Mohammad Moradzadeh

Voltage Coordination in Multi-Area Power Systems via Distributed Model Predictive Control

This paper proposes a coordination paradigm for properly coordinating local control actions, taken by many communicating control agents (CAs), in order to maintain multi-area power system voltages within acceptable bounds. The proposed control scheme is inspired by distributed model predictive control (DMPC), and relies on the communication of planned local control actions among neighboring CAs, each possibly operated by an independent transmission system operator (TSO). Each CA, knowing a local model of its own area, as well as reduced-order QSS models of its immediate neighboring areas, and assuming a simpler equivalent PV models for its remote neighbors, performs a greedy local optimization over a finite window in time, communicating its planned control input sequence to its immediate neighbors only. The good performance of the proposed real-time model-based feedback coordinating controller, following major disturbances, is illustrated using time-domain simulation of the well-known realistic Nordic32 test system, assuming worst-case conditions.

A hybrid framework for coordinated voltage control of power systems

Modeling and simulation of increasingly complex power systems is becoming more important for design, implementation and validation of power system on-line management. Current special-purpose tools are generally weak in the sense that they are mostly block-oriented and thus demand a huge amount of manual rewriting to get the equations into explicit form. Moreover, modification and examination of their encapsulated component models is very time-consuming and often practically impossible. This paper describes an efficient hybrid framework for modeling and simulation of power systems in the interest of coordinated voltage control and stability analysis using Modelica as a general-purpose object-oriented language. The proposed hybrid framework has been tested on a 12-bus power system. Simulation results show that the interaction between continuous dynamics of the power system and hybrid automata representing the discrete logical controllers and also nonlinear behavior of load dynamics can easily be studied in the proposed framework. On the other hand, the high speed of the simulator allows any coordinated control strategy to be effectively verified as countermeasure to arrest voltage collapse.

Multi-objective optimization for environomic scheduling in microgrids

Microgrids are small-scale power systems including distributed generation (DG) units, storage devices and controllable loads, and can operate either connected or isolated from the utility grid. Ensuring an efficient, reliable, economic and environmentally friendly microgrid operation, an environomic power dispatch system is needed. In this paper, a formulation of an environomic scheduling approach in microgrids is proposed using multi-objective decision making method. The application aims to fulfill the time-varying energy demand while minimizing the costs and emissions of the internal production and imported energy from the utility grid. Operational constraints such as generator limits, operation and maintenance costs and the intermittency renewable energy sources (RES) will be satisfied. A representative microgrid structure, including measurement data, is studied as an example and some simulation results are presented to demonstrate the performance of the environomic scheduling approach.

Congestion-induced wind curtailment mitigation using energy storage

Allowing the connection of additional renewable energy sources (RES) in areas with limited transmission capacity is becoming of a serious concern. Building new transmission lines only provides a long-term solution to cope with this issue due to the fact that it takes much longer time (up to 5-10 years) compared to time needed to build new wind farms (about 1 year). Storage is proven to be an effective solution to make maximal use of existing grid infrastructures in the short-term. This paper proposes a cost-benefit optimization formulation for optimally sizing the storage in a wind-storage system which is connected to an external spot market via limited transmission lines. A small test system is studied in order to find the optimal size of storage to avoid congestion by allowing revenue to be generated only via reducing the congestion-induced wind curtailment. Additional revenue streams can be also included to maximize the monetary value of the wind-storage system.

Day-ahead electricity price forecasting using WPT, GMI and modified LSSVM-based S-OLABC algorithm

Electricity price forecasting has nowadays become a significant task to all market players in deregulated electricity market. The information obtained from future electricity helps market participants to develop cost-effective bidding strategies to maximize their profit. Accurate price forecasting involves all market participants such as customer or producer in competitive electricity markets. This paper presents a novel hybrid algorithm to forecast day-ahead prices in the electricity market. This hybrid algorithm consists of (a) generalized mutual information (GMI), wavelet packet transform (WPT) as pre-processing methods, (b) least squares support vector machine based on Bayesian model (LSSVM-B) as forecaster engine, (c) and a modified artificial bee colony (ABC) algorithm used for optimization. Moreover, the orthogonal learning (OL) is used as a global search tool to enhance the exploitation of the ABC algorithm. Hereafter, call the proposed hybrid algorithm as S-OLABC. The numerical simulation results performed in this paper for different cases in comparison to previously known classical and intelligent methods. In addition, it will be shown that GMI based on WPT has better performance in extracting input features compared to classical mutual information (MI).

