Under Frequency Load Shedding Relays Research Articles

Optimal placement of BESS in a power system network for frequency support during contingency

In this work, a strategy is proposed for the optimal placement of a Battery Energy Storage System (BESS) in a power system network for frequency support during a power system contingency. It is an optimization algorithm that considers the best location for the integration of a BESS for a frequency support as the place that will result in a minimum rate of change of frequency (RoCoF) during a power system disturbance. The formulation (which aims at determining the minimum RoCoF during contingency) was based on the inertia constant contributions and active power injections (during contingency) from a mixed power generation sources of conventional power plants (CPPs), wind power plants (WPPs) and a battery energy storage system (BESS). Three different optimization solvers, particle swarm optimization (PSO), Fmincon MATLAB solver, and genetic algorithm (GA)) were used in solving the optimization problem for the purpose of comparing the results obtained in order to choose the minimum RoCoF value among the three optimization solvers. The proposed methodology was tested using two network models namely a modified 12-bus and 53 -bus (Western Cape) test systems each consisting of CPPs, WPPs and BESS as energy sources. Simulation results show that when BESS is placed on its optimal location of bus 61 (using the modified 53-bus Western Cape Network model) the power imbalance due to contingency was reduced to about 38 % of its maximum value of 4791 MW and consequently the system frequency nadir was improved from 49.49 Hz to 49.60 Hz. This is very necessary in order to keep the system frequency from falling beyond the limit that may activate the underfrequency load shedding relays.

Optimal operation of under-frequency load shedding relays by hybrid optimization of particle swarm and bacterial foraging algorithms

Particle Swarm (PSO) and Bacterial Foraging (BF) Optimizers are two widely used optimization techniques. A proper combination of these two algorithms would improve their search capability while minimizing their shortcomings, such as parameter dependency and premature convergence. This paper presents a hybrid optimization algorithm that combines PSO and BF (HPSBF) to ensure security and the system’s stability following faults and disturbances. The formulated objective function is claimed to be innovative and straightforward.The set objectives are to minimize the dropped load by shedding relays while maximizing the lowermost swing frequency. The optimal operation of Under-Frequency Load-Shedding (UFLS) Relays is driven by the HPSBF technique as a bounded optimization with bounds representing the limits of the system’s state variables. The viability of the HPSBF is verified against conventional-, PSO-, and BF-UFLS approaches. The standard IEEE 9-bus and IEEE 39-bus systems are exploited to examine the response of the developed UFLS techniques. The tested systems are exposed to various operational scenarios such as loss of power plants and a considerable abrupt load increase. The DigSilent power factor software is used to simulate the IEEE 9- and 39-bus systems, while MATLAB code was implemented to obtain optimal operational points for the implemented algorithms. The HPSBF accomplished the uppermost swing frequency and the lowermost quantity of the disconnected load. Furthermore, the computational times of HPSBF are equivalent to those of the PSO.

An MILP formulation for controlled islanding coordinated with under frequeny load shedding plan

As both controlled islanding and under frequency load shedding (UFLS) plans, curtail a predetermined amount of load, they must be coordinated to avoid excessive and unnecessary load shedding. In this paper, firstly an MILP formulation for controlled islanding with the purpose of determining island boundaries is presented, then a two-stage plan is proposed to coordinate the controlled islanding strategy and the UFLS plan. In the first stage, the islanding boundaries are determined using a mixed integer linear programming (MILP) model. In this stage, the set of splitting lines and the required load shedding for the controlled islanding plan are determined to achieve the minimum power imbalance over all resulted islands. However, as the UFLS relays are armed in each island, the resulted islanding strategy should be modified in the presence of UFLS relays. In the second stage, the required amount of load shedding is adjusted if the UFLS plan is not enough to make power balance in that island. The system frequency response is discretized considering the governor actions, load damping and UFLS activation. To achieve a practical controlled islanding plan coordinated with UFLS relay’s settings, a variety of operational and structural constraints are included. Also, the AC power balance equations are linearized at a given operating point. The proposed coordinated controlled islanding scheme is applied over the IEEE 118-bus test system.

A Monte-Carlo Simulation Method for Setting the Underfrequency Load Shedding Relays and Selecting the Spinning Reserve Policy in Autonomous Power Systems

This paper presents a computational method using the Monte-Carlo simulation approach for the calculation of the settings of load shedding underfrequency relays and the selection of appropriate spinning reserve policy in autonomous power systems. The method can be used for comparing alternative strategies by taking into account the amount of load to be shed and the corresponding risk for system stability. This method was applied on a system, that is based on the autonomous power system of the Greek island of Crete and the obtained results are presented and discussed.

An adaptive method for setting underfrequency load shedding relays

An adaptive scheme is proposed for determining the amount of load to be shed by underfrequency relays based on the observed initial slope of the frequency deviation. following the system separation. This initial slope contains all the information required to estimate that size of the step change in load caused by the system separation and to forecast the depth and even the approximate time of the maximum frequency dip. From this observation, the first step of load shedding can be set up adaptively, with additional steps to follow at prescribed intervals and amounts. The first step is considered the most important and is selected arbitrarily at one-half the static load shed target, with additional increments of about 0.1 per unit to be shed at 0.3 Hz increments until the dynamic load shed amount has been reached.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>