Existing Energy Management Systems Research Articles

МЕТОДИКА ВЕРОЯТНОСТНОЙ ОЦЕНКИ ЭЛЕКТРОПОТРЕБЛЕНИЯ (ВОПРОСЫ ЭНЕРГЕТИЧЕСКОЙ БЕЗОПАСНОСТИ И ПРАВОВОГО ОБЕСПЕЧЕНИЯ)

The article deals with the problem of determining the actual energy consumption of outdoor lighting in municipalities, which arises as a result of the shortcomings of the existing energy management system and leads to contradictions between electricity suppliers and the municipality. The lack of metering devices and a wide variety of types of lighting lamps leads to the fact that the standard calculation methods used by the supplier unreasonably overestimate the cost of real consumption, thus limiting the budgetary possibilities of cities. It is proposed to solve this problem through the use of rank-parametric tools, which are successfully used for evaluation and forecasting in industry.

Forecasting Wind Speed Using Clustering of Trend-Based Time Series Data

Accurate forecasting of wind speed is crucial for the efficient operation of wind energy systems. As a time-series concern, wind forecasting may help determine how much electricity a proposed wind farm might produce annually. The majority of forecasting techniques perform differently depending on seasonal and trends variation. For this reason, time series data frequently have seasonal and nonlinear trend components eliminated in order to simplify wind forecasting approach. The application function used to remove the seasonality and trend determines accuracy. The proposed method begins by identifying and extracting underlying trends from historical wind speed data, segmenting the time series into distinct trend-based components. This paper proposes a hybrid method for predicting time series. A method for clustering data has been designed that identifies clusters of time series data with similar trend components. Statistical procedures, such as generalized autoregressive and autoregressive integrated moving average scoring approaches, are used to each individual cluster after the appropriate clusters of related trend components have been identified. Ultimately, the components that are made are combined. The datasets collected from the NREL site. The experiment demonstrates that when compared to current statistical approaches, the cluster-based forecasting approach performs better. This research makes contribution towards the field of renewable energy forecasting by providing a robust and scalable method for wind speed prediction, which can be integrated into existing energy management systems for improving the efficiency and stability of wind energy generation. The research paper examines the trend features of time series data of wind employing the suggested hybrid technique on wind forecasting. Performance calculated in terms of RMSE and MAE shows that the proposed technique succeeds as compared to other state of the art techniques.

Revolutionizing smart grid-ready management systems: A holistic framework for optimal grid reliability

Existing energy management systems are becoming increasingly insecure and inefficient due to the rapid adoption of smart grid technology. Current research indicates that effectively managing dynamic energy flows, adjusting to changing needs, and protecting against new cyber threats remain significant challenges for the smart grid system. An advanced and comprehensive plan for managing smart grids is therefore required, capable of addressing these delicate and multifaceted problems. The proposed framework addresses these challenges through unifying several key aspects, it includes an advanced data acquisition system that captures real-time data from various grid sources, enabling comprehensive energy monitoring and dynamic flow analysis. By integrating predictive algorithms, the framework provides precise energy demand forecasting, which is essential for adaptive grid management. A significant contribution is the incorporation of an AI-based module for diagnostics and prognostics, which leverages machine learning techniques to shift from reactive to proactive maintenance strategies. The optimal power flow (OPF) optimization module represents a central component of the framework. It employs advanced computational methods to ensure efficient and cost-effective power distribution, particularly in grids incorporating renewable energy sources. Additionally, the architectural framework is strengthened by a robust cybersecurity module designed to safeguard against a wide range of cyber threats, maintaining the integrity of both operational and consumer data. This paper also addresses practical implementation challenges such as compatibility with existing infrastructure, investment costs, and the need for specialized training. This solution represents a new benchmark for smart grid operations, ensuring more sustainable and efficient energy systems.

