Implementation of Advanced Power Application Software to KEPCO'S Energy Management System

The rigidity of information technology (IT) has been hindering the development of various businesses regarding energy management systems (EMSs) of power networks, although this area has become more diversified, resulting in changes of elements in the systems due to the introduction of renewable energy (RE) and the new energy industry. In order to effectively accommodate these changes, EMSs should be developed in a structure with a standard-based interface, which can secure interoperability between components in the EMS. In previous studies, the common information model (CIM) proposed by IEC TC57 has been utilized for developing EMSs of power networks, but there are gaps between the existing CIM and an information model for the EMSs of carbon-free island microgrids (MGs), which are a newly introduced form of power network covering multiple islands for reducing carbon emissions. This paper proposes a CIM-based software platform for a carbon-free island MG-EMS to efficiently operate the power network and secure interoperability between components in the MG-EMS. Concerning service restoration of the power network, use cases and business objects representing information exchanged between the components in the EMS are derived, and the existing CIM is extended based on the results of the gap analysis in order to provide necessary information on the MG-EMS. The validity of the proposed platform is verified by exchanging payloads between components in the MG-EMS based on the profile extracted from the extended CIM. Furthermore, the performance of the proposed platform regarding data size and speed of data exchange is presented. Based on the case study results, it is concluded that the proposed platform based on the extended CIM can exchange data between the components in the MG-EMS, achieving reasonable data size and speed of data exchange with the help of the interoperability between components in the carbon-free island MG-EMS.

Energy and maintenance management systems in the context of industry 4.0. Implementation in a real case

In this study, a solar-hydrogen hybrid power generation system is modeled by developing a smart energy management system (EMS) to sustain a continuous power flow for a local load in a constituted residential hybrid power plant. The developed EMS checks the total energy demand of the hybrid power plant and operates the solar power plant or the hydrogen energy based power plant to provide a sustainable power for the local load. A new control card is developed and a real-time EMS is performed in Labview for controlling and monitoring the hybrid system. The implemented electronic control card manages the active power flow of the hybrid system to provide a sustainable power demand of the local load. The current energy demand of the residential power plants can be viable in the lack of the sun or hydrogen, thanks to the developed EMS. The proposed EMS is modeled in Matlab/Simulink, and verified by the experimental study. The experimental results show that the proposed EMS provides a sustainable energy infrastructure for the residential hybrid power plants, and it is also easy implemented and suitable for residential real system applications.

Multi-channel multi-core CPU parallel and CPU+GPU heterogeneous parallel are effective means to enhance Network Analysis Application computing. To solve the job scheduling problem of Network Analysis Application with multi-level dispatching, multi-user, multi-task in CPU/GPU heterogeneous cluster environment, a multi-user concurrent job scheduling method for Network Analysis Application in CPU/GPU cluster is proposed. According to the characteristics of Network Analysis Application, it is suggested that state estimation and dispatcher power flow should be accelerated in parallel with CPU, while static security analysis, perturbation power flow calculation and interruption capacity scanning should be accelerated in parallel with CPU+GPU. The job scheduling method proposed in this paper can satisfy the high concurrent requests of multi-level Dispatching & Control Center in the isomorphic and heterogeneous computing environments.

This paper presents a novel power flow control strategy, combined with an economic analysis, for an energy management system (EMS) involving a hybrid energy storage. The EMS operates a remote microgrid and directs the power flow to either batteries or supercapacitors to increase the life of the batteries. This paper demonstrates how the use of supercapacitors increases the lifetime of the batteries and ultimately how it affects the economics of the system. The proposed EMS controller also compensates for the 120-Hz ripple on the dc bus. Modeling, simulations, and experimental verification are presented together with the procedure to perform the assessment of the battery lifetime, according to the tuning parameters of the controller.

