J.A. Laghari

This paper presents a new under-frequency load
shedding technique based on the combination of random and
fixed priority of loads. It has been observed that placing all of
the loads in the distribution system with fixed priority results
in un-optimum load shedding. On the other hand, designing the
load priority with a combination of random and fixed priority
provides the technique with some sort of flexibility in achieving the
optimal load shedding. The validation of the proposed scheme on
different scenarios proves that the proposed technique is capable
of achieving the optimal load shedding and recovering frequency
to nominal value without any overshoot.

Accurate and fast islanding detection of distributed generation is highly important for its successful operation
in distribution networks. Up to now, various islanding detection technique based on communication,
passive, active and hybrid methods have been proposed. However, each technique suffers from
certain demerits that cause inaccuracies in islanding detection. Computational intelligence based techniques,
due to their robustness and flexibility in dealing with complex nonlinear systems, is an option
that might solve this problem. This paper aims to provide a comprehensive review of computational
intelligence based techniques applied for islanding detection of distributed generation. Moreover, the
paper compares the accuracies of computational intelligence based techniques over existing techniques
to provide a handful of information for industries and utility researchers to determine the best method
for their respective system.

The interconnection of distributed generation (DG) into distribution networks is undergoing a rapid global
expansion. It enhances the system’s reliability, while simultaneously reduces pollution problems
related to the generation of electrical power. To fully utilize the benefits of DGs, certain technical issues
need to be addressed. One of the most important issues in this context is islanding detection. This paper
presents a new islanding detection technique that is suitable for multiple mini-hydro type DG units. The
proposed strategy is based on the rate of change of reactive power and load connecting strategy to detect
islanding within the system. For a large power mismatch, islanding is detected by rate of change of reactive
power only. However, for a close power mismatch, the rate of change of reactive power initiates a
load connecting strategy, which in turn alters the load on the distribution network. This load variation
in the distribution network causes a variation in the rate of change of reactive power, which is utilized
to distinguish islanding and other events. The simulation results show that the proposed strategy is effective
in detecting islanding occurrence in a distribution network.

The power system blackout history of last two decades is presented.Conventional load shedding techniques, their types and limitations are presented.Applications of intelligent techniques in load shedding are presented.Intelligent techniques include ANN, fuzzy logic, ANFIS, genetic algorithm and PSO.The discussion and comparison between these techniques are provided.Recent blackouts around the world question the reliability of conventional and adaptive load shedding techniques in avoiding such power outages. To address this issue, reliable techniques are required to provide fast and accurate load shedding to prevent collapse in the power system. Computational intelligence techniques, due to their robustness and flexibility in dealing with complex non-linear systems, could be an option in addressing this problem. Computational intelligence includes techniques like artificial neural networks, genetic algorithms, fuzzy logic control, adaptive neuro-fuzzy inference system, and particle swarm optimization. Research in these techniques is being undertaken in order to discover means for more efficient and reliable load shedding. This paper provides an overview of these techniques as applied to load shedding in a power system. This paper also compares the advantages of computational intelligence techniques over conventional load shedding techniques. Finally, this paper discusses the limitation of computational intelligence techniques, which restricts their usage in load shedding in real time.

Mini hydro power plants (MHPP) are gaining attraction as a cost effective source for rural electrification in developing countries due to its environmental friendly operation. These MHPP plants suffer from the speed control problem due to continuous load variation. PID controllers fail to provide optimum speed control due to its limitation of parameter tuning. Alternatively, Fuzzy logic control is commonly used for implementing intelligent control for the nonlinear system. This paper presents a new fuzzy logic based governor for frequency / speed regulation of MHPP for implementation in distribution network. For verification, the response of load frequency control using fuzzy based governor and PID based governor is compared. The simulation results show that fuzzy based governor ensures robust control by improving the frequency response as well as dynamic response in comparison to PID based governor. Furthermore, fuzzy based governor enables the generator to continuously supply power even at 25% load variation whereas generator with PID based governor fails to supply power even at 20% load variation.

High penetration of distributed generation (DG) in distribution level has open an opportunity for islanding operation of distribution networks. Through proper islanding operation, the reliability of the system can be improved by continuously supplying power from DG. However, an effective protection schemes for an islanded network are still an issue to be solved. Specifically to balance DG generation and load demand in order to maintain system frequency. Hence, an effective underfrequency load shedding scheme is required for an islanded distribution network which is not as strong as the grid. This paper presents a new under-frequency load shedding scheme for an islanded distribution network. A combination of adaptive under-frequency load shedding and state estimation is proposed for efficient and precise load shedding scheme. In this proposed method, overload is anticipated by utilizing an adaptive underfrequency load shedding scheme. Meanwhile, State estimation is used to estimate the load value. Finally, the estimated value of overload will be shed according to the estimated value of each bus demand.

