Multi-area System Research Articles

AGC of a multiarea system incorporating accurate HVDC and precise wind turbine systems

AGC of a multiarea system incorporating accurate HVDC and precise wind turbine systems

A novel cascaded PID controller for automatic generation control analysis with renewable sources

Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control &#x0028 AGC &#x0029 with diverse renewable sources and a modified-cascaded controller are presented in the paper. Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution &#x0028 hITLBO-DE &#x0029 algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative &#x0028 PID &#x0029, integral double derivative &#x0028 IDD &#x0029 and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change. The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5&#x0025 of the connected load and robustness analysis is shown by modifying essential factors simultaneously by &#x2213 30&#x0025. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.

Decentralised optimal dispatch of multi‐area power systems based on non‐linear value‐function approximation

In recent years, the use of interconnected multi-area systems has increased significantly. To operate these systems efficiently, a proper coordination approach among different areas is required. With this context, a novel decentralised optimal dispatch algorithm is proposed in this study. The centralised economic dispatch model is decoupled into a series of sub-problems for different areas, allowing the independent decision of each area without a central operator. The detailed information of each area is not required for information exchange. To better estimate the impact of each area's decision on other areas, the approximate value functions of the tie-line powers are added into the local objective function of the sub-problem. This technique makes the decentralised solution of the proposed algorithm more explicit and rational compared with most existing distributed algorithms. Besides, the proposed technique does not require parameter tuning and has good convergence performance. Numerical simulations on several test systems and a real power system demonstrate that the proposed algorithm is favourable in terms of accuracy, adaptability, and computational efficiency.

Automatic generation control of a solar thermal and dish‐stirling solar thermal system integrated multi‐area system incorporating accurate HVDC link model using crow search algorithm optimised FOPI Minus FODF controller

This article demonstrates the automatic generation control of a multi-area system incorporating various sources. Area-1 and area-2 consist of thermal and parabolic trough solar thermal plant (PTSTP) of fixed and random solar insolation, respectively, and area-3 comprises of thermal and realistic dish-stirling solar thermal system units. A maiden effort has been made to use a fractional order (FO) proportional-integral minus FO derivative with filter coefficient (FOPI-FODF) controller as a secondary controller. The controller gains are optimised using a novel algorithm called crow search algorithm. Comparisons of system dynamic response with and without renewable energy sources for FOPI-FODF, and for some commonly used integer order and FO controller's reveals the better performance of FOPI-FODF controller. A study comparing both fixed and random solar insolation in PTSTP of different areas have been tested. An accurate high-voltage direct current (AHVDC) line model is designed using inertia emulation strategy and is placed instead of AC tie line, and with parallel AC tie lines resulting in better system dynamic performances than AC tie line alone. The selection of the optimum location of AHVDC line in parallel AC tie line exposes the AHVDC line connected with the area where the system is disturbed.

Effect of inertia heterogeneity on frequency dynamics of low‐inertia power systems

Based on fundamental dynamic simulation principles and illustrative case studies, this study aims to identify key changes in the dynamic behaviour of the system due to the high penetration of renewable energy sources (RES) affecting frequency dynamics and provide guidelines for performing frequency stability analysis in low-inertia power systems with a large penetration of RES. First, a critical comparison of the frequency responses obtained using a system equivalent model and a detailed dynamic model following an active power disturbance are presented. It is then demonstrated, using detailed dynamic models of two multi-area systems, such that when the proportion of RES prevails over the share of synchronous generator (SG), the dynamic coupling among areas (even separated by short-medium length lines) reduces and the inertia of the system should be considered as heterogeneous instead of a global parameter. Following this, the study discusses how frequency dynamics may be strongly and complexly affected by the physical characteristics of converter-connected generation leading to increased frequency and voltage interactions when the proportion of converter connected RES becomes greater than SG. The resulting changes in the system's dynamic behaviour due to frequency and voltage interactions can increase the actual active power imbalance size following a credible contingency so that careful considerations to protect the system against an excessively high rate of change of frequency should be made. In order to evaluate the extent of this change in system dynamic behaviour, an appropriate dynamic model of the network should be used with adequate multi-area representation of RES and loads.

