Implementation of a Dynamic Network Model of the Nigerian Transmission Grid for Investigations on Power System Stability

- Electricity is the backbone of any modern society and economy. Therefore, economic growth and increase in social wealth of a country usually lead to an increase in demand for electrical energy especially for a country as Nigeria. As the population of Nigeria is increasing exponentially, there exist a need to make basic needs constantly available, for the wellbeing of the increasing population. This is possible through mechanization. Reliable and stable electricity supply is the surest means to this end. As a result, there is need to constantly review the dynamics of the power system while more energy sources and loads are being added to the existing power network grid. This creates a demand for precise models for the corresponding network. In this paper, the power network system of the Nigerian transmission grid was implemented at normal operations to include the dynamic models to the corresponding network elements (i.e. generation Units based on their installed capacities and controllers). With the help of this model, stationary load flow calculations, as well as network’s model performance in steady state was conducted. The network’s model performance in the case of load changes and fault operations was also carried out. These allowed for investigations on the stability status of the Nigerian transmission grid.


A brief on the Nigerian Electricity System
Electricity generation in Nigeria was thought to have begun in 1896 during the British colonial times. In 1929, the first recognised electrical company was set up to control electricity generation, transmission and distribution in the country. The arm which was charged with power generation (then hydro plants power) was known as the Nigerian Dams Authority (NDA) while the arm charged with the electricity transmission and distribution was known as the Electricity Corporation of Nigeria (ECN). Because of the country's division into different regions, other electrical companies began springing up in various regions that saw to the running of the electricity generation and consumption [1]. It was not until 1972 that the only hydroelectric company at that time -Nigerian Dams Authority, merged with the Electricity Corporation of Nigeria (ECN) -the conglomeration of the small companies, to found the National Electrical Power Authority (NEPA). As this was the only federal parastatal that controlled electricity generation in the country. They were in control of 94% of the total electricity generation and maintained 100% of the transmission, distribution, the marketing sector and the system operators [2]. This monopoly hindered the needed development in the sector that later led to the deregulation of electric power in Nigeria [3]. After the deregulation, 11 distribution companies (DISCO) took over the distribution of electricity, 6-generation companies (GENCO) took over the generation arm while the transmission company of Nigeria still manages the electricity transmission from 330kV to 33kV high voltage infrastructures in the electricity system of Nigeria. The power plants owned by the Niger Delta Power Holding Company (NDPHC) are controlled by the three tiers of government in Nigeria (Federal, State and Local). These power plants are classified as being part of the National Integrated Power Project (NIPP) while others are wholly owned by the state governments and/or private companies/individuals. Such a power plant is referred to as an Independent Power Producer (IPP).
A brief history and structure of the Nigerian electricity system is summarized in figure 1.

THE NIGERIAN POWER NETWORK
Electricity is generated in Nigeria between 10.5 kV to 16 kV from the generators in power plant stations. From these voltage levels, they are stepped-up by transformers depending on the choice of the injection voltage level but mostly to 330kV. Transmission of Electricity sets in immediately from this point. Transmission starts with the transportation of the generated power through the 330kV voltage network along transmission lines/conductors and is stepped-down by transformers to 132 kV at the transmission substations. This voltage is again transported along 132 kV transmission lines to the injection substations and stepped down by a transformer to 33 kV. This is where the Distribution of electricity starts. The voltage is further transported along the 33 kV transmission lines and is stepped down to 11 kV which in turn, is stepped down again to 0.415 kV before it find its way to Nigerian homes and/ offices [4].
These normal procedures does not disprove the fact that there are other voltage levels (e.g. 66 kV etc.) used by industries in Nigeria but these are subject to specific voltage requirements of these industries. This is a function of their machines and equipment. At present, the total installed generation capacity in the entire network based on the received data from Transmission Company of Nigeria (TCN) in November 2018 is approximately 12,908 MW. The Power plants that contribute to this Capacity comprises of less-decommissioned units and therefore, were used in the analysis of the stability of the Nigerian network and Table 1 to Table 4 show their list.