Impact of increased penetration of large-scale wind farms on power system dynamic stability - A review

Increased penetration of wind farms has created a new security concern for transmission system operators (TSOs) regarding the dynamic stability of the system. The renewable energy sources (RES) with more intermittent characteristics and lower inertial response can have considerable effect on the dynamic behavior of the conventional power systems, and as a result the characteristics of the oscillations may be significantly impacted. There are many research in literature that investigate the impact of wind penetration on dynamic stability of the power system, with even contradictory findings reported by different authors. This paper, based on most recent literature, presents a comprehensive survey on the impact of high penetration of wind farms on dynamic stability of power systems in particular on the small-signal and transient rotor angle stability. Even though, there cannot be a general statement made as an answer to the problem under consideration, however, this paper has drawn several important conclusions that must be carefully taken into account when integrating wind power into existing power systems.

Use of energy storage for Belgian power network

The intermittent and fluctuating nature of output power of renewable energy sources (RES) can lead to serious security concerns such as congestion in the transmission system. Incorporating storage devices with RES is technically an effective means to mitigate this concern by allowing fluctuating RES to be as stable as traditional power plants. Storage is an even more consumer-friendly solution with greater control over electricity consumption time and price compared to e.g. demand-side management which offers limited control over the price for end users. It can also contribute to lower the electricity price, peak-shave the demand, defer upgrade investments, provide ride-through solution for (momentary) faults, contribute to voltage/frequency control, increase the share of green energy and thus reduce overall greenhouse gas emissions, improve power quality by reducing harmonic distortions and voltage sags/surges, facilitate utilization of more efficient off-peak generation units, etc. This paper assesses the technical applicability and economical viability of different storage devices to the Belgian power network, focusing on the structure of the Belgian electricity market. A high-level overview of widely-used storage technologies, their benefits and shortcomings are also provided.

Distributed communication-based Model Predictive Control for long-term voltage instability

This paper deals with a form of long-term voltage instability which can arise from uncoordinated control actions taken by interacting voltage controllers. An effective coordination paradigm, based on Model Predictive Control (MPC), is proposed in order to properly coordinate local control actions taken by Load Tap Changing transformers (LTCs). This coordination is achieved by exchange of information on local planned LTC moves among immediate neighboring control agents (CAs) only, within a prediction horizon. Each MPC-based voltage controller, knows only a reduced-order local hybrid system model of its own area, and uses approximate models for its immediate neighboring areas, as well as even more approximate models for remote areas. Simulation results on well-known Nordic32 test system illustrate the good performance of the proposed real-time coordinating voltage controller.

Simultaneous optimal placement and parameter-tuning of SVC, TCSC and PSS using Honey-Bee Mating Optimization

Power system stabilizer (PSS), an auxiliary controller used in conjunction with the excitation system of synchronous generators, is mandatorily needed for damping low-frequency oscillations. FACTS devices are also increasingly being employed to provide sufficient damping for inter-area oscillations. However, uncoordinated tuning of PSSs and FACTS devices may cause unwanted interactions that further results in the system destabilization. This paper aims to simultaneously find optimal location as well as parameters of Static Var Compensator (SVC), Thyristor-Controlled Series Compensator (TCSC) and PSS controllers using multi-objective Honey-Bee Mating Optimization (HBMO) to damp low-frequency oscillations in multi-machine power systems. The proposed objective functions are eigenvalue-based that shift the system eigenvalues associated with the electromechanical modes to the left half of the s-plane and minimize the speed deviations at all machines. Simulation results on a 16-machine 68-bus power system confirm the effectiveness of the proposed method to be a useful framework for the optimal placement and parameter-tuning of the many existing controllers in large-scale power systems.

Financial Compensation of Energy Security Service Provided by Dual-Branch Controller of Large-Scale Photovoltaic System in Competitive Electricity Markets

The financial value of security service provided by dual-branch controller of a large-scale photovoltaic system (LPS) has been investigated in this paper. To perform this task, it is necessary to investigate the impact of LPS on small-signal stability of power network. To study the impact and performance of LPS on low-frequency oscillatory modes, a systematic scheme is developed to achieve an accurate model of multi-machine power network including of the LPS technology. A fully-described LPS model with all network-relevant control functions will be obtained. The proposed model has been then employed in the study of financial compensation strategy of security service provided by the LPS controller. The proposed compensation strategy in this paper is based on correlation of swing damping rate (SDR) criterion with generation cost (GC) criterion as dynamic and pecuniary indices, respectively. A weighted sum of performance and robustness indices is considered for SDR. The financial profit created by dual-branch controller of LPS as ancillary service (AS) is evaluated by a two-purpose optimization based on SDR and GC indices. The proposed strategy is tested on a modified 6-machine 3-area power system. Comprehensive discussion is provided to describe the performance of the presented method.