This paper describes the implementation of real-time stability assessment in the power system control centers of the Independent System Operator in Bosnia and Herzegovina (NOS-BiH) and, respectively, a National Dispatching System in North Africa. These solutions are conceptually different in terms of stability assessment scope and techniques -- but are very similar in terms of implementation approach. At the NIS-BiH, it provides for rapidly quantifying the risk of blackout, tracking the distance to instability in real-time, and presenting the results in meaningful and user-friendly formats. The technique is based on a fast steady-state stability algorithm that computes the maximum system loadability for the current state and for postulated contingencies. The stability application is seamlessly integrated with the SINAUT Spectrum SCADA/EMS and runs automatically after each successful execution of the State Estimator and/or Dispatcher's Power Flow. The North Africa solution is based on dynamic security analysis aimed at evaluating the transient system stability conditions in advance of performing scheduled system outages, e.g., major switching actions such as switching transmission lines or large capacitors. Practical experience results are presented and illustrated.

An energy management system (EMS) is necessary to provide the UAV propulsion system with the energy from multiple power sources. This paper presents a new control strategy of EMS for a small solar-powered unmanned aerial vehicle (UAV). The EMS based on the value of DC bus voltage can efficiently manage the power from PV modules and the storage system, which support the UAV operation steadily even under potential rapidly varying atmospheric condition. In this EMS, PV modules can operate at multi-mode by self-adaption control strategy and storage system can be flexibly controlled to coordinate system energy power flow. The results of simulation and experiments are included to verify the effectiveness of the proposed EMS.

The nature of transmission and distribution networks has drastically changed over the last several decades, due to a high penetration of electronically interfaced energy resources (EIERs). Consequently, the complexity of the operation and the management of these networks have considerably increased. This strongly affected the energy management systems and distribution management systems, especially the power flow calculation as their basic power application. Electronically interfaced energy resources can employ a wide range of control strategies that cannot be represented with traditional single-phase bus types used for traditional alternating current machines in a symmetrical operation. Power flow is the main subject of this paper, and the main objectives are as follows: (i) to prove that the traditional bus classification—θV (slack bus), PQ, and PV—is not sufficient for an unbalanced power flow formulation and the calculation of emerging large-scale unbalanced electric networks containing traditional alternating current machines and particularly EIERs; (ii) to introduce a new bus classification suitable for the power flow modeling and calculation of these networks; and (iii) to present a robust and accurate unbalanced power flow method based on the new bus classification and a bus type inspection principle. Numerical tests show that the developed power flow method can be successfully applied in the on-line calculation mode of both energy management system and distribution management system dealing with large-scale networks.

Grey wolf-optimized artificial neural networks used in DC–AC hybrid distribution networks, to regulate the energy consumption, is presented in this study. Energy management system that takes into consideration, the distributed generation, load demand, and battery state of charge are being considered. The artificial neural network have been trained, utilising the profile data, based on the energy storage system’s charging and discharging characteristics, under various distribution network power conditions. Moreover, the error rate was kept, well under 10%. The suggested energy management system, that employs an artificial neural network, has been trained to function in the optimal mode, utilising grey wolf optimization for each grid-connected power converter. Small-scale hybrid DC/AC microgrids have been developed and tested, in order to simulate and verify the proposed energy management system. The grey wolf optimized neural network energy management system has been proven to provide 99.48 % efficiency, which is superior when compared to other methods existing in the literatures.

Energy management systems are necessary in off-grid direct current (DC) power systems such as electric vehicles and DC microgrids to manipulate their distributed power sources. The system is tightly connected to the communication system between elements. In this sense, the energy management system is recognized as one of the cyber-physical systems. Power (or energy) packet and its dispatching system is also a cyber-physical approach to the DC system. The concept of power packet is tracing the packets in information networks. A power packet consists of a unit of DC power and the information tag which is attached to the power as voltage waveforms. The power flow has been numerically studied in power packet dispatching network. However, its characteristics and limitations are still unknown from the practical point of view. This paper experimentally verifies the half-duplex power packet transmission. The half-duplex transmission is one of the ways to transfer packets bidirectionally. The results showed that the half-duplex power packet transmission can be achieved in an experimental system with a MAC protocol as the information network. The results clarify that the communication system design may help the power system design.