IMPLEMENTED DYNAMIC COMPONENTS FOR THE NIGERIAN NETWORK
The representation of the network dynamics was done using the standard dynamic models for synchronous machine and their control devices. The reason for the choice of the controllers is based on the condition to use standard IEEE recommended models in order to facilitate the tuning processes for better and expected results. The dynamic components of the Generators in the power plants listed in Table 1 to Table 4 were implemented. These included the Synchronous generator, the Turbine/Governor (TGOV), the Automatic Voltage Regulator (AVR), as well as Power System Stabilizer (PSS). Below are the graphic diagrams of the above components modelled in the network.

Power Plant Model
A synchronous generator standard model in PowerFactory was used to define the characteristics of the power plants and their dynamic components in the design. The power plant frame is shown in figure 4. The choice of this model is based on IEEE guide for synchronous generator modeling practice and applications in power system stability analysis [6]. In the power plant frame shown below, it is important to state that the meter bus placed to introduce voltage and frequency measurements to the power system stabiliser (PSS) input, the over-excitation limiter (OEL) and the under-excitation limiter (UEL), all situated at the left side of the power plant frame was not considered in this design and therefore does not contribute to the overall activity of the entire system. Irrespective of the type of synchronous generator and the controllers used, the power plant frame in figure 3 remains almost the same for most configurations. Hence, for any type of controller used depending on its input variables, the synchronous generator will deliver the necessary input variables for efficient operation of its controllers.

Turbine/Governor Model
A steam turbine converts the stored energy of high pressure and high temperature steam into a rotating energy. This energy is in turn converted into electrical energy by the generator whose speed is controlled by the governor [8]. In Nigeria, the heat source for the boiler supplying the steam is typically fired by Liquefied natural gas (LNG). The Turbine/Governor models used in the design were of IEEE recommendations for dynamic models of Turbine-Governor in power system studies [9]. Two models were used, one for the hydro-plant (HYGOV) and the other for the thermal plants (TGOV1).
In these two models (HYGOV and TGOV1), the operations and basic signals are the same. The basic input signals of measured frequency and electrical power are compared at the summation point (-) against their reference set values in order to decode any deviation. The result of these deviations in the frequency and power to the reference values is necessary to enable creation of the necessary primary control Droop instruction needed to be fed into the controller for valve adjustment (steam/gas open/close time) in the event of any disturbance. The signal gate Limiter, which serves as valve adjustment regulator, is also placed alongside the necessary delay constant functions considering the effect of frictional losses and are also compared with other signals like the apparent power and powerfactor from the synchronous generator to be able to effect a controlled change in the turbine input (pt) of that power plant.

Fig -5: Frame of the Thermal Turbine-Governor (TGOV1)
The important signals to the studies are shown in Table 6.

Automatic Voltage Regulator Model
Here, the choice of the Automatic Voltage Regulator (AVR_SEXS) as the voltage regulator and the excitation system used for the synchronous generator was influenced by ENTSO-E in [10].
The basic operations of the automatic voltage regulation of SEX standard is significantly the same with any other AVR device. One of its few advantages can be attributed to low number of input parameters as against many other standard models. It is important to state that the voltage input signals of OEL and UEL are not considered in this model.

Fig -6: Frame of the AVR Device (AVR_SEXS) in PowerFactory
Here, the reference voltage (Usetp) alongside any bias (Vbias), terminal voltage (ut) and the voltage output of the PSS (Upss) are compared. Any deviation at this stage is fed to the filter in the lead-lag block. The output of this filter is then fed into the excitation limiter controller. With the help of its gain, the controller output is tuned in such a way that its output signal, excitation voltage (ve/ueers), is to control the generator stator terminal voltage.

