Energy Management of Integrated Electric-gas Prosumers with Peer-to-Peer Trading: A GNE Approach

There are various approaches to energy and carbon management and the most appropriate approach is likely tochange over time. Selecting the appropriate approach is pivotal in determining how successful an organisation will be in achieving its energy and carbon management objectives. Over the last fifteen years, Gosford City Council has undergone numerous shifts in its approach to the management of energy and carbon across its operations. Council initially focused on reducing its carbon footprint, firstly by setting aspirational targets and followed by the setting of evidence based targets. In response to rising energy costs, Council shifted from a “carbon abatement” to an “energy management” focus in 2012. At this time, the sophistication of Council’s energy management program was vastly improved with the introduction of a corporate energy management information system and a revolving energy fund. In 2014, Council’s energy management program focused on “use less” and“pay less” levers. The first lever “use less” covered much the same ground as previous carbon abatement approaches, however, the second energy management lever, “pay less” unlocked significant additional value to Council. Pay less initiatives, such as energy procurement, load shifting, energy account management and bill validation resulted in energy cost savings of hundreds of thousands of dollars for Council. Council is now shifting from a tactical to a more strategic approach to energy management. An Energy Management Strategy is under development. The Energy Management Strategy will introduce an Energy Productivity Improvement Objective. This objective will focus on recognising the complete economic value of improved energy and carbon management. This should yield organisational productivity improvements and economic value in the local community. The strategy also introduces advanced energy metrics such as an energy cost index and asset class energy intensity metrics. The appropriate approach for Gosford City Council’s energy and carbon management has advanced in line with wider organisation objectives, values and maturity of its energy management systems.

This paper investigates the application of utility theory in decision-making related to energy use behavior and management practice in the energy sector. By conducting a systematic literature review, this study aims to understand the theoretical and practical applications of utility theory in optimizing energy consumption and management strategies. The review targets a comprehensive collection of academic works that apply utility theory to various aspects of energy use behavior and management decisions, including efficiency initiatives, renewable energy adoption, and sustainable infrastructure development. A systematic literature review methodology was adopted, which encompassed a rigorous selection process to identify relevant studies, followed by a detailed analysis of how utility theory has been employed to influence energy-related decisions in residential, commercial, and industrial settings. The review findings were synthesized to outline the implications for both policy and practice, highlighting the role of utility theory in guiding more efficient and sustainable energy management practices. Through this exploration, the paper provides a discussion on bridging the gap between economic theoretical models and practical energy management applications. It also offers insights into how decision-making influenced by utility theory can lead to enhanced energy efficiency and sustainability. The findings offer valuable guidance for policymakers and energy managers in designing and implementing energy systems and policies that maximize utility while considering environmental and economic impacts. This paper serves to advance the theoretical framework of utility theory and its practical application in energy management, facilitating better-informed strategies that align with global sustainability goals.

The energy efficiency gap is known as the difference between optimal level of energy efficiency and the actual level of achieved energy efficiency. Energy management has proven to further close the energy efficiency gap. Energy management may differ depending on whether it concerns a large, energy-intensive company or small and medium-sized enterprises (SMEs). SMEs are of high interest since they form a large share of the economy today. For SMEs, a lighter form of energy management, in the form of energy efficiency network participation, has proven to deliver sound energy efficiency impact, while for larger, energy-intensive firms, a certified energy management system may be more suitable. However, various barriers inhibit adoption of energy efficiency measures. While there is an array of research on barriers to and driving forces for energy efficiency in general, research on barriers to, and driving forces for, energy management is rare, one exception being a study of energy-intensive pulp and paper mills. This holds even more so for industrial SMEs. This paper aims to identify the barriers to, and drivers for, energy management in manufacturing SMEs. Results of this explorative study show that the top four barriers to energy management are lack of time/other priorities, non-energy-related working tasks are prioritized higher, slim organization, and lack of internal expert competences, i.e., mainly organizational barriers. The top four drivers for energy management are to reduce production waste, participation in energy efficiency networks, cost reduction from lower energy use, and commitment from top management. Furthermore, results show that energy management among the studied SMEs seems to not be as mature, even though the companies participated in an energy management capacity building program in the form of energy efficiency networks, which, in turn, shows a still largely untapped potential in the societal aim to reduce the energy efficiency and management gaps. The main contribution of this paper is a first novel attempt to explore barriers to, and drivers for, energy management among SMEs.

