The load–frequency control (LFC) problem has been one of the major subjects in a power system. In
practice, LFC systems use proportional–integral (PI) controllers. However since these controllers are designed
using a linear model, the non-linearities of the system are not accounted for and they are incapable of
gaining good dynamical performance for a wide range of operating conditions in a multi-area power system.
A strategy for solving this problem because of the distributed nature of a multi-area power system is
presented by using a multi-agent reinforcement learning (MARL) approach. It consists of two agents in each
power area; the estimator agent provides the area control error (ACE) signal based on the frequency bias
estimation and the controller agent uses reinforcement learning to control the power system in which genetic
algorithm optimisation is used to tune its parameters. This method does not depend on any knowledge of the
system and it admits considerable flexibility in defining the control objective. Also, by finding the ACE signal
based on the frequency bias estimation the LFC performance is improved and by using the MARL parallel, computation is
realised, leading to a high degree of scalability. Here, to illustrate the accuracy of the proposed approach, a
three-area power system example is given with two scenarios.

Load–frequency control : a GA-based multi-agent reinforcement learning

In this paper, a novel energy storage method based on pumped hydropower energy storage (PHES) for a renewable energy integrated micro-grid (REMG) is proposed, and the load frequency control (LFC) for the system is studied. In a typical REMG, micro pumped storage units are built that rely on a tall building to convert energy by pumping water up to store energy and releasing the stored water to generate energy. Because of the fluctuation of renewable energy (RE) and the perturbation of the load demand, frequency deviation, and tie-line power interchange are inevitable. In this paper, the LFC controller optimization problem for the REMG is investigated, and the optimal controllers for multi-areas in the REMG are designed. To solve the optimization problem of LFC, a novel meta-heuristic algorithm called artificial sheep algorithm (ASA) is applied in the task of LFC optimization. In the experiments, RE scenarios of different seasons, the impact of PHES, and the control robustness are studied. The results not only prove the feasibility of the proposed REMG but also show the effectiveness of the optimized controllers in maintaining frequency stability under various conditions.

Load Frequency Control of a Novel Renewable Energy Integrated Micro-Grid Containing Pumped Hydropower Energy Storage

State-of-the-art of controllers and soft computing techniques for regulated load frequency management of single/multi-area traditional and renewable energy based power systems

https://www.econstor.eu/bitstream/10419/243599/1/1666090360.pdf

Load frequency controllers considering renewable energy integration in power system

The electrical power system has experienced several changes during the last decade, raised by continuously increasing load demand, rapid depletion in fossil fuels, and newly electrical deregulation policy. In the past, numerous review literatures has been published in the field of Load Frequency Control (LFC), which deals with different and recent control strategies for the successful operation of the power system. Moreover, due to changes in lifestyle, increasing load demand, expansion of industrialization, and environmental issues, Renewable Energy Sources (RES) integration becomes the obvious adaptive choice. Since generation from RES is stochastic in nature and depends upon the weather condition and other aspects at every instant of time. Therefore, high penetration may reflect specific issues regarding voltage instability, frequency stabilization, and reliability obstruction. Hence this issue has been covered effectively in this review work. Furthermore, the work precisely summarized and briefly explained the different scenarios of Energy Storage (ES), micro-grid and Flexible AC Transmission System (FACTS) to explore the possible solutions and future aspects. The merit and demerit of different controllers are also investigated with the help of a comparison's tables and also some other analytical comparisons. The overall study examines an in-depth review of recent technical core aspects for LFC based on classical and modern power system which involves the non-linear model, controller design parameters, soft-computing application, attributes of Load forecasting, as well as integration of RES in a deregulated environment. This effective, comprehensive literature survey is very helpful for researchers to bridge the gap between recent development, implementation, challenges and future trends of RES in LFC. 

A literature survey on load frequency control considering renewable energy integration in power system: Recent trends and future prospects

This paper proposes a distributed model predictive control based load frequency control (MPC-LFC) scheme to improve control performances in the frequency regulation of power system. In order to reduce the computational burden in the rolling optimization with a sufficiently large prediction horizon, the orthonormal Laguerre functions are utilized to approximate the predicted control trajectory. The closed-loop stability of the proposed MPC scheme is achieved by adding a terminal equality constraint to the online quadratic optimization and taking the cost function as the Lyapunov function. Furthermore, the treatments of some typical constraints in load frequency control have been studied based on the specific Laguerre-based formulations. Simulations have been conducted in two different interconnected power systems to validate the effectiveness of the proposed distributed MPC-LFC as well as its superiority over the comparative methods.

A distributed model predictive control based load frequency control scheme for multi-area interconnected power system using discrete-time Laguerre functions.

With increasing wind farm, solar farm, and pump storage plant integrations, intense frequency fluctuation of the pumped storage hydro unit (PSHU) under the no-load running condition, which is cause...

Zhongdong Qian

Papers

A distributed model predictive control based load frequency control scheme for multi-area interconnected power system using discrete-time Laguerre functions.

A parameter adaptive identification method for a pumped storage hydro unit regulation system model using an improved gravitational search algorithm