Commercial Users Research Articles

Baseline Load Forecasting for Demand Response Taking Meteorological Factors into Account

To conduct baseline load forecasting for commercial building users participating in demand response, this paper proposes a demand response baseline load forecasting method that takes meteorological factors into account. Using the principal component analysis, the meteorological indicators contributing more than 80% to the baseline load are selected as the reference data for forecasting neural network baseline load. The isolated forest algorithm and KNN algorithm are used to identify the abnormal data and to fill in the missing data, and the data with different attributes are partially “decoupled.” The two parts of the decoupled data are separately used for neural network load forecasting, and the total baseline load of users is obtained after merging. From these results, it is obvious that the proposed method can effectively improve the forecasting accuracy of the baseline load of the algorithm.

Data sharing in agricultural supply chains: Using semantics to enable sustainable food systems

The agrifood system faces a great many economic, social and environmental challenges. One of the biggest practical challenges has been to achieve greater data sharing throughout the agrifood system and the supply chain, both to inform other stakeholders about a product and equally to incentivise greater environmental sustainability. In this paper, a data sharing architecture is described built on three principles (a) reuse of existing semantic standards; (b) integration with legacy systems; and (c) a distributed architecture where stakeholders control access to their own data. The system has been developed based on the requirements of commercial users and is designed to allow queries across a federated network of agrifood stakeholders. The Ploutos semantic model is built on an integration of existing ontologies. The Ploutos architecture is built on a discovery directory and interoperability enablers, which use graph query patterns to traverse the network and collect the requisite data to be shared. The system is exemplified in the context of a pilot involving commercial stakeholders in the processed fruit sector. The data sharing approach is highly extensible with considerable potential for capturing sustainability related data.

Operating peer-to-peer electricity markets under uncertainty via learning-based, distributed optimal control

Towards the global endeavor of clean energy transition, there is a rapid development of distributed energy resources installed in the premises of residential or commercial users, enabling them to act as flexible energy prosumers. Empowering prosumers is envisioned as a catalytic development for modern energy economies, with recent research, as well as innovation and policy actions, pointing to the promising direction of decentralized energy markets, where active energy prosumers exchange energy in a decentralized fashion. Despite the vast amount of recent research on prosumer-centric peer-to-peer (p2p) energy markets, only a small subset of studies accounts for managing the inherent uncertainty of prosumers’ flexible demands.In this paper, we consider the problem of controlling the decisions of energy prosumers’ within a p2p exchange network. The multi-bilateral economic dispatch is formulated as an optimal control problem. The proposed solution is based on a direct lookahead policy, effectively addressing the issues of dimensionality and local constraint satisfaction. Experimental simulations demonstrate the method’s efficiency and the system’s behavior. The proposed formulation and method is shown to effectively address the operation of p2p markets under uncertainty, closely tracking the performance of the (full information) optimal-in-hindsight benchmark.

Study on the Fitting Method of Power User Load Curve Under the Condition of Spot Operation

With the acceleration and deepening of the power market reform, the National Development and Reform Commission has issued power system reform documents to promote all industrial and commercial users to enter the power market. For the spot pilot area, the clearing and settlement time is required to be more accurate. Except for a few large industrial users, a wide range of small and medium-sized users and residents do not have the meter conditions for time-sharing measurement, and the investment in large-scale transformation of measuring equipment is huge, so the settlement basis must be obtained by fitting. This paper proposes a reverse derivation method of the user load curve. First, deducting the user curve with metering conditions from the load curve, and then calculating different types of user curves by adding weight coefficient fitting. At the same time, it proposes a method to deal with fitting deviation, which realizes the fitting of user curves without time-sharing meters, supports the needs of spot market settlement, and effectively promotes the entry of all industrial and commercial users into the market.

Application of Mobile Energy Storage System in Dynamic Capacity Increasing Scenario

Aiming at the problem of insufficient capacity caused by the intermittent peak power consumption of some small and medium-sized industrial and commercial power users, the electrochemical energy storage on the customer side can exert a dynamic capacity increase effect, while taking into account peak valley arbitrage and emergency power protection functions. The mobile energy storage system further increases the flexibility of the energy storage system and the applicability of scenarios. It can be matched with the smart cloud platform of energy storage on the customer side. The business model under the application scenario has a good market promotion prospect. Through the actual case analysis, it is proved that the system and the model meet the theoretical expectation.