Energy efficiency and management practices are increasingly being integrated into sustainable finance frameworks as organizations seek to reduce energy consumption, costs, and emissions. However, comprehensive analysis of the implementation and impacts of energy audits and management under these frameworks has been limited. This research conducts an assessment of how energy auditing and management practices are being incorporated into sustainable finance policies, tools, and reporting methodologies. The study utilizes a mixed methods approach combining broad quantitative benchmarking and qualitative case studies. First, an extensive benchmarking framework is developed to assess and compare the integration of energy audit and management provisions across major sustainable finance frameworks, standards, and guidelines. Quantitative data is compiled and analyzed to identify strengths, gaps, and opportunities for improvement. Next, an in-depth qualitative case study analysis is conducted on a select group of organizations to develop a nuanced understanding of motivations, implementation challenges, and measurable impacts related to adopting energy management practices within sustainable finance commitments. Cases represent diverse sectors, geographies, and sustainable finance frameworks. Data collection involves sustainability reports, internal documents, and key informant interviews. This dual-pronged assessment methodology allows for a comprehensive analysis of the current landscape as well as targeted insights to inform the effective integration of energy management activities into sustainable finance efforts. The benchmarking provides a systematic overview of the field, while the case studies add a rich, practical understanding of real-world implementation. By evaluating integration depth, extent of implementation, motivations, challenges, and impacts, this study generates actionable intelligence to advance energy management as a key component of sustainable finance frameworks and commitments. The analysis provides both specific recommendations and a framework to inform future integration efforts by governments, standard setters, reporting organizations, and practitioners.

As a retailer between the energy suppliers and end users, the integrated energy service provider (IESP) can effectively coordinate the energy supply end and the energy use end by setting energy prices and energy management. Because most of the current research focuses on the pricing of electricity retailers, there are few studies on IESP energy pricing and management, which are still at the initial stage. At the same time, the existing research often does not consider the impact of demand response (DR) and uncertainties, such as natural gas and electricity wholesale prices, on the pricing of IESP. It is necessary to model the DR and uncertainties in the integrated energy system. Aiming at the inadequacy of the existing research and to address the energy pricing and management of IESP, this paper develops a two-stage stochastic hierarchical framework, which comprehensively considers the DR strategy of the user end, characteristics of the electricity/gas/heat storage and the uncertainties of electricity and gas wholesale prices. The proposed hierarchical model for energy pricing and management is a two-layer model: the upper layer is the problem of maximizing the benefits of IESP, and the lower layer is the problem of minimizing the energy cost of user agents. Through the complementary transformation, the linearization method and the strong duality principle in the optimization theory, the model is transformed into a mixed-integer linear programing (MILP) problem, which can be easily solved by the off-shelf commercial solver. Finally, the simulation results are provided to demonstrate the interactive operation between the IESP and user agent through energy prices setting, DR strategy and energy management.

Advances in new equipment, new processes, and new technology are the driving forces in improvements in energy management, energy efficiency, and energy cost control. Of all recent developments affecting energy management, the most powerful new technology to come into use in the last several years has been information technology (IT). The combination of cheap, high-performance microcomputers together with the emergence of high-capacity communication lines, networks, and the internet has produced explosive growth in IT and its application throughout our economy. Energy information and control systems have been no exception. IT and internet-based systems are the wave of the future. Almost every piece of equipment and almost every activity will be connected and integrated into the overall facility operation in the next several years. The internet, with the worldwide web has become quickly and easily accessible to all facility employees. It has allowed the development of many new opportunities for energy and facility managers to quickly and effectively control and manage their operations. The capability and use of IT and the internet in the form of web-based energy information and control systems continues to grow at a very rapid rate. New equipment and new suppliers appear almost daily, and existing suppliers of older equipment are beginning to offer new web-based systems. Facility managers, maintenance managers, and energy managers are all having to deal with this rapid deployment of web-based equipment and systems, and need to be prepared for current and future applications of internet-based technologies in their facilities. In some cases, facilities are developing their own information and control systems or at least subsystems, and are trying to understand how to connect and interface new IT equipment to their older energy management or facility management systems. The purpose of this article is to help prepare energy managers to understand some of the basic concepts and principles of IT. We hope that they can successfully apply IT to their facility, and have the knowledge to supervise the IT work of a consultant or a vendor. Knowing what is going on and what is involved is important information for energy managers if they are going to successfully purchase, install, and operate these complex, web-based energy information and control systems. Energy management is a very comprehensive area, and this article is the first in a series whose purpose is to address the most significant concepts and principles that the typical energy or facility manager might need. The emphasis of this series is on computer networking, use of facility operation databases, and sharing data using the web and the TCP/IP communications protocol. This first article will introduce basic principles, structures, and definitions needed for most facility IT applications.