Scenario-Based Uncertainty Modeling for Power Management in Islanded Microgrid Using the Mixed-Integer Distributed Ant Colony Optimization

Reliable droop-controlled islanded microgrids are necessary to expand coverage and maximize renewables potential. Nonetheless, due to uncertainties surrounding renewable generation and load forecast, substantial power mismatch is expected at off-peak hours. Existing energy management systems such as storage and demand response are not equipped to handle a large power mismatch. Hence, utilizing dump loads to consume excess power is a promising solution to keep frequency and voltage within permissible limits during low-load hours. Considering the uncertainty in wind generation and demand forecast during off-peak hours, the dump load allocation problem was modeled within a scenario-based stochastic framework. The multi-objective optimization with uncertainty was formulated to minimize total microgrid cost, maximum voltage error, frequency deviation, and total energy loss. The mixed-integer distributed ant colony optimization was utilized in a massive parallelization framework for the first time in microgrids to solve the decomposed deterministic problem of the most probable scenarios. Moreover, a flexible and robust load-flow method called general backward/forward sweep was used to obtain the load-flow solution. The optimization problem was applied to the IEEE 69-bus and 118-bus systems. Furthermore, a cost benefit analysis was provided to highlight the proposed method’s advantage over battery-based power management solutions. Lastly, the obtained results further demonstrate the fundamental role of dump load as power management solution while minimizing costs and energy losses.

Research on Energy Management System Based on Hall Model

The energy management system is an organic combination of a series of interrelated elements for enterprises to establish and achieve energy policies and objectives. In order to solve the problems of inconsistency of the existing standard system, unclear components and the ambiguity and randomness of a single management method, this paper constructs a three-dimensional structure model of energy management system based on Hall model. from the perspective of energy management, taking the big data formed by the enterprise energy management system as the background, aiming to improve the efficiency and provide reference for the construction of energy management system. By introducing the time dimension to realize the unified expression framework of energy management involved in the energy management standard system and the energy management regulation system, the seven logical steps of the logical dimension of the energy management system are proposed, and the knowledge dimension, which is composed of professional knowledge and skills required to complete the above stages and steps, is added to form a three-dimensional structure space composed of the time dimension, logical dimension and knowledge dimension. Through the example, it is found that the application of Hall's three-dimensional structure model to build an energy management system can greatly improve the efficiency, optimize the existing energy management system and means of the enterprise, and make the establishment of energy management system more systematic, and the energy management system built based on Hall's three-dimensional model can be further promoted and applied.

Microgrid Energy Management and Methods for Managing Forecast Uncertainties

The rising demand for electricity, economic benefits, and environmental pressures related to the use of fossil fuels are driving electricity generation mostly from renewable energy sources. One of the main challenges in renewable energy generation is uncertainty involved in forecasting because of the intermittent nature of renewable sources. The demand also varies according to the time of day, the season, the location, the climate, and the availability of resources. Microgrids offer a potential solution for the integration of small-scale renewable energy sources and loads along with energy storage systems and other non-renewable sources. However, intermittent generation and varying demand need to be matched to provide stable power to consumers. Therefore, it is crucial to design an energy management system to effectively manage the energy sources and supply loads for reliable and efficient operation. This paper reviews different techniques proposed in the literature to achieve the objectives of a microgrid energy management system. The benefits of existing energy management systems and their challenges are also discussed. The challenges associated with uncertainties and methods to overcome them are critically reviewed.

A novel and comprehensive mechanism for the energy management of a Hybrid Micro-grid System

Renewable energy has gained enormous popularity in recent years. Both independent and grid-connected renewable energy generating capacity has increased. The potential to create green energy that is both ecologically benign and financially operative is the primary argument. To reduce the cost of maintaining a hybrid microgrid, this study provides a novel control algorithm as well as a suitable energy management system. The energy storage technologies are used in the hybrid microgrid system which consist of photovoltaic cell, fuel cell and supercapacitor. The optimal power flow in the hybrid microgrid component is developed using energy management system which consents control system to batteries, load and economic analysis with the input of electric grid. In this paper supercapacitor is which is directly connected to DC and provide fast response to load changing. DC voltage, current and hybrid microgrid is managed using the local control system. The power change in photovoltaic system is solved using energy storage system. The purpose of control method in hybrid microgrid is used to enhance the hybrid microgrid flexibility and generation of renewable resources and stored it in grid. The effectiveness and the flexibility of the proposed controller in energy management of hybrid microgrid system is simulated. The proposed energy management system provides high performance related to the existing energy management system.