PID controller design for interval load frequency control system with communication time delay

In load frequency control (LFC), the data from measurements sensors are transmitted from far-off remote terminal units (RTUs) to the controlling center and control signals are transmitted from the controlling center to the plant location. These transmissions of various signals are possible via communication channels which are characterized by constant delays. Modern day power systems are quite complex in the present deregulated environment. This complexity has been further enhanced by the inherent delay introduced by the communication channels. Because of the communication delay, the conventional load frequency control design techniques give unacceptable performance. Further, in case of severe delay, the load frequency control system may become unstable. In view of this, a proportional–integral–derivative (PID) controller is designed using stability boundary locus (SBL) approach for interval single area power system with non-reheated thermal turbine and reheated thermal turbine having communication delay and then the proposed approach is validated on the multi-area IEEE 39-bus New England test system. The simulation results indicate the efficacy of the proposed methodology.

A New Model to Simulate Local Market Power in a Multi-Area Electricity Market: Application to the European Case

The work presented in this article proposes an original method that models the medium-term market equilibrium under imperfect competition circumstances in multi-area electricity systems. It provides a system analysis considering multiple market splitting possibilities, where local market power may appear according to the status of the interconnections. As a result of new policies and regulations, power systems are increasingly integrating the existing electricity markets in unified frameworks. The integration of electricity markets poses highly challenging tasks due to the uncertainty that comes from the agents’ strategic behaviors which depend on multiple factors, for instance, the state of the interconnections. When it comes to modeling these effects, the purpose is to identify each strategy by using conjectured-price responses that depend on the different states of the system. Consequently, the problem becomes highly combinatorial, which heightens its size as well as its complexity. Therefore, the purpose of this work’s methodology is the reduction of the possible network configurations so as to ensure a computational tractability in the problem. In order to validate this methodology, it has been put to the test in a realistic and full-scale two-year operation planning model of the European electricity market that consists of a group of nine countries.

Application of diverse FACTS in AGC of multi-area interconnected energy systems

This article presents the simple and effective control design for active power regulation of modern energy delivery system. As an energy delivery system experiences the demand changes as per the demand of the modern energy users due to which the system frequency is highly troubled and fluctuating. To balance such demand changes and to stable the system occurrence fluctuations, the thyristor control phase shifter (TCPS) in synchronisation with super conducting magnetic energy storage (SMES) or TCPS in coordination with capacitive energy storage (CES) based model predictive control (MPC) technique are proposed. SMES-SMES and CES-CES configurations are also tested for energy delivery system. The effectiveness of the proposed system regulator design are guaranteed by analyzing the transient system performance under varying load pattern, sinusoidal load change and for system non-linearities. A comparative performance analysis between TCPS-SMES, TCPS-CES, SMES-SMES and CES-CES based MPC of energy system are tested and presented.

Application of diverse FACTS in AGC of multi-area interconnected energy systems

This article presents the simple and effective control design for active power regulation of modern energy delivery system. As an energy delivery system experiences the demand changes as per the demand of the modern energy users due to which the system frequency is highly troubled and fluctuating. To balance such demand changes and to stable the system occurrence fluctuations, the thyristor control phase shifter (TCPS) in synchronisation with super conducting magnetic energy storage (SMES) or TCPS in coordination with capacitive energy storage (CES) based model predictive control (MPC) technique are proposed. SMES-SMES and CES-CES configurations are also tested for energy delivery system. The effectiveness of the proposed system regulator design are guaranteed by analyzing the transient system performance under varying load pattern, sinusoidal load change and for system non-linearities. A comparative performance analysis between TCPS-SMES, TCPS-CES, SMES-SMES and CES-CES based MPC of energy system are tested and presented.

Coordinated tuning of controller-parameters using symbiotic organisms search algorithm for frequency regulation of multi-area wind integrated power system