The future of energy and technology management is being shaped by innovations, data-driven insights, and the development of smart solutions that aim to address global energy challenges while promoting sustainability. As the demand for energy continues to rise, there is a growing need for advanced technologies that optimize energy production, distribution, and consumption. Key innovations, such as renewable energy technologies, smart grids, and energy storage systems, are paving the way for more efficient and sustainable energy management. The integration of data analytics and Internet of Things (IoT) devices allows for real-time monitoring and predictive analytics, enabling better decision-making in energy systems. These technologies are driving the shift towards decentralized energy models, where consumers can generate, store, and manage their energy consumption autonomously. Data-driven insights are crucial in optimizing energy usage and enhancing system reliability. Machine learning and artificial intelligence (AI) are being utilized to predict energy demands, identify inefficiencies, and optimize operational processes in real-time. By leveraging big data, energy managers can gain a deeper understanding of consumption patterns, enabling the creation of tailored energy solutions that reduce waste and lower costs. Furthermore, the development of smart cities and smart homes is transforming how energy is consumed, with interconnected systems that adjust energy use based on real-time conditions. As energy management becomes more sophisticated, the role of technology in developing smart solutions for energy efficiency and sustainability will continue to expand. The convergence of AI, IoT, and renewable energy will play a critical role in building a resilient and low-carbon energy infrastructure. The future of energy and technology management is not only about meeting the growing energy demand but also about achieving environmental sustainability and operational efficiency. Embracing these innovations will be key to unlocking the full potential of energy systems in the years ahead.

Over the five-year period (2002-2006) the Oklahoma State University Industrial Assessment Center (IAC) performed energy assessments for 106 different clients, writing 835 recommendations, for a total of $23,937,099 in potential estimated annual savings. IAC clients served consisted of small and medium-sized manufacturers ranging from food manufactures to foundries. The OSU IAC served clients in Oklahoma, Kansas, Missouri, Arkansas, and Texas. In addition to client service, student training and instruction was a major accomplishment. The OSU IAC employed (and trained) 12 baccalaureate-level students, 17 masters-level graduate students, and 7 doctoral-level graduate students. Most are practicing in the energy management area. Training was focused on both energy assessment and safety. Safety training was both center-based training as well as on-site training. Energy management related training was focused on classroom (for academic credit) work at both the undergraduate and graduate level. IEM 4923 (Energy and Water Management) was developed to serve both the IAC as well as non-IAC students. It was delivered once per year, with enrollments of typically 10 to 20 students. This course was required for IAC student employees, both undergraduate and graduate. This course was patterned after the AEE CEM (five-day) course for practicing professionals. IEM 4923 required each student more » to attend at least one on-site assessment and write at least one recommendation for their client’s report. Hence, a hands-on approach was practiced. Advance level courses were used to train graduate students. Two courses played major roles here: IEM 5923 (Advanced Energy and Water Management) and IEM 5943 (Hazardous Material and Waste). Graduate student participation in these courses helped the IAC to gain additional perspectives in on-site assessment and resulting recommendations. Numerous hands-on demonstration/training was conducted by directors and graduate students in order to gain proficiency in using the combustion analyzer, IR camera, logging equipment, light metering equipment, and other equipment. Instruction included usage and basic maintenance. While undergraduate students worked with the coursework and on-the-job training, graduate students were expected to do more. A typical MS student was required to complete a 3-hour independent study in some interesting facet of energy management under the supervision of a director. PhD students were expected to complete from three to six hours of independent study work in the energy management field, as well as center their dissertation research in the general area of energy/productivity/quality management. During the project period, two PhDs were completed, with several more near completion. « less