Feature level fine grained sentiment analysis using boosted long short-term memory with improvised local search whale optimization.

In the modern era, Internet-based e-commerce world, consumers express their thoughts on the product or service through ranking and reviews. Sentiment analysis uncovers contextual inferences in user sentiment, assisting the commercial industry and end users in understanding the perception of the product or service. Variations in textual arrangement, complex logic, and sequence length are some of the challenges to accurately forecast the sentiment score of user reviews. Therefore, a novel improvised local search whale optimization improved long short-term memory (LSTM) for feature-level sentiment analysis of online product reviews is proposed in this study. The proposed feature-level sentiment analysis method includes 'data collection', 'pre-processing', 'feature extraction', 'feature selection', and finally 'sentiment classification'. First, the product reviews given from different customers are acquired, and then the retrieved data is pre-processed. These pre-processed data go through a feature extraction procedure using a modified inverse class frequency algorithm (LFMI) based on log term frequency. Then the feature is selected via levy flight-based mayfly optimization algorithm (LFMO). At last, the selected data is transformed to the improvised local search whale optimization boosted long short-term memory (ILW-LSTM) model, which categorizes the sentiment of the customer reviews as 'positive', 'negative', 'very positive', 'very negative', and 'neutral'. The 'Prompt Cloud dataset' is used for the performance study of the suggested classifiers. Our suggested ILW-LSTM model is put to the test using standard performance evaluation. The primary metrics used to assess our suggested model are 'accuracy', 'recall', 'precision', and 'F1-score'. The proposed ILW-LSTM method provides an accuracy of 97%. In comparison to other leading algorithms, the outcome reveals that the ILW-LSTM model outperformed well in feature-level sentiment classification.

MP51-02 AQUABLATION POSTOPERATIVE BLEEDING RISK REDUCTION

You have accessJournal of UrologyCME1 Apr 2023MP51-02 AQUABLATION POSTOPERATIVE BLEEDING RISK REDUCTION Dean Elterman, Steven A. Kaplan, Lori Lerner, Brian Helfand, Mihir Desai, Neil Barber, Rick Popert, Philip Charlesworth, and Thorsten Bach Dean EltermanDean Elterman More articles by this author , Steven A. KaplanSteven A. Kaplan More articles by this author , Lori LernerLori Lerner More articles by this author , Brian HelfandBrian Helfand More articles by this author , Mihir DesaiMihir Desai More articles by this author , Neil BarberNeil Barber More articles by this author , Rick PopertRick Popert More articles by this author , Philip CharlesworthPhilip Charlesworth More articles by this author , and Thorsten BachThorsten Bach More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003299.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Aquablation was originally studied in two FDA clinical trials spanning the years of 2015-2017 (WATER in prostates ≤80 mL, WATER II in prostates ≥80 mL). Aquablation was granted approval by FDA in December of 2017. Since then, commercial users have adopted a refined focal cautery approach for hemostasis. METHODS: Consecutive, commercial patients undergoing Aquablation from Asia, Europe, and North America were evaluated for bleeding risk of transfusion and takeback over the last 4 years. The source for the reported bleeding events was the FDA MAUDE database that requires manufactures to report global incidents. RESULTS: 13,447 Aquablation cases were performed with a mean prostate size of 90 mL (range 12 to 535 mL). Following the introduction of the focal bladder neck cautery protocol in January 2020, Figure 1 demonstrates a remarkable decline in bleeding risk requiring an intervention (either a transfusion, takeback for cautery, or takeback for clot evacuation). In 2021 and 2022, the risk of transfusion has reduced to 0.3% and 0.2%, respectively. CONCLUSIONS: Aquablation has leveraged imaging and robotics to allow surgeons to treat the a broad range of prostate sizes. However, early learnings in the development of the procedure, surgeons realized a standardized hemostasis technique was nececessry. Following the adoption of the standardized protocol, the bleeding risk has been reduced by 10-fold and allowing some surgeons the option of day-case Aquablation. Source of Funding: Not applicable © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e692 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Dean Elterman More articles by this author Steven A. Kaplan More articles by this author Lori Lerner More articles by this author Brian Helfand More articles by this author Mihir Desai More articles by this author Neil Barber More articles by this author Rick Popert More articles by this author Philip Charlesworth More articles by this author Thorsten Bach More articles by this author Expand All Advertisement PDF downloadLoading ...

