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This paper presents a voltage control method using multiple distributed generators (DGs) based on a multi-agent system framework. The output controller of each DG is represented as a DG agent, and each voltage-monitoring device is represented as a monitoring agent. These agents cooperate to accomplish voltage regulation through a coordinating agent...
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... the proposed method, the bus voltages in the distribution system can be controlled by coordinating the reactive power output of the DGs. Figure 1 shows the basic structure of the MAS platform. Each agent links to an electrical node of the distribution network or an output controller of a DG. ...
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... follows that a DG that only belongs to that area does not contribute to voltage compensation. To clarify the output of the FIS rule-based evaluation, a three-dimensional plot of the fuzzy rules described in Section 3.2 is shown in Figure 10. Following the development of the decision-making model of the moderator, we studied two voltage violation cases to verify the effectiveness of the proposed voltage control method. ...
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... first case shows the general voltage control process when the voltage problem occurs due to a load increase. Figure 11a shows the initial operating conditions for Case 1: the demand power of the loads and the output power of DGs are given in the form of P + jQ in kW and kVar. In the initial state, the voltage of the last bus was 0.9613 p.u. (normal state). ...
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... DG agents then bid for that proposal by providing the data on Q s and Q m , the values of which are listed in Table 2. The moderator determined the additional reactive power output of each DG based on these bidding data; the values of the inputs and outputs to the moderator are also listed in Table 2. Figure 12a shows the variation in the voltage profile. The abnormal state of the last bus voltage (red-circle line) was restored to the normal state (blue-star line). ...
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... second case shows how the voltage can be recovered to within the normal range when the voltage problem cannot be resolved using a single voltage control process. In this case, the initial condition was assumed to be as shown in Figure 11b, where the last bus voltage was significantly below the normal limit, at 0.9355 p.u. This voltage problem cannot be resolved through one voltage control process, as the voltage compensation determined by Equation (14) is not sufficient. ...
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Low-voltage direct current (LVDC) distribution systems have been evolving into interesting ways of integrating distributed energy resources (DERs) and power electronics loads to local distribution networks. In LVDC distribution systems, voltage regulation is one of the most important issues, whereas AC systems have concerns such as frequency, power...
The high penetration of renewable energy sources in modern distribution networks poses challenges for grid voltage regulation. In this study, a multi-agent distributed voltage control strategy based on the proximal Jacobian alternating direction method of multipliers (PJ-ADMM) is proposed for distribution power systems with a high penetration of ph...
Citations
... The centralized control of a smart grid can monitor the data in real-time and with the forecasting capacity, intelligent allocation of generation resources can be performed. It can also optimize the operation time of distributed generation and improve the management of resources under different conditions (García-López et al. 2018;Kang, Chung, and Moon 2015). The intelligent functions can be attained through an effective communication system, considering the environmental conditions and technical standards to ensure efficient data flow through fast full-duplex communication infrastructure (Asaad et al. 2018;Jiang and Mamishev 2004;Jingcheng et al. 2012). ...
... ( García-López et al. 2018;Kang, Chung, and Moon 2015) Monitoring technologies ...
The smart grid is not a monolithic system, but rather is a collection of several renewable energy resources and enabling technologies in which, intelligent control is an integral part of its mechanism to improve the utilization of assets. The dynamic characteristics of a smart grid upgrade the conventional system requirements using advanced control strategies to provide continuous power to the load from intermittent renewable generation. The communication networks and control systems that enable the accommodation of distributed generation are crucial technologies in monitoring, protecting, and operating the smart grid in a centralized or decentralized manner. This paper improves the earlier published review articles by exploring the evolution of smart grids in light of renewable energy penetration with associated features. Then, the review gives an overview of notable research works in the literature aimed at developing the management and control of smart energy systems. The reader is provided with an in-depth analysis of advanced cloud computing, the internet of things, and blockchain technology with real examples for the related renewable energy projects in smart cities. Furthermore, a special interest has been paid to quantify the performance of communication technologies along with the protocols through the conceptual investigation o b f real cases using the optimized network engineering tools. The outcomes of the presented review can assist researchers to understand the driving mechanism of smart grid as a route to intelligently utilize renewable energy storage. It is concluded that the amalgamation of blockchain and artificial intelligence for renewable energy management is the key area where the avenue is still open for future research studies.
... Distribution systems were not originally designed to operate with DG; therefore, its insertion in the network must be carefully planned out. In this regard, the integration of DG in distribution networks has been the focus of several studies [2][3][4][5][6][7][8][9][10][11][12]. Most of these studies aim at harvesting the potential benefits of DG such as: reduction of power losses [2][3][4], improvement of voltage profile [5], improvement of stability [6], and deferral of investments [7]. ...