When tripping events or overloading cases occur in power system, load shedding scheme operates to shed some load and stabilize the
frequency. However, amount of load to be shed greatly depends on, how fast governor can utilizeDG spinning reserve. This paper compares the
response of DG with fuzzy based governor and PID based governor in utilization of DG spinning reserve. The simulation results show that DG with
fuzzy based governor utilizes spinning reserve more quickly and requires lesser load to be shed than a DG with PID based governor.

Implementations of mini hydro schemes with conventional hydraulic, electrical equipment's and controllers have proven very expensive and uneconomical. Many developing countries that are in need of rural electrification have encountered economical problem when setting up these mini hydro schemes. To address this problem, alternative options and new designs of these equipment's have been explored by many researchers around the world. The application of these new designs would reduce the overall cost of mini hydro development and would help in making it a cost effective technology. These new designs will also help developing countries to provide electricity to rural areas or remote regions where interconnection of transmission line from the electrical grid is uneconomical. The new designs can also be an enabling factor in boosting up electricity generation using a renewable energy source. This paper provides survey of all these alternative options and new designs in the controller, hydraulic turbine and generators that have been implemented in different countries of the world.

This paper implements the State Space Search Method (SSSM) in polar coordinate form to calculate low voltage solution and Maximum Loading Point of system in ill conditioned system. SSSM modifies the direction of state variable (buses voltage and phase) by using optimal multiplier in order to converge load flow equations in ill conditioned system. The privilege of SSSM emerges in the keeping dimension of load flow jacobian matrix constant. While another method such as continuation and homotopy methods change the framework of jacobian matrix based on predictor and corrector in term of increasing load demand. Indeed, the calculation process of SSSM is based on standard Newton Raphson load flow method. The validation of SSSM is shown by the testing IEEE test systems of 14 and 30 in well and maximum loading point as ill-conditioned systems.

One of the challenge in islanding operation is to maintain frequency stability when generation is less than demand. This paper presents a new Under-Frequency Load shedding scheme for an islanded distribution network. The scheme is based on an adaptive and intelligent load shedding techniques. This proposed scheme is able to conserve power system collapse even for large disturbance and events in the system. The proposed scheme is evaluated through simulation in PSCAD/EMTDC software. A distribution network connected with mini-hydro generation in Malaysia is chosen for the test. Various test scenarios show the effectiveness of the proposed load shedding scheme to shed optimum load.

In islanding mode, system frequency is severely disturbed due to imbalance between generation and load demand resulting in overloading or loss of generation cases. In order to cope with these events, under-frequency load shedding scheme (UFLS) is applied to stabilize the frequency. This paper presents an intelligent under frequency load shedding scheme implemented on mini-hydro operating in islanded mode. The proposed UFLS scheme consists of a fuzzy logic load shedding controller (FLLSC) with load shedding controller module (LSCM). The FLLSC by measuring frequency and rate of change of frequency estimates the amount of load to be shed. The LSCM sheds the load estimated by FLLSC. This scheme is tested for event based and response based cases. The results have shown that proposed load shedding scheme successfully estimates the amount of load to be shed and stabilizes the frequency for these cases.

IEEE working group on prime movers recommended different governors for hydro power plants. This paper presents the comparative studies on all of these governors for mini hydro power plants (MHPP) operating in parallel and supplying power to distribution network. The purpose of this study is to find their suitability in controlling the frequency of the system for large load variations in an islanded distribution network. The mini hydro power plant with its distribution network is modeled in PSCAD software. The mechanical hydraulic governor, electro hydraulic PID governor, electro-hydraulic PI governor and Enhanced governor are evaluated one by one to find the best response in controlling frequency when disturbance occurs. The load variations from 10% to 50% both addition and reduction are tested for every governor. This study will assists in selecting a particular governor for isolated mode, interconnected mode as well as for islanding mode of operation in distributed generation.

The frequency of power system is very sensitive to load changing when operating in
islanded mode. This may causes overloading or loss of generation cases. Under-Frequency Load
Shedding (UFLS) Scheme is commonly applied to stabilize the frequency during these cases.
Conventional UFLS scheme operates successfully in interconnected grid system and may not work
well when applied to DG based system operating in islanded mode. This paper presents a new
fuzzy logic based under- frequency load shedding scheme implemented on mini hydro type-DG
operating in islanded mode.
The proposed strategy is based on frequency, rate of change of frequency and load prioritization.
In proposed UFLS scheme, a fuzzy logic load shedding controller (FLLSC) with Load Shed
Controller Module (LSCM) is modelled. FLLSC measures amount of load to be shed and LSCM
shed the respective load to stabilize frequency. The proposed scheme is validated on different
event-based and response-based cases. Simulation results show that proposed scheme is effective
in shedding optimal number of loads while stabilizing the frequency.