Although smart grids are regarded as the technology to overcome the limits of nowadays power distribution grids, the transition will require much time. Dynamic pricing, a straightforward implementation of demand response, may provide the means to manipulate the grid load thus extending the life expectancy of current technology. However, to integrate a dynamic pricing scheme in the crowded pool of technologies, available at demand side, a proper energy manager with the support of a pricing profile forecaster is mandatory. Although energy management and price forecasting are recurrent topics, in literature they have been addressed separately. On the other hand, in this work, the aim is to investigate how well an energy manager is able to perform in presence of data uncertainty originating from the forecasting process. On purpose, an energy and resource manager has been revised and extended in the current manuscript. Finally, it has been complemented with a price forecasting technique, based on the Extreme Learning Machine paradigm. The proposed forecaster has proven to be better performing and more robust, with respect to the most common forecasting approaches. The energy manager, as well, has proven that the energy efficiency of the residential environment can be improved significantly. Nonetheless, to achieve the theoretical optimum, forecasting techniques tailored for that purpose may be required.

One of the latest innovations in the industrial environment was the emergence of Industry 4.0. Along with numerous challenges, there are many chances for companies in it. Besides automation, energy efficiency and energy flexibility is becoming increasing important. Because of the planned phasing-out of nuclear power and high prices for energy, it is important for companies to reduce their energy consumption in order to reduce cost and stay compatible in market place. Therefore strategic energy management plays an important role in overcoming these obstacles. Implementation of energy management is often based on standards and norms with the DIN EN ISO 50001 being the most important. Energy monitoring is a key factor for the successful execution of energy management. For energy monitoring of Industry 4.0 production plants, a cloud based energy monitoring and management system was developed. This solution allows users to monitor their production in real time enabling them a possibility of condition monitoring, energy flexible planning of production based on historic data and energy management along with load management. The detailed concept of the cloud based totally integrated energy management system, beginning with data acquisition to data analysis and visualization is presented in this paper.

A review of barriers to and driving forces for improved energy efficiency in Swedish industry– Recommendations for successful in-house energy management

Energy audit and management of an industrial site based on energy efficiency, economic, and environmental analysis

Effective energy monitoring, reporting, and management strategies for wise energy usage is one of the objectives of Energy Management. Numerous researches have highlighted the extremely good profits of imposing business and industrial energy management measures. Notably, a number of those research display that extra financial savings may be found out in growing international locations. Unfortunately, industries in developing countries like Nigeria are lagging behind in the adoption of energy management measures and as such missing the benefits of implementation. This research study sets out to evaluate the energy consumption performance in manufacturing industry in order to showcase the gains of energy management in manufacturing industry. Data on weekly energy consumption (in MW) and weekly production of sugar (in Bags, 50kg/bag) were obtained from a sugar manufacturing company in southwestern Nigeria. Energy management data analysis and modeling was done using linear regression plot of energy consumption against production; energy intensity plot and cumulative sum of difference (CUSUM) plot respectively. The energy performance model was obtained from the linear regression plot and two parameters namely incremental energy consumed per bag (per kg) of sugar produced and “no-production” energy consumption are the performance measures. The model showed that the incremental energy consumed per bag (or per kg) is 0.00008 MW/Bag or 80W/Bag or 1600W/kg while the no-production energy consumption is 211.73 MW. Results also reveals that the no-production activities consumed energy more when compared with the actual energy used for production. CUSUM identified five periods when energy consumption gave higher and increased production thereby showing that CUSUM charts are more effective in detecting changes in energy consumption. The research study has shown how energy management data analysis can be helpful in taking decision that will enhance increased production and reduction of no-production energy consumption activities.
 Keywords: Energy management, CUSUM, Performance model, Energy, No-production energy consumption

Energy management in Lucknow city

A distributed energy monitoring network system based on data fusion via improved PSO