... In this regard, the integration of DG in distribution networks has been the focus of several studies [2][3][4][5][6][7][8][9][10][11][12]. Most of these studies aim at harvesting the potential benefits of DG such as: reduction of power losses [2][3][4], improvement of voltage profile [5], improvement of stability [6], and deferral of investments [7]. In recent years there has been an important increase in the participation of DG in distribution systems. ...
In this paper we present a scatter search (SS) heuristic for the optimal location, sizing and contract pricing of distributed generation (DG) in electric distribution systems. The proposed optimization approach considers the interaction of two agents: (i) the potential investor and owner of the DG, and (ii) the Distribution Company (DisCo) in charge of the operation of the network. The DG owner seeks to maximize his profits from selling energy to the DisCo, while the DisCo aims at minimizing the cost of serving the network demand, while meeting network constraints. To serve the expected demand the DisCo is able to purchase energy, through long-term bilateral contracts, from the wholesale electricity market and from the DG units within the network. The interaction of both agents leads to a bilevel programming problem that we solve through a SS heuristic. Computational experiments show that SS outperforms a genetic algorithm hybridized with local search both in terms of solution quality and computational time.
... In distribution network, the number of grounding fault reaches 70% in all types of system faults, and over 70% of them are transient faults [1]. Self-healing plays an important role in distribution network [2][3][4][5][6][7][8]. The systems, which have been effectively grounding, protect themselves by switching breakers when grounding faults occur. ...
Signal injection method (SIM) is widely applied to the insulation parameters' measurement in distribution network for its convenience and safety. It can be divided into two kinds of patterns: injecting a specific frequency signal or several frequencies' groups, and scanning frequency in a scheduled frequency scope. In order to avoid the disadvantages in related researches, improved signal injection method (ISIM), in which the frequency characteristic of the transformer magnetizing impedance is taken into consideration, is proposed. In addition, optimization for signal injection position has been accomplished, and the corresponding three calculation methods of line-To-ground capacitance has been derived. Calculations are carried out through the vector information (vector calculation method), the amplitude information (amplitude calculation method), the phase information (phase calculation method) of voltage and current in signal injecting port, respectively. The line-To-ground capacitance is represented by lumped parameter capacitances in high-voltage simulation test. Eight different sinusoidal signals are injected into zero-sequence circuit, and then line-To-ground capacitance is calculated with the above-mentioned vector calculation method based on the voltage and the current data of the injecting port. The results obtained by the vector calculation method show that ISIM has a wider application frequency range compared with signal injection method with rated parameters (RSIM) and SIM. The RSIM is calculated with the rated transformer parameters of magnetizing impedance, and the SIM based on the ideal transformer model, and the relative errors of calculation results of ISIM are smaller than that for other methods in general. The six groups of two-frequency set are chosen in a specific scope which is recommended by vector calculation results. Based on ISIM, the line-To-ground capacitance calculations through the amplitude calculation method and phase calculation method are compared, and then its application frequency range, which can work as a guidance for line-To-ground capacitance measurement, is concluded.
... Energies 2017, 10, 156 2 of 16 systems (ESSs). Both of them could be involved by the distribution system operator (DSO) in regulating the network operating conditions, e.g., as illustrated in [6][7][8][9]. ...
The recent growing diffusion of dispersed generation in low voltage (LV) distribution networks is entailing new rules to make local generators participate in network stability. Consequently, national and international grid codes, which define the connection rules for stability and safety of electrical power systems, have been updated requiring distributed generators and electrical storage systems to supply stabilizing contributions. In this scenario, specific attention to the uncontrolled islanding issue has to be addressed since currently required anti-islanding protection systems, based on relays locally measuring voltage and frequency, could no longer be suitable. In this paper, the effects on the interface protection performance of different LV generators’ stabilizing functions are analysed. The study takes into account existing requirements, such as the generators’ active power regulation (according to the measured frequency) and reactive power regulation (depending on the local measured voltage). In addition, the paper focuses on other stabilizing features under discussion, derived from the medium voltage (MV) distribution network grid codes or proposed in the literature, such as fast voltage support (FVS) and inertia emulation. Stabilizing functions have been reproduced in the DIgSILENT PowerFactory 2016 software environment, making use of its native programming language. Later, they are tested both alone and together, aiming to obtain a comprehensive analysis on their impact on the anti-islanding protection effectiveness. Through dynamic simulations in several network scenarios the paper demonstrates the detrimental impact that such stabilizing regulations may have on loss-of-main protection effectiveness, leading to an increased risk of unintentional islanding.
