Load frequency controllers considering renewable energy integration in power system

Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency

Novel control design and strategy for load frequency control in restructured power systems

In restructured electric power systems, a number of generation companies and independent power producers compete in the energy market to make a profit. Furthermore, a new marketplace for ancillary services is established, providing an additional profit opportunity for those power suppliers. These services are essential since they help support the transmission of power from energy sources to loads, and maintain reliable operation of the overall system. This dissertation addresses regulation , a major ancillary service also known as the load frequency control (LFC) problem, and presents novel control designs and strategies for the LFC in restructured power systems.;A power system is an interconnection of control areas, which are operated according to control performance standards established by the North American Electric Reliability Council (NERC). LFC is a necessary mechanism in each control area because it maintains a balance between power demand and power generation while assuring compliance with NERC standards.;This dissertation first develops three new control designs that yield effective and robust load frequency control actions. All controllers developed here require only local measurements. The first control design is based on decoupling each area thru modeling of the interconnection effects of other control areas. The second control design relies on the robust H infinity theory in terms of linear matrix inequalities (LMIs). The third control design is achieved by the collaboration between genetic algorithms (GAs) and LMIs. The first two control designs result in high-order dynamic controllers. The third design requires only a simple proportional-integral (PI) controller while yielding control performance as good as those resulting from the previous two designs. Consequently, the third control design is the most preferable due to its simplicity and suitability for industry practice. Furthermore, a stability analysis method based on perturbation theory of eigenvalues is developed to assess the stability of the entire power system being equipped by the proposed controllers.;Second, to comply with NERC standards, two LFC strategies are developed to direct LFC\u27s actions. One strategy employs fuzzy logic to mimic a skillful operator\u27s actions so that all decisions are made efficiently. The other strategy treats the compliance with NERC standards as constraints while minimizing the operational and maintenance costs associated with LFC actions. Three new indices are introduced to assess economic benefits from the strategy compared to the conventional methods. Simulation is performed to demonstrate performances of all proposed methods and strategies

Load Frequency Control (LFC) Strategies in Renewable Energy‐Based Hybrid Power Systems:A Review

The hybrid power system is a combination of renewable energy power plants and conventional energy power plants. This integration causes power quality issues including poor settling times and higher transient contents. The main issue of such interconnection is the frequency variations caused in the hybrid power system. Load Frequency Controller (LFC) design ensures the reliable and efficient operation of the power system. The main function of LFC is to maintain the system frequency within safe limits, hence keeping power at a specific range. An LFC should be supported with modern and intelligent control structures for providing the adequate power to the system. This paper presents a comprehensive review of several LFC structures in a diverse configuration of a power system. First of all, an overview of a renewable energy-based power system is provided with a need for the development of LFC. The basic operation was studied in single-area, multi-area and multi-stage power system configurations. Types of controllers developed on different techniques studied with an overview of different control techniques were utilized. The comparative analysis of various controllers and strategies was performed graphically. The future scope of work provided lists the potential areas for conducting further research. Finally, the paper concludes by emphasizing the need for better LFC design in complex power system environments

Optimal fuzzy-PID controller with derivative filter for load frequency control including UPFC and SMES

A newly adopted optimization technique known as sine-cosine algorithm (SCA) is suggested in this research article to tune the gains of Fuzzy-PID controller along with a derivative filter (Fuzzy-PIDF) of a hybrid interconnected system for the Load Frequency Control (LFC). The scrutinized multi-generation system considers hydro, gas and thermal sources in all areas of the dual area power system integrated with UPFC (unified power flow controller) and SMES (Super-conducting magnetic energy storage) units. The preeminence of the offered Fuzzy-PIDF controller is recognized over Fuzzy-PID controller by comparing their dynamic performance indices concerning minimum undershoot, settling time and also peak overshoot. Finally, the sensitiveness and sturdiness of the recommended control method are proved by altering the parameters of the system from their nominal values and by the implementation of random loading in the system

Self-adaptive fuzzy-PID controller for AGC study in deregulated Power System

The aim of this paper elucidates the AGC issues in a large scale interconnected power system incorporating HVDC link under the deregulated environment. The performance of the system is degraded under the influence of abrupt load change, and parameter variation. To perceive a reliable and quality power supply, secondary robust controllers are essential. A novel self-adaptive Fuzzy-PID controller is proposed to ameliorate the dynamic performance of both the conventional PID and Fuzzy-PID controller, employed in the restructured power system. In self-adaptive Fuzzy-PID controller unlike the Fuzzy-PID controller, the output scaling factors are tuned dynamically while the controller is functioning. These three controllers are designed by enumerating different gains and scaling factors, applying a budding nature-inspired algorithm known as Wild Goat Algorithm (WGA). The superior dynamic performance of frequency and tie-line power deviation under self-adaptive Fuzzy-PID controller in comparison to its' counterparts is investigated by dispatching the scheduled and unscheduled power under different contracts such as poolco based transaction, bilateral transaction and contract violation based transaction through different tie-lines. The dynamic response under parameter variation and random load perturbation confers the robustness of the proposed controller