Simulation-Based Optimization of Residential Energy Flows Using White Box Modeling by Genetic Programming

The development of energy management systems that optimize the electrical energy flows of residential buildings has become important nowadays. The optimization is formulated as a symbolic regression problem that is solved by genetic programming, which provides near optimal results while being highly performant during application. Additionally, the so-trained energy flow controllers are explainable and therefore address three of the current major disadvantages of most existing solutions. 260 controllers are trained to calculate the optimal gridfeed-in value for an inverter and are evaluated for their ability to minimize the energy costs and to support grid stability and battery lifetime. Additionally, they are compared to two existing energy management systems, a rule-based self consumption optimization and a linear model predictive controller. It is shown that this energy management system can significantly minimize energy costs compared to both reference systems by up to 58.25%, support grid stability and prolong battery lifetime by up to 76.48%.

OPTIMAL POWER MANAGEMENT SYSTEM: A CONCEPTUAL DESIGN APPROACH

Indian power management system is one among the largest power system networks in the world. India has a complex power transmission network which is monitored by multi-level integrated systems installed at many control levels. The Indian power sector is expected to grow both in its installed capacity and energy demand which makes it extremely essential to equip the country’s power grid with novel applications of smart grid technologies. A technologically advanced architecture of power system could be beneficial to address issues at micro level and improve flexibility and robustness of the system. This research highlights technical advancements which are in practice in different countries. A conceptual design framework has been proposed which can be integrated with the existing energy management system and thus could potentially help in an improvised efficient monitoring and control system. Thus, help resolve chances of cascaded outages leading to blackouts.

Enhanced Energy Management System With Corrective Transmission Switching Strategy—Part I: Methodology

The flexibility in transmission networks is not fully utilized in existing energy management systems (EMSs). Corrective transmission switching (CTS) is proposed in this two-part paper to enable EMS to take advantage of the flexibility in transmission systems in a practical way. This paper proposes the following two EMS procedures: first, Procedure-A connects real-time security-constrained economic dispatch (RT SCED) with real-time contingency analysis (RTCA), which is consistent with industrial practice; and second, Procedure-B, an enhanced version of Procedure-A, includes CTS in EMS with the proposed concept of branch pseudo limit used in RT SCED. Part-I of this paper presents the methodology, whereas Part-II includes detailed results analysis. It is demonstrated that Procedure-A can effectively eliminate the base case overloads and the potential post-contingency overloads identified by RTCA, and Procedure-B can achieve significant congestion cost reduction with consideration of CTS in RT SCED. Numerical simulations also illustrate that integrating CTS into RT SCED would improve social welfare.

Sensor-based ambient intelligence for optimal energy efficiency

Purpose – This paper aims to describe research work to create an innovative, and intelligent solution for energy efficiency optimisation. Design/methodology/approach – A novel approach is taken to energy consumption monitoring by using ambient intelligence (AmI), extended data sets and knowledge management (KM) technologies. These are combined to create a decision support system as an innovative add-on to currently used energy management systems. Standard energy consumption data are complemented by information from AmI systems from both environment-ambient and process ambient sources and processed within a service-oriented-architecture-based platform. The new platform allows for building of different energy efficiency software services using measured and processed data. Four were selected for the system prototypes: condition-based energy consumption warning, online diagnostics of energy-related problems, support to manufacturing process lines installation and ramp-up phase, and continuous improvement/optimisation of energy efficiency. Findings – An innovative and intelligent solution for energy efficiency optimisation is demonstrated in two typical manufacturing companies, within one case study. Energy efficiency is improved and the novel approach using AmI with KM technologies is shown to work well as an add-on to currently used energy management systems. Research limitations/implications – The decision support systems are only at the prototype stage. These systems improved on existing energy management systems. The system functionalities have only been trialled in two manufacturing companies (the one case study is described). Practical implications – A decision support system has been created as an innovative add-on to currently used energy management systems and energy efficiency software services are developed as the front end of the system. Energy efficiency is improved. Originality/value – For the first time, research work has moved into industry to optimise energy efficiency using AmI, extended data sets and KM technologies. An AmI monitoring system for energy consumption is presented that is intended for use in manufacturing companies to provide comprehensive information about energy use, and knowledge-based support for improvements in energy efficiency. The services interactively provide suggestions for appropriate actions for energy problem elimination and energy efficiency increase. The system functionalities were trialled in two typical manufacturing companies, within one case study described in the paper.