Power System Stabilizer (PSS) Model
Here, PSS is used to enhance damping of power system oscillations through excitation control. The PSS (i.e. PSS2A) standard model used in this design was influenced by the IEEE recommended practice for Excitation system models for power system stability studies [11]. The PSS2A standard Frame in Powerfactory is shown in figure 7. The Ic1-first input code, Ic2-second input code, Input base (IPB) selector: 1-Generator MVA, 0-Generator MW base). From any input selected, Signal 1 and/ Signal 2, almost the same process is followed. The selected input signal either takes the MVA or MW base as assigned to it by the IPB selector, is fed into necessary first order lag differentiators and then to the signal transducer block (T6 and T7) represented by their time constants. Again, their outputs are compared and the result fed into the Lead-Lag block which allows for ramp-tracking in the input signals. The output of the Lead-Lag block is then compared with the gain-tuned input of the Signal 2 and the result fed into the PSS controller.
The output at this stage is also fed into other necessary first and second Lead-Lag derivative and delay blocks which is responsible for the control of phase compensations. The output of this lead-Lag block serves as input to the voltage Limiter block used for excitation control to output the controlled-voltage signal input (Upss), which in turn, as an input to the AVR device, is used to add damping to the synchronous generator stator oscillations in the case of any disturbance in the network.

Ibus= YbusVbus
Where Ibus is the vector of the injecting bus currents and Vbus is the vector of bus voltages measured from the reference node. Ybus can also be referred to as the admittance matrix. The diagonal element of each node is the sum of admittances connected to it. It is also known as self-admittance given by [12]: The off-diagonal element is equal to the negative of the admittance between the nodes. It is known as mutual admittance and it is shown below.
In summary, the flow chart for the Newton-Raphson Load flow calculation algorithm is shown in figure 8.

STABILITY INVESTIGATIONS
The Stability Analysis, RMS simulation (electromechanical transient) was implemented using previously discussed control devices following analysis and results were collected during the top of Maximum Hour power flow (MH-22:00 Hours). This 22-hours analysis is chosen because it is the hours of maximum power flow at maximum load utilities.
For this study case, six (6) Buses, B'Kebbi (North-West), Osogbo NCC (South-West), New-Haven (South-East), Ikot-Ekpene (South-South), Maiduguri (North-East), including the Slack Bus, Egbin (West) were selected for the terminal voltage and frequency behaviour analysis. They were selected because of their strategic locations in the Nigerian Map.
In addition, short circuit event was created on the longest line, B'Kebbi-Kainji (310km) with a switch event of 100ms. The behaviour of this short circuit event on the transmission network was monitored on the three (3) longest lines that included, B'Kebbi-Kainji (310km), Osogbo-Ikeja West (235km) and New Haven-Ikot Ekpene (143km) lines, the above mentioned Buses in our case study as well as on the randomly selected Power Plants units, which included, the Egbin Plant (ST1-slack machine), Shiroro (411G1-hydro station), Sapele Gas GT1 (thermal station) and Asco Plant (thermal station). One of the importance of this short circuit analysis is to be able to simulate and investigate single and/ multiple faults as well as be able to check the ratings of network equipment during the planning period. Below are the results of the analysis as shown by DigSILENT PowerFactory software.

SUMMARY AND CONCLUSION
From the entire characteristic figures shown in part 5, it is clear that the voltage and frequency characteristics of the modelled dynamic components of the Nigerian transmission network resulted to expected and favourable outcomes, prior to addition of further controllers to increase fast damping during system oscillations because of transient events. This shows in a greater extent the accuracy and fitting of the standard dynamic models used in the Nigerian transmission network modelling and suggest their suitability in the future power system analysis and operational procedure follow-up of the Nigerian transmission Network. This research have succeeded in exposing the stability of the Nigerian Transmission Network. The fact that the National Control Center (NCC) of the Transmission Company of Nigeria (TCN) do not perform system dynamics is evident in the epileptic power supply that Nigeria is currently battling at any careless disturbance. The dynamic models of the power plants helped to understand the behaviour of the critical network parameters and as such will help in understanding the effect of any contingency in the network.
The importance of these dynamic models implementation is far beyond this project as it serves as the platform for all other analysis and any electrical parameter investigation that maybe of interest to the system operators, the National Electricity Regulatory Commission (NERC), the National Control Center and/ the research Academia. These can include but are not limited to Modal Analysis, further transient analysis, Contingency Analysis, short circuit single or multiple fault analysis and other investigations. These analyses are important in the Nigerian context especially during the case of load shading, generators out of operation due to faults or maintenance, integration of renewable energy sources into the Grid etc.