Practical Distributed Control for Cooperative Multicopters in Structured Free Flight Concepts

Unmanned Aerial Vehicles (UAVs) are now becoming increasingly accessible to amateur and commercial users alike. Several types of airspace structures have been proposed in recent research, which include several structured free flight concepts. In this paper, for simplicity, distributed coordination of the motions of cooperative multicopters in structured airspace concepts is focused on. This is formulated as a free flight problem, including convergence to destination lines/planes and inter-agent collision avoidance. The destination line of each multicopter is known a priori. Further, Lyapunov-like functions are designed elaborately, while formal analysis and proofs of the proposed distributed control are given to show that the free flight control problem can be solved. What is more, by the proposed controller, a multicopter can keep away from another as soon as possible once it enters the safety area of another one. Simulations and experiments are given to show the effectiveness of the proposed method.

Анализ протоколов безопасности на базе системы распространения лицензируемого контента

In recent years, the number of cyberattacks has increased significantly. Most enterprises need reliable protection of the intracorporate networks. Intrusion prevention systems allow timely and automatic response to threats of various kinds that cannot be identified by firewalls, anti-viruses and other security systems. Many companies are represented on the market, providing their signatures to implement intrusion prevention systems developed by manufacturers of network equipment or personal security. There is a need to preserve the confidentiality of these rules with the implementation of the possibility of application on devices commercial users. That’s why systems for the distribution of licensed content to consumer devices are being developed. However, it is necessary to ensure a high level of security of such systems, to avoid leaks of classified data provided by third-party vendors.

KRIMINALISASI PEKERJA SEKS KOMERSIAL MELALUI ONLINE (Putusan PN SLEMAN Nomor 564/Pid.Sus/2020/PN Smn)

The rampant practice of prostitution in Indonesia needs to get serious attention considering that so far the practice of prostitution has not have a clear rule of law. So far, positive law in Indonesia only provides punishment for service providers (pimps) only. Meanwhile, commercial sex workers and service users cannot be ensnared by law. The impact of this causes the practice of prostitution to continue to thrive among the community. The research method that the author uses is the normative juridical method, meaning that the data used consists of primary, secondary, and tertiary legal materials. As for the results of the study,that the criminalization of commercial sex workers through online according to positive law in Indonesia by referring to the rules regarding online prostitution outside the Criminal Code is found in Article 2 paragraph (1) of Law no. 21 of 2007 concerning the Crime of Trafficking in Persons, Article 30, Article 33, Article 35 of Law No. 44 of 2008 concerning Pornography, and Article 27 of the ITE Law, but absolutely the commercial sex workers can be held criminally liable using the ITE Law.

Price freezes and gas pass-through: an estimation of the price impact of electricity market restructuring

This article examines the impact of market restructuring on retail prices, using the restructuring of the electricity industry as a case study. Utilizing synthetic control as an estimation strategy, this paper finds retail competition reduced retail prices across all sectors by an average of $1.5/MWh, relative to their counterfactual outcome. On average, prices fell for residential and commercial users and rose for industrial users. The price differential is consistent with the enactment of price ceilings and increased pass-through of changes in the price of natural gas.

Solutions for the commercialization challenges of Horizon Europe and earth observation consortia: co-creation, innovation, decision-making, tech-transfer, and sustainability actions