소비전력 최소화를 위한 빅데이터 환경에서의 공간기반 에너지 관리 시스템에 관한 연구

This paper proposed the method to reduce and manage the amount of using power by using the Self-Learning of inference engine that evolves through learning increasingly smart ways for each spaces with in the Space-Based Energy Management System (SEMS, Space-based Energy Management System) that is defined as smallest unit space with constant size and similar characteristics by using the collectible Big Data from the various information networks and the informations of various sensors from the existing Energy Management System(EMS), mostly including such as the Energy Management Systems for the Factory (FEMS, Factory Energy Management System), the Energy Management Systems for Buildings (BEMS, Building Energy Management System), and Energy Management Systems for Residential (HEMS, Home Energy Management System), that is monitoring and controlling the power of systems through various sensors and administrators by measuring the temperature and illumination.

스마트 그리드를 위한 소규모 전력에너지 관리 시스템 개발에 관한 연구

스마트 그리드는 기존에 발전소에서 전력을 일방적으로 공급하는 단방향 전력망에 정보기술을 접목하여 전력 공급자와 소비자가 양방향으로 실시간 정보를 교환함으로써 에너지 효율을 최적화하는 방식이다. 스마트그리드의 전력 관리 시스템은 동적인 가격제도와 함께 소비자들에게 전력사용에 대한 정보를 제공함으로써, 수요의 반응을 유도하고, 전력 계통의 투자와 운영에 있어 효율을 향상시키는데 있다. 하지만, 최근 전력 관리 시스템들은 실시간 가격 등 가격 제도에 주로 초점을 두고 있다. 본 논문에서는 가격 제도에 초점을 둔 기존 전력관리 시스템을 개선하여 전력 사용의 효율성에 초점을 둔 전력에너지 운영 관리 시스템을 제안한다. 전력 데이터는 배전반에 설치된 PMU(Phasor Measurement Units)를 통해 수집되며 데이터 마이닝 기법을 통한 분석 방법으로 효율성 높이고자 한다. 또한 전력 부족 및 과잉 공급 시 PMU와 양방향 통신을 통해 제어할 수 있도록 구현 및 실험하여 전력에너지 관리시스템의 효율성을 입증하였다. A smart grid is an electric-power grid that employs a new information technology.This technology makes it possible to exchange real-time energy information between suppliers and consumers, finally resulting in high energy efficiency. The energy management system in smart grid provides up to date information on electricity consumption as well as dynamic electricity price to consumers of smart grid system. However, the existing energy management systems only focus on pricing system, for example, real-time electricity prices. In this paper, we try to improve the existing energy management system and propose the energy management system that mainly focuses on the efficiency of electricity consumption. In the proposed management system, PMU(Phasor Measurement Units) installed in switchboards gathers electricity data in a real time. We also propose to use data mining method, which is applied to analyzed electricity data for improving energy efficiency. Also, the proposed energy management system is designed to efficiently control the electricity between PMU and management system in case of a shortage of electricity or surplus electricity.

Development of a self-adapting intelligent system for building energy saving and context-aware smart services

Recent advances in ubiquitous technologies facilitate context-aware systems which can offer situation-based services. Wireless sensor networks (WSNs) have become increasingly important in recent years due to their ability to monitor and manage situational information for various intelligent services in ubiquitous environments. However, existing energy management systems are not effectively implemented in home and building environments due to their architectural limitations, such as static system architecture and a finite battery lifetime. Therefore, in this paper, we propose a Self-adapting intelligent system used for providing building control and energy saving services in buildings. Our system consists of a gateway (selfadapting intelligent gateway) and a sensor (self-adapting intelligent sensor). In addition, we also propose an energy-efficiency self-clustering sensor network (ESSN) and a node type indicator based routing (NTIR) protocol that considers the requirements of WSNs, such as network lifetime and system resource management. In order to verify the efficiency of our system, we implemented our system in real test bed and conducted experiments. The results show that autonomous power saving using our system is approximately 16-24% depending on the number of SIS.