Presently, the integration of renewable energy into existing power system to cater increasing power needs is a growing trend. Wind energy is one of the prominent utilized renewable sources. However, the generation level of integrated wind energy significantly affects the frequency characteristics of entire system. Further, if the control scheme of wind systems are not properly working then this situation may deteriorate the frequency characteristics of whole system. Therefore, it is indispensable to tune the parameters of controllers of existing and wind systems in proper coordination so as to improve the frequency characteristics of the system. Consequently, in this work, a coordinated tuning of parameters of controllers to improve frequency characteristics of a multi-area interconnected thermal system in presence of doubly-fed induction generator (DFIG) based wind generation is presented. A widely used two-area non-reheat thermal interconnected system is simulated having its one area integrated with DFIG based wind generation. The parameters of controllers of thermal and wind systems are coordinately tuned using symbiotic organisms search (SOS) algorithm. Different design objectives are framed to achieve improved frequency characteristics of entire system. The considered objectives are combined together by proper assignment of weights using analytic hierarchy process to form a single objective function. Several test cases with diverse disturbances under different wind penetration levels are conducted to test the performance of system with SOS based controllers. To further assess the effectiveness of proposed controllers, other controllers using differential evolution (DE), elephant herding optimization (EHO), particle swarm optimization (PSO) and teaching-learning-based optimization (TLBO) are also designed and comparatively tested under the considered cases.

Utilisation of plug‐in electric vehicles for frequency regulation of multi‐area thermal interconnected power system

The application of plug-in electric vehicles (PEVs) is assumed to be wide in power system in regulating the system frequency in the near future. This paper provides an aggregate model of an interconnected multi-area thermal system with the incorporation of PEVs for frequency control in each of the three areas. Two degree of freedom proportional–integral–derivative (2DOF-PID) controller has been utilised for robust secondary control in all the three control areas. An optimisation technique inspired by nature named as wind-driven optimisation (WDO) technique is employed to decide the optimal values of the controller gains. The effectiveness of WDO optimised 2DOF-PID controller is verified by performing various comparative analysis with conventional PID controller under nominal system condition and random loading condition. An analysis has also been carried out to evaluate the system performance with variation in state of the integrated PEVs. The impact of introducing PEVs in the system in frequency regulation has been vigorously studied under different system conditions such as nominal, random loading condition, and simultaneous perturbation in two and three areas to testify their advantages. The comparisons reveal that with the integration of PEVs in the system, the system dynamics gets enhanced to a large extent.

Robust type-2 fuzzy fractional order PID controller for dynamic stability enhancement of power system having RES based microgrid penetration

The increased penetration of renewable energy sources (RES) based microgrid (MG) to the power system can affect the system stability due to the difference in dynamic characteristics of this kind of MG from the conventional generators. The reduction in system inertia caused by these power electronics interfaced renewable power generations introduces a negative effect in the dynamic stability of the system and may cause ensuing instability problems. On the other hand, power injection of RES based MG improves the damping performance with the reduction of transmission line congestion and power loss. Thus it becomes imperative to analyze the new dynamic stability concerns and control performance of a power system in the context of increased MG penetration. This study thoroughly investigates the impact of RES based MG penetration on the dynamic stability and control of a multi-machine multi-area system under varying operating conditions. The design of a novel type-2 fuzzy fractional order PID based power system stabilizer (PSS) using a meta-heuristic hybrid algorithm is presented in this paper for improving the electromechanical oscillation damping performance of the power system to enhance the dynamic stability. The large bandwidth, memory effect and flat phase contribution in the frequency response of fractional-order PID controllers are exploited to make the controller perform well against a wide range of system uncertainties in the presence of an MG. First, the parameter tuning problem of the type-2 fuzzy fractional order PID controller is transformed to an optimization problem that is solved using a hybrid algorithm by combining a dynamic genetic algorithm (DGA) with a bacteria foraging algorithm (BFA). The capability of the proposed controller in damping the low-frequency oscillations in the system with various MG penetration ratios is assessed through non-linear time-domain simulations and some performance indices under different disturbances and operating conditions.

Decentralized optimal multi-area generation scheduling considering renewable resources mix and dynamic tie line rating

Electrical power networks usually consist of multi-area systems, which are connected by tie lines. Dynamic economic/environmental dispatch of multi-area approaches are used to schedule such networks. The goal of multi-area scheduling is determining the optimal operation of generation units and the tie line power flow in a certain period by minimizing environmental constraints. Such operation problem is limited by technical constraints of thermal generation units, tie line constraints, and transmission losses. A major limitation of multi-area economic/environmental dispatch problem is the capacity of tie lines. The worst scenario of weather condition is generally employed to set this capacity. This value is called static line rating (SLR). However, the SLR is less than the real-time capacity of overhead line. The capacity of overhead line can be determined by estimation of weather condition data for better utilization of overhead lines. This value is called dynamic line rating (DLR). In this paper, a decentralized methodology is proposed for optimal scheduling generation units taking into consideration environmental constraint, dynamic line rating, wind power generations; compressed air energy storage and power pool market. The ε-constraint approach is applied to solve proposed dynamic economic/environmental dispatch of multi-area model. In addition, a fuzzy satisfying technique is used to select the best compromise solution. An interconnected, multi-area power system with cross-border trading in the presence of wind power uncertainty and the storage unit is considered for evaluating the proposed method. The proposed decentralized approach is based on the integrated simplicial decomposition method (SDM), the nonlinear block Gauss-Seidel (GS) method and the augmented Lagrangian method (ALM) (SDM-GS-ALM) decomposition algorithm, because we need to schedule a multi-area network without central operation intervention.