European Community (EC) Horizon-funded projects and Earth Observation-based Consortia aim to create sustainable value for Space, Land, and Oceans. They typically focus on addressing Sustainable Development Goals (SDGs). Many of these projects (e.g. Commercialization and Innovation Actions) have an ambitious challenge to ensure that partners share core competencies to simultaneously achieve technological and commercial success and sustainability after the end of the EC funds. To achieve this ambitious challenge, Horizon projects must have a proper governance model and a systematized process that can manage the existing paradoxical tensions involving numerous European partners and their respective agendas and stakeholders. This article presents the VCW-Value Creation Wheel (Lages in J Bus Res 69: 4849–4855, 2016), as a framework that has its roots back in 1995 and has been used since 2015 in the context of numerous Space Business, Earth Observation, and European Community (EC) projects, to address complex problems and paradoxical tensions. In this article, we discuss six of these paradoxical tensions that large Horizon Consortia face in commercialization, namely when managing innovation ecosystems, co-creating, taking digitalization, decision-making, tech-transfer, and sustainability actions. We discuss and evaluate how alliance partners could find the optimal balance between (1) cooperation, competition, and coopetition perspectives; (2) financial, environmental, and social value creation; (3) tech-push and market-pull orientations; (4) global and local market solutions; (5) functionality driven and human-centered design (UX/UI); (6) centralized and decentralized online store approaches. We discuss these challenges within the case of the EC H2020 NextLand project answering the call for greening the economy in line with the Sustainable Development Goals (SDGs). We analyze NextLand Online Store, and its Business and Innovation Ecosystem while considering the input of its different stakeholders, such as NextLand’s commercial team, service providers, users, advisors, EC referees, and internal and external stakeholders. Preliminary insights from a twin project in the field of Blue Economy (EC H2020 NextOcean), are also used to support our arguments. Partners, referees, and EC officers should address the tensions mentioned in this article during the referee and approval processes in the pre-grant and post-grant agreement stages. Moreover, we propose using the Value Creation Wheel (VCW) method and the VCW meta-framework as a systematized process that allows us to co-create and manage the innovation ecosystem while engaging all the stakeholders and presenting solutions to address these tensions. The article concludes with theoretical implications and limitations, managerial and public policy implications, and lessons for Horizon Europe, earth observation, remote sensing, and space business projects.

Economic evaluation of solar PV electricity prosumption in Ghana

Residential and commercial facility users are looking for ways to reduce their energy bills; this has resulted in nano and micro solar energy production in the form of electricity prosumption in contemporary times. Several technical factors characterise rooftop solar projects informing the decision to go solar. Amongst these factors are the solar energy available from the PV system, self-consumption ratio and overall system efficiency. However, from the investor's viewpoint, the most critical factor is the economic viability of the proposed project. Since energy economics is vital to investors, the paper seeks to analyse the economics (financial feasibility and profitability) associated with different types of prosumers in Ghana's residential and commercial classes. The net present value, internal rate of return, profitability index, and discounted payback were the economic indicators used to appraise Ghana's financial feasibility and profitability of electricity prosumption. The study shows that electricity prosumption in Ghana is worth investing in. The best investment option in the residential and commercial classes is the prosumers with grid integration and without storage (type 2). In the residential tariff class, the best investment option is the prosumers, whose energy demands are between 301 kWh and 600 kWh.

Simulation‐data‐driven load disaggregation based on multi‐channel neural network for industrial and commercial users

AbstractThe immeasurable energy‐saving potential of industrial parks and commercial buildings with unprecedented growth in scale and quantity can be well exploited by load disaggregation, a promising technique for demand‐side refinement management. However, traditional load disaggregation studies mainly focus on residential users and neglect the collection and analysis of industrial and commercial loads. This study employs a simulated response model of versatile load categories with voltage‐dependent load functions to overcome the unavailability of industrial and commercial datasets. Specially, a weighting factors allocation method considering probability statistics of power consumption distribution characteristics is proposed to construct a typical daily multi‐type load aggregation model. Furthermore, an intelligent load disaggregation strategy is developed based on a multi‐channel neural network to constructively improve multi‐feature tracking and convergence efficiency. Finally, the simulation results of the detailed study case confirm the tractability and effectiveness of the proposed approach to carry out load identification among multi‐type users, with an accuracy of 94.9% and errors of individual categories controlled between 3.32% and 10.686%. Moreover, additional interference tests demonstrate that the developed model has superiority over common load disaggregation structures, with better tolerance to exceptional voltage fluctuation and noise.

