each building also has a photovoltaic system and an energy storage – battery. Photovoltaic system is modeled using system dynamics. Photovoltaic generates electricity depending what time of the day it is and if there is any sun resource available. Battery storage is modeled using state chart. The overview of the agent building can be seen in Figure 11.

   At the main level, the whole city is controlled by developed algorithm. The consumption, number of turned off loads, amount of generated electricity from the building, total consumption and generation can be read on the simulation screen.

·         If the PV system produces electricity and consumption is lower than generation then the energy surplus is stored into the energy storage to balance generation and consumption. This is done only after the thermo and hydro power plant decreased their generation by the maximum possible value;

·         If the consumption is higher than generation due to a malfunction or some terrorist attack, first the thermo and hydro power plants increase their generation. If that is not enough then the extra needed energy is taken from the batteries. If in the meantime the malfunction has not been repaired and all the batteries are empty, the four controllable loads (water heater, dishwasher, washing machine and refrigerator) start to be turned off in buildings until the balance is again achieved. 

Figure 11 Overview of the building modeled as an agent in AnyLogic

Figure 12 Overview of the main level

Simulation and Results

In the simulation, two scenarios were analyzed:

·         Scenario 1: meeting the peak power using the demand response

·         Scenario 2: minimizing the effect of bigger malfunction or terrorist attack also using the demand response.

Scenario 1

   During some periods of the day, there is an increase in consumption and higher power generation is needed. In business as usual case, the result is that there is an imbalance between the generation and the consumption. Additional 490 kW is needed to meet the peak period and another 250 kWh of energy.

 

Figure 13 Generation and consumption without demand response

 

   After analyzing the same event, but this time using the demand response, the generation and consumption are always balanced due to the extra energy from the battery storage.

 

Scenario 2

   In this scenario, the following situation was analyzed. Hydro power plant has stopped working due to a huge malfunction or a terrorist attack. It is not possible to import energy from anywhere else and all that is available is the demand response. The situation without the demand response is shown in Figure 13. 

Figure 14 Generation and consumption with demand response

 


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