Design of a proportional-integral-derivative controller for an automatic generation control of multi-area power thermal systems using firefly algorithm

Essentially, it is significant to supply the consumer with reliable and sufficient power. Since, power quality is measured by the consistency in frequency and power flow between control areas. Thus, in a power system operation and control, automatic generation control &#x0028 AGC &#x0029 plays a crucial role. In this paper, multi-area &#x0028 Five areas: area 1, area 2, area 3, area 4 and area 5 &#x0029 reheat thermal power systems are considered with proportional-integral-derivative &#x0028 PID &#x0029 controller as a supplementary controller. Each area in the investigated power system is equipped with appropriate governor unit, turbine with reheater unit, generator and speed regulator unit. The PID controller parameters are optimized by considering nature bio-inspired firefly algorithm &#x0028 FFA &#x0029. The experimental results demonstrated the comparison of the proposed system performance &#x0028 FFA-PID &#x0029 with optimized PID controller based genetic algorithm &#x0028 GA-PID &#x0029 and particle swarm optimization &#x0028 PSO &#x0029 technique &#x0028 PSO-PID &#x0029 for the same investigated power system. The results proved the efficiency of employing the integral time absolute error &#x0028 ITAE &#x0029 cost function with one percent step load perturbation &#x0028 1 &#x0025 SLP &#x0029 in area 1. The proposed system based FFA achieved the least settling time compared to using the GA or the PSO algorithms, while, it attained good results with respect to the peak overshoot &#x002F undershoot. In addition, the FFA performance is improved with the increased number of iterations which outperformed the other optimization algorithms based controller.

Adaptive deep dynamic programming for integrated frequency control of multi-area multi-microgrid systems

To reduce the frequency deviation of a multi-area multi-microgrid system, a framework of integrated frequency control is designed in this paper, which can replace load frequency control (LFC) and generation command dispatch (GCD).Then an adaptive deep dynamic programming (ADDP) scheme is proposed for the integrated frequency control. The ADDP contains three deep neural networks, i.e., deep prediction neural network, deep critic neural network and deep action neural network. Deep prediction neural network is applied to predict the next state of the multi-area multi-microgrid system from the previous states and the previous actions. Deep critic neural network is employed in the evaluations of the performance of the deep action neural network. Deep action neural network is introduced to simultaneously provide generation commands for all the LFC units in the multi-area multi-microgrid system. The ADDP is compared with other 157 algorithms under six case studies, i.e., basic situation, plug-and-play, communication failure, all-day long disturbance, time-varying topology and parameters varying. The other 157 algorithms consist of adaptive dynamic programming and 156 combined algorithms, which combined with 12 control algorithms for the controller of LFC and 13 optimization algorithms for GCD. Simulation results verify the effectiveness and superiority of the ADDP for integrated frequency control of a multi-area multi-microgrid system.

Performance Assessment of Fuzzy Logic Controller for Load Frequency Control in multi source multi area system

This article confers the performance of Fuzzy logic controller for Load Frequency Control (LFC) in multi-source multi area power system .The suggested multi area systems are studied for various operating load conditions to realize the deviations found in system frequency and the interchange power through tie-line. The distinct energy sources include hydro, thermal, wind and diesel power plants. The system models are compared for the conventional PI controller and suggested fuzzy logic controller. It is remarked from the simulation results that the proposed fuzzy logic controller contributes superior dynamic response over conventional controller.