Load Frequency Control in Isolated Micro-Grids with Electrical Vehicles Based on Multivariable Generalized Predictive Theory

In power systems, although the inertia energy in power sources can partly cover power unbalances caused by load disturbance or renewable energy fluctuation, it is still hard to maintain the frequency deviation within acceptable ranges. However, with the vehicle-to-grid (V2G) technique, electric vehicles (EVs) can act as mobile energy storage units, which could be a solution for load frequency control (LFC) in an isolated grid. In this paper, a LFC model of an isolated micro-grid with EVs, distributed generations and their constraints is developed. In addition, a controller based on multivariable generalized predictive control (MGPC) theory is proposed for LFC in the isolated micro-grid, where EVs and diesel generator (DG) are coordinated to achieve a satisfied performance on load frequency. A benchmark isolated micro-grid with EVs, DG, and wind farm is modeled in the Matlab/Simulink environment to demonstrate the effectiveness of the proposed method. Simulation results demonstrate that with MGPC, the energy stored in EVs can be managed intelligently according to LFC requirement. This improves the system frequency stability with complex operation situations including the random renewable energy resource and the continuous load disturbances

Studies of Economics and Stability with Variable Generation and Controllable Load

This work probes several aspects of the renewable resources and controllable loads. The investigation includes the impact of wind power in bidding process in a deregulated power market, the effect of load damping elements on power system frequency stability and security, and impact of controllable load on system operation from the viewpoint of economic volatility and physical security. In the first part, new bidding models are developed under two schemes for wind generation to analyze the competition among generation companies (GENCOs) with transmission constraints considered. The proposed method employs the supply function equilibrium (SFE) to model a GENCO’s bidding strategy. The bidding process is solved as a bi-level optimization problem. An intelligent search based on Genetic Algorithm (GA) and Monte Carlo simulation (MCS) is applied to obtain the solution. This model also considers the probabilistic variability of wind output. In the second part, the effect of frequency-sensitive load on system frequency using typical system frequency response (SFR) model is investigated. Theoretic analysis based on transfer functions shows that the frequency deviation under a variable load-damping coefficient is relatively small and bounded when the power system is essentially stable; while the frequency deviation can be accelerated when the power system is unstable after disturbance. For the stable case, the largest frequency dip under a perturbation and the corresponding critical time can be derived by inverse Laplace transformation using a full model considering effect of load-damping coefficient. Further, the error in evaluating the load-damping coefficient gives the largest impact on frequency deviation right at the time when the largest frequency dip occurs. In the last part, a new demand response model is presented. It models system economic dispatch as a feedback control process and introduces a flexible and adjustable load cost as a controlled signal to adjust load response. Compared to the conventional “one time use” static load dispatch model, this dynamic feedback demand response model can adjust load to desired level in finite discrete time steps. In addition, MCS and interval mathematics are applied to describing uncertainty of an individual end-user’s response to an ISO’s expected dispatch

Control of Thermal Power System Using Adaptive Fuzzy Logic Control

Controlling thermal power systems increases the overall system efficiency and satisfies the desired requirements. In such a large system, fuel reduction of even a small percentage leads to large energy saving. Hence, power systems are gaining significant attention from engineers and scientists. In this thesis, the uncontrolled power system for single area, two area, and three area is modelled using state space representation. Frequency deviation is simulated using MATLAB and SIMULINK. PID control is added to the system to analyze the effect of conventional control on system output response. Adaptive fuzzy logic control is added to the uncontrolled system using MATLAB Fuzzy Inference System and its effect on the system output response is measured in terms of overshoot/undershoot percentage, settling time, and steady state frequency error. Effect of adaptive fuzzy logic control is analyzed on single area, two area, and three area power system. Tie-line power exchange among areas is investigated before and after implementation of PID and adaptive fuzzy logic control. For the purpose of comparison in this thesis, a conventional PID control and an adaptive fuzzy logic control is applied to two different thermal power systems. The simulations demonstrate that adaptive fuzzy logic control is proved to be more efficient and reliable than conventional PID control in power system control problem