• Energy Research

By the proliferation of electric vehicles (EVs) in power systems, it is needed to manage their demand energy within a regulated market framework. From the market perspective, integration of different market players, such as the energy producers, aggregators, and loads, could complicate the system operation and management. Therefore, an appropriate model of the market that shows the exact behavior of the system components is needed. In this paper, a new tri-level game theoretical approach for energy management of EVs and EV charging stations (EVCSs) as independent decision makers for their energy scenarios is proposed. To make it practical for a real power system, the system operator is also included in the proposed method as a master decision maker. Therefore, EVs’ and EVCSs’ objectives are to maximize their financial profits, while the system operator indirectly controls their energy scenarios in order to fulfill the system’s technical constraints. To do so, at the highest level of the proposed method, technical goals of the system, which are related to the system operational condition, will be followed as the objective criteria. At the second level of the designed model, the EVCSs financial objectives are optimized. In the third level of the proposed method, it is tried to minimize the EVs’ cost function. The method is tested on an IEEE 9-bus standard system, and the results show a superior performance of the proposed energy management system (EMS) compared with the conventional EMS methods in terms of technical and financial objectives. In this way, it is shown that in the case of considering only one aspect of the system, either financial or technical, the other aspects of the system may not be satisfied. Hence, it is essential to consider both the financial and technical aspects of the system simultaneously, in order to operate the system optimally and securely.

The Internet of Things (IoT) is beginning to shape the future of many industries and emerging markets. One of the target markets for IoT is the energy systems. IoT is a matter of producing, transferring, and processing information, therefore all parts of the system including software and hardware parts should be considered as a whole. In this paper, a state-of-the-art of the IoT-based energy systems is presented to review the recent activities on every component of IoT in energy systems. Challenges in this subject area are discussed, and some solutions are presented thereafter.

AbstractInverter‐based generators (IBGs) are becoming popular in modern power systems. When the penetration of IBGs is increasing in power systems, new stability, protection, and monitoring challenges are introduced in the grid. Grid‐forming (GFM) control of converters is seen as a promising solution for future power grids to overcome particular stability challenges. Here, the technical challenges of the GFM‐based IBGs are reviewed from the point of view of TSOs and academic research. The properties of different GFM methods are studied for different GFM‐based IBGs for a single grid‐tied IBG and using the IEEE 9‐bus test system. Simulation results are provided by using the PSCAD‐EMT simulation software.

In this paper, a Lyapunov-based method is used in order to determine the stability boundaries of the grid-connected voltage source converter (VSC). To do so, a state space model of the VSC is used to form the Lyapunov function of the system. Then, by using the eigenvalues of the Lyapunov function, the system stability boundaries will be determined. It is shown that the grid-connected VSC works in its stable mode when all of its Lyapunov function’s eigenvalues are positive. The proposed model validity is tested by time-domain simulation. Simulation results show that the method is credible in determining the stability margin of the grid-connected VSC.

By the increase of the penetration of power-electronic-based (PE-based) units, such as wind turbines and PV systems, many features of those power systems, such as stability, security, and protection, have been changed. In this paper, the security of electrical grids with high wind turbines penetration is discussed. To do so, first, an overview of the power systems’ security assessment is presented. Based on that, stability and security challenges introduced by increasing the penetration of wind turbines in power systems are studied, and a new guideline for the security assessment of the PE-based power systems is proposed. Simulation results for the IEEE 39-bus test system show that the proposed security guideline is necessary for PE-based power systems, as the conventional security assessments may not be able to indicate its security status properly.

Abstract This paper reveals that the existing techniques have some deficiencies in the proper estimation of voltage stability margin (VSM) when applied to a power system with different load change scenarios. The problem gets worse when credible contingencies occur. This paper proposes a real-time wide-area approach to estimate VSM of power systems with different possible load change scenarios under normal and contingency operating conditions. The new method is based on an artificial neural network (ANN) whose inputs are bus voltage phasors captured by phasor measurement units (PMUs) and rates of change of active power loads. A new input feature is also accommodated to overcome the inability of trained ANN in prediction of VSM under N−1 and N−2 contingencies. With a new algorithm, the number of contingencies is reduced for the effective training of ANN. Robustness of the proposed technique is assured through adding a random noise to input variables. To deal with systems with a limited number of PMUs, a search algorithm is accomplished to identify the optimal placement of PMUs. The proposed method is examined on the IEEE 6-bus and the New England 39-bus test system. Results show that the VSM could be predicted with less than 1% error.

Existing techniques exploiting local measurements to calculate the long-term voltage stability mostly rely on Thevenin equivalent concept. This notion calls for two or more distinct measurement sets for computation of Thevenin parameters assuming that the power system stays unchanged during the data collection, which is not essentially true. This paper presents a new method for computation of voltage stability margin associated with system load buses using voltage and current magnitudes. The proposed method is independent from the system variations; thus, it does not suffer from the shortcoming of regular Thevenin equivalent method. The new methodology is based on this observation that in the stable region of voltage stability curve, the normalized absolute value of the rate of change of voltage magnitude is greater than that of the current magnitude. This observation is supported by the theoretical analysis as well. To demonstrate performance of the developed method, a simple radial network and the IEEE 14-bus test system are examined.