An Integrated Framework for Smart Microgrids Modeling, Monitoring, Control, Communication, and Verification

The microgrid (MG) paradigm is a new concept which is considered as a solution for addressing technical, economical, and environmental issues of modern power systems. The application of MG is the subject of extensive studies and experimental tests. It is recognized that there are a number of technical challenges concerning the operation, monitoring, control, and protection of MGs systems. In this respect, the rapid development of the information and communication technologies (ICTs) has opened the door for feasible and cost-effective solutions allowing more extensive intra- and interutility information exchange, diffusion, and open access to a wide range of real-time information. Consequently, the ICTs could represent a strategic tool in supporting effective MG operation. According to this statement, the paper proposes an advanced framework based on the service-oriented architectures for integrated MG modeling, monitoring, and control. The proposed framework is platform, language, and vendor independent, and thus it is an ideal candidate for an effective integration in existing energy management systems and distribution management systems (EMSs/DMSs).

Development of energy management system – Case study of Serbian car manufacturer

The procedure of development of energy management system applied to an existing company (Serbian car producer “Zastava”) is shown in the paper. The aim of the paper is to provide a guideline for entrepreneurs in metal-working industry in implementing energy management system. First of all, paper includes: critical analysis of existing energy management system (energy matrix), principles of effective energy management organization (with energy manager and energy team in its structure) and energy management politics. Based on the results of energy auditing and performed technological and economical feasibility studies several energy saving measures related to different energy sources (steam, hot water, compressed air, electricity and water) were proposed, implemented and valuated. The proposed measures are not exclusively related to car assembly industry; they can be easily applied to other metal-working facilities with minor modifications. Such energy management system reduces energy costs and increase profitability of a factory.

A model for strategic selection of feeder management systems: A case study

The move to integrating distribution management system (DMS) and feeder management system (FMS) in China is becoming the main trend in recent years, in addition to upgrading and rebuilding existing energy management system (EMS) and DMS. However, with increasing complexity in the social environments along with rapidly changing technologies, how to select a suitable contractor and a FMS project is becoming an important issue for electric power companies. This paper first briefly introduces FMS and then lists its critical success criteria. A model that applies a multi-criteria decision-making (MCDM) method, an analytic network process (ANP) associated with benefits, opportunities, costs and risks (BOCR), is constructed to help power companies to select the most suitable FMS project.

Operations management of new project development: innovation, efficient, effective aspects

The integration of distribution management systems (DMS) and feeder management systems (FMS) in China has become a trend in recent years, in addition to upgrading and rebuilding the existing energy management system and DMS. However, some management methods are different and contradictory, thus result in obstacles to innovation and effectiveness. Thus, firms still struggle to find effective process management that is associated with innovative project operations. In addition, there is no standard method to evaluate information technology (IT) projects, and at least 40% of IT projects realize no benefits. It is astonishing that none of the above-mentioned issues have been addressed or solved by previous literatures. In order to fill the vacancy, this paper first briefly introduces FMS and determines its critical success criteria, and then proposes suitable forms of organization for knowledge management. It also applies process management methods according to knowledge creation mode and maturity of the project. Finally, an analytic network process associated with benefits, opportunities, costs, and risks is constructed to compare the performance of different FMS projects with and without adopting the proposed methodology.

Who's watching the unattended substation [substation television system

The substation television system is a product of the combination of security protecting technology with the automation of electric power dispatch, the purpose of which is to enable a substation attended by a few people and capable of performing the functions of telemetry, telesignaling, telecontrol, and teleregulation to genuinely become an unattended one. In the construction of an unattended substation, what a power company is most worried about is whether the reliability of the primary and secondary equipment can satisfy the requirement for unattended operation. However, from the point of view of technological development, it is only natural for the first generation of the television system to come into being, which is capable of monitoring all aspects of the safe operation of an unattended substation while working in coordination with the existing energy management system (EMS). This article is concerned with the structure and function of a new generation of television system and two crucial techniques in its implementation, that is, the integrated transmission of multiple media information and the remote control over the unattended substation as well the prospects for the trend of the merger of the television system with the EMS.

Interfacing an Existing Energy Management System to a Newly Established Market Operations System

To support the deregulated energy markets, electric utilities and marketing entities are implementing new market operation systems to provide the necessary bid/offering applications, scheduling algorithms, and after-the-fact settlement tools. Utilities are integrating existing Energy Management Systems (EMS) that already provide some of the required tools and data with these new marketing operation systems. This integration work requires careful coordination of the interfaces between the Market Operating System and EMS. This paper identifies issues associated with these interfaces and presents guidelines leading to successful implementation.