In the context of microgrid, renewable energy variations are still a major concern for operators, especially in industrial applications in which microgrids are typically located in remote areas and are operated autonomously. Information gap decision theory (IGDT) is a nonprobabilistic method utilized to appraise various levels of risk without the availability of statistical data, such as probability density functions of uncertain parameters. Despite such a rewarding feature, the IGDT in its current form is unable to obtain time-varying robustness bands, meaning that it does not take into consideration the system risk imposed by renewable energy injections at each individual time interval in a short-term operation horizon. To overcome this issue, this article presents a modified version of the IGDT named weighted IGDT (W-IGDT), yielding risk-based time-varying robustness bands rather than time-independent ones. This article also proposes a W-IGDT-based energy management system (EMS) based on a linked unit commitment-optimal power flow (UC-OPF) framework, which simultaneously incorporates the generating units on/off status as well as power flow limits into the optimization procedure. In order to illustrate the performance of the proposed EMS, a CIGRE microgrid benchmark is utilized, and the results indicate the effectiveness of the W-IGDT-based EMS in terms of optimal operation and addressing the intermittency of renewable energy sources.

Context: This paper proposes an energy management system (EMS) for battery energy storage systems (BESS) to reduce operating costs in AC microgrids (MGs) operating in grid-connected (GON) and islanded (GOFF) mode, considering energy purchase, conventional generation, and maintenance costs while accounting for all the operational constraints of the system and its components. Method: A master-slave methodology based on particle swarm optimization (PSO) and an hourly power flow based on the successive approximations method (SAM) is used as a smart BESS operation strategy. This proposal is validated in a 33-bus AC-MG operating in GON and GOFF modes, in comparison with two methods utilizing the vortex search algorithm (VSA) and conitnuos version of the Chu & Beasley genetic algorithm (CBGA) and the same power flow. Results: The PSO-based EMS achieved the lowest costs i.e., 6897.59 USD/day (GON) and 17 527.42 USD/day (GOFF), with cost reductions of 1.45 and 0.13 %, and low standard deviation values (0.067 and 0.014 %), which confirms its efficiency, robustness, and constraint compliance. Conclusions: The EMS based on PSO/SAM delivers superior solution quality and processing times in both modes of operation. In GON mode, it reduces the mean costs by 0.0287%compared to the VSA and 0.2252%vs. the CBGA, whereas, in GOFF mode, the reductions are 0.0191 and 0.0355 %, respectively. These results reflect a more effective cost reduction than exact methods, which constitutes this paper’s main contribution.

This paper proposes the development of a shipboard Energy Management System (EMS), specifically devised to enhance the efficiency of electrical microgrids in cruise vessels. Due to the target application, the reference electrical plant is an Integrated Power System, typical of modern All Electric Ships (AESs). In order to enable the EMS operation, suitable architecture modifications on the current electrical system have been envisaged, which are also coherent with the ongoing transition of today marine electrical plants toward the microgrid paradigm. In particular, the introduction of energy storage systems (ESSs) has been considered. The proposed EMS performs a real-time scheduling of the electrical power flows, based on load demand forecasting data and a Dynamic Programming (DP)-based optimization strategy. Its main goal is the reduction of the load peaks, which are responsible for unnecessary oversizing of the electrical generators and consequently of inefficient operation. The EMS has been set up using a low-cost programmable embedded platform. The test results on the EMS demonstrate its effectiveness and feasibility.

A central question in the analysis and operation of power networks is feasibility of the power flow equations subject to security constraints. For large-scale networks the solution of the nonlinear AC power flow equations can be constructed only numerically or approximated through the linear DC power flow. The latter serves as well-used approximation to obtain the phase angle differences near an acceptable operating point, but the accuracy of the DC approximation drops in a stressed grid. Here, we propose a modified DC approximation that applies to lossless networks with parametric uncertainties and with voltage magnitudes bounded within security constraints. We show that the phase angle differences can xbe well approximated by the solution to a set of linear and interval-valued equations reminiscent of the DC power flow equations. Our proposed approximation improves upon the standard DC approximation, is computationally attractive and provably exact for a broad range of network topologies and parameters. We validate the accuracy of our approximation through standard power network test cases with randomized power demand at the loads.

2 - Energy Management for Medium-Voltage Direct Current Networks