... A MAS can be defined as a system comprising multiple intelligent agents that have the abilities of autonomous decision-making and communication with other agents [9,10]. In [11,12], the authors suggested an agent-based algorithm to control the reactive power output of distributed energy resources (DERs) for proper voltage regulation with a few communication requirements. However, they did not consider the coordination between OLTC and DERs. ...
Low-voltage direct current (LVDC) distribution systems have been evolving into interesting ways of integrating distributed energy resources (DERs) and power electronics loads to local distribution networks. In LVDC distribution systems, voltage regulation is one of the most important issues, whereas AC systems have concerns such as frequency, power factor, reactive power, harmonic distortion and so on. This paper focuses on a voltage control method for a LVDC distribution system based on the concept of multi-agent system (MAS), which can deploy intelligence and decision-making abilities to local areas. This paper proposes a distributed power flow analysis method using local information refined by local agents and communication between agents based on MAS. This paper also proposes a voltage control method by coordinating the main AC/DC converter and multiple DERs. By using the proposed method, we can effectively maintain the line voltages in a pre-defined normal range. The performance of the proposed voltage control method is evaluated by case studies and compared to conventional methods.
... of DERs are quite different [5,6]. As a result, the conventional centralized control is inadequate for microgrid systems [7][8][9]. ...
Data acquisition and supervisory control are usually performed using client-server
architecture and centralized control in conventional power systems. However, the message
transmission and fault clearing are too slow for large-scale complex power systems. Microgrid
systems have various types of distributed energy resources (DERs) which are quite different
in characteristics and capacities, thus, the client-server architecture and centralized control are
inadequate to control and operate in microgrids. Based on MATLAB/Simulink (ver.R2012a)
simulation software and Java Agent Development Framework (JADE) (JADE 4.1.1-revision 6532),
this paper proposes a novel fault protection technology that used multi-agent system (MAS) to
perform fault detection, fault isolation and service restoration in microgrids. A new topology
identification method using the YBus Matrix Algorithm is presented to successfully recognize
the network configurations. The identification technology can respond to microgrid variations.
Furthermore, the interactive communications among intelligent electronic devices (IEDs), circuit
breakers (CBs), and agents are clarified during fault occurrence. The simulation results show that the
proposed MAS-based microgrids can promptly isolate faults and protect the system against faults in
real time.
... Power system stability; (2) Power system reliability; (3) Flexible alternating current transmission systems (FACTS) applied to power systems; (4) Application of optimization methods to power systems; (5) Architectures and models of smart grids; (6) Power market; (7) Control, operation, and planning of distributed generation resources; (8) Smart home with energy management systems; (9) Microgrids and active distribution networks; (10) Virtual power plants and demand response. ...
... The transmission system category covers high-voltage direct current (HVDC), FACTS, and thermal standards [5,8,12,21]. The distribution system category covers many topics, such as voltage control, network reconfiguration, microgrids, power quality, smart distribution, and multi-agents [6,10,11,14,20,22]. The end-users category covers demand response, frequency control, and critical peak pricing [7,15,18,19]. ...
... The power market category deals with problems of contract design and load serving entities [9,18]. Several papers [8,10,15,18] cover more than one subject. ...
This book contains articles [1–22] that were accepted for publication in a Special Issue of Energies on the subject of “Electric Power Systems Research”.[...]
This paper focuses on voltage control schemes for multi-terminal low-voltage direct current (LVDC) distribution systems. In a multi-terminal LVDC distribution system, there can be multiple AC/DC converters that connect the LVDC distribution system to the AC grids. This configuration can provide enhanced reliability, grid-supporting functionality, and higher efficiency. The main applications of multi-terminal LVDC distribution systems include flexible power exchange between multiple power grids and integration of distributed energy resources (DERs) using DC voltages such as photovoltaics (PVs) and battery energy storage systems (BESSs). In multi-terminal LVDC distribution systems, voltage regulation is one of the most important issues for maintaining the electric power balance between demand and supply and providing high power quality to end customers. This paper focuses on a voltage control method for multi-terminal LVDC distribution system that can efficiently coordinate multiple control units, such as AC/DC converters, PVs and BESSs. In this paper, a control hierarchy is defined for undervoltage (UV) and overvoltage (OV) problems in LVDC distribution systems based on the control priority between the control units. This paper also proposes methods to determine accurate control commands for AC/DC converters and DERs. By using the proposed method, we can effectively maintain the line voltages in multi-terminal LVDC distribution systems in the normal range. The performance of the proposed voltage control method is evaluated by case studies.