Continuation Power Flow Model for Interconnected Systems Considering the Electricity Market Influence and Its Corresponding Distributed Algorithm

The existing continuation power flow (CPF) methods, which mainly focus on regional independent systems, are not suitable for multi-area interconnected bulk systems in the electricity market environment. These existing CPF models cannot simulate the control behaviors of active/reactive power exchange among subsystems, and the corresponding CPF algorithms cannot satisfy the requirements of data sharing. This study presents a novel CPF model and its corresponding distributed algorithm for interconnected systems in which the influence of the electricity market is considered. This CPF method has the following unique features: 1) Regarding the bilateral power trading contracts (BPTCs) among regional subsystems, the nonlinear constraint equations of the directional trading active power via the interface are derived, and a multi-balancing machine strategy is introduced for realizing the active power balance of each subsystem. 2) Based on the simulation of the constant-voltage control behavior of the pilot buses in the regional automatic voltage control (AVC) system, the constant-voltage control behavior of the boundary buses of the tie-lines is further simulated to realize the reactive power balance among the regional subsystems. 3) According to the characteristics of the proposed CPF model, a novel distributed CPF algorithm based on block matrix computations is presented for realizing the decomposition and coordination calculation of multiple regional subsystems. This distributed algorithm preserves the precision and convergence of integrated CPF algorithms and has an advantage in terms of the calculation speed. The performance of the proposed CPF model and distributed algorithm is demonstrated via case studies and comparative analyses.

Stability Improvement in Grid Connected Multi Area System using ANFIS Based SVC Controller

Stability Improvement in Grid Connected Multi Area System using ANFIS Based SVC Controller

A Transformation-Based Multi-Area Dynamic Economic Dispatch Approach for Preserving Information Privacy of Individual Areas

As the growing interconnection of regional electricity grids and the large-scale integration of renewable energy demand for effective coordination among multiple areas, the multi-area dynamic economic dispatch (MA-DED) problem has been studied for exploring coordinated optimal operations to achieve overall energy security and economic efficiency. However, due to political and technical challenges, a centralized solution to MA-DED is unlikely to be practically feasible. In turn, decomposition schemes have been applied for solving MA-DED in a distributed manner so as to avoid disclosing commercially sensitive information of individual areas to others. In recognizing computational challenges of distributed approaches, this paper discusses a transformation-based MA-DED approach, which masks each area’s private information in the objective and constraints of MA-DED by privately generated and held random matrices. Strategies of using additional slack variables and redundant constraints are also discussed to further disguise system scale of each area from being disclosed. More importantly, optimal solutions to the original MA-DED problem, including tie-line power flows, dispatches of generators and loads, and locational marginal prices, can be retrieved from solutions of the transformed problem. Numerical studies show effectiveness of the proposed approach for guaranteeing the same optimal MA-DED solution, while preserving information privacy of individual areas. Moreover, the proposed approach presents significant computational benefits over distributed approaches, especially for multi-area systems with larger numbers of tie-lines and more complicated connection topologies of areas.

Improved-salp swarm optimized type-II fuzzy controller in load frequency control of multi area islanded AC microgrid

Abstract The present article deals with load frequency control (LFC) in an islanded two area AC microgrid (MC) system. In this study the proposed two area MG system comprises different micro sources including Micro-turbine (MT), Diesel engine generator (DEG) and Fuel Cells (FC) which are primarily responsible for balancing load and power generation in an interconnected system. MG in grid-connected mode has lower possibility of frequency control problem due to active presence of utility grid. Whereas MG in islanded mode faces huge frequency control problem due to dynamic nature of different renewable energy sources (RES) and different uncertainties like wind power fluctuations, disturbances in solar irradiation power, dynamics in applied load and system parameters (damping coefficient & Inertia constant). In regard to this the present article proposes a robust type-II fuzzy PID controller to create secondary frequency control loop for maintaining both frequency and tie-line power to their nominal values under different uncertainties. For performance study, the proposed type-II fuzzy PID controller performances are compared with type-I fuzzy controller, PID and PI controllers. To obtain optimal gain values of above controllers, a meta-heuristic improved-salp swarm optimization (I-SSO) algorithm has been implemented and proposed I-SSO technique performances are compared with original SSO, Particle swarm optimization (PSO) and Genetic Algorithm (GA) techniques. Finally it is observed from different performance analysis that proposed I-SSO tuned type-II fuzzy controller exhibits superior performances for load frequency control in multi-area islanded AC microgrid system under different uncertainty conditions.