Energy Tariff Policies for Renewable Energy Development: Comparison between Selected European Countries and Sri Lanka

This article is written within the European Project “THREE-Lanka” which has the aim of modernizing the higher education related to Renewable Energy (RE) in Sri Lanka. The paper presents the outcomes of analysing various incentive schemes to stimulate RE development. In Europe, there was substantial growth in RE installation through generous incentives in the first years. Then, to regulate this growth, in recent years, the auction system has been introduced to improve the competition among companies that install RE plants. In Sri Lanka, on the other hand, the main energy tariff policies focus on the spread of PhotoVoltaics (PV) through contributions based on the electricity fed into the grid. This paper provides an updated view of the evolution of the energy tariff policies in the relevant European countries with respect to Sri Lanka, covering some recent policy developments. Within the Sri Lankan framework, four case studies involving residential, commercial, and industrial users are outlined to suggest better mechanisms (in the case of not adequate current incentive tariff) for supporting the deployment of grid-connected PV systems in a wide power range. Such knowledge transfer in the THREE-Lanka project will demonstrate the enormous potential RE capacity in a developing country, still depending on fossil fuels but willing to follow the path towards sustainability.

RF Systems on Chip and Mixed-Signal Front-End Devices: Game-Changing RF Technologies for Space Applications

Growing interest in the commercialization of space (NewSpace) is leading to increased acceptance of commercial off-the-shelf (COTS) electronics and thus enabling use in space of the latest technologies developed for terrestrial applications. This opens new capabilities for applications in space missions. RF communication via satellites has been established for decades; traditionally used for military applications, it is becoming increasingly important for commercial users. Today, global connectivity and access to the Internet has never been so important, and the demand for worldwide connectivity increases significantly each year. Space-based Internet access is especially important for areas with poor terrestrial infrastructure, such as Africa and Antarctica. There are already geostationary-Earth orbit (GEO)-stationary-located satellites available such as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Inmarsat</i> or low-Earth orbit (LEO) satellite constellations like Iridium, which provide almost-global access to the Internet, but they are either very expensive or have low data rates and long latencies, so they are not very attractive. New solutions with high data rates, low latencies, and affordable fees are currently in development, such as StarLink, with its giga constellation <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> , and Amazon’s Project Kuiper <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> , <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref> , <xref ref-type="bibr" rid="ref5" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[5]</xref> . So it is true: there really has been a change in the market with the NewSpace Era. With NewSpace, or in other words, the commercialization of space, traditional space missions with high-quality assurance requirements, very long design and manufacturing times, and extraordinary costs may become obsolete at a certain point, at least when it comes to commercial services like satellite-based Internet access. To decrease the lead time and costs of such missions, satellite designers and manufacturers need to rely on commercially available electronics, namely, COTS devices, which are usually much cheaper and have better performance and shorter lead times compared to space-qualified parts. In terms of performance, COTS devices have great benefits over space-qualified parts simply because the design, development, and qualification processes for space parts are very complex and take years before they are qualified and available for the market. It is likely that state-of-the-art space-qualified parts are 10 years behind what we currently have available for terrestrial applications, such as for the automotive or industrial markets <xref ref-type="bibr" rid="ref6" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[6]</xref> . One obvious reason is certainly that electronic parts manufacturers develop products for certain markets, and space is yet not one of the biggest or most attractive markets. But this has already started changing and big players such as Texas Instruments and Analog Devices are moving forward with the NewSpace wave and establishing ever-more products for commercial space applications. Truly, using state-of-the art electronics is not only of interest for the space-based Internet, there are also other space-related applications that can clearly benefit from using the latest technologies.

A Survey on RISC-V-Based Machine Learning Ecosystem

In recent years, the advancements in specialized hardware architectures have supported the industry and the research community to address the computation power needed for more enhanced and compute intensive artificial intelligence (AI) algorithms and applications that have already reached a substantial growth, such as in natural language processing (NLP) and computer vision (CV). The developments of open-source hardware (OSH) and the contribution towards the creation of hardware-based accelerators with implication mainly in machine learning (ML), has also been significant. In particular, the reduced instruction-set computer-five (RISC-V) open standard architecture has been widely adopted by a community of researchers and commercial users, worldwide, in numerous openly available implementations. The selection through a plethora of RISC-V processor cores and the mix of architectures and configurations combined with the proliferation of ML software frameworks for ML workloads, is not trivial. In order to facilitate this process, this paper presents a survey focused on the assessment of the ecosystem that entails RISC-V based hardware for creating a classification of system-on-chip (SoC) and CPU cores, along with an inclusive arrangement of the latest released frameworks that have supported open hardware integration for ML applications. Moreover, part of this work is devoted to the challenges that are concerned, such as power efficiency and reliability, when designing and building application with OSH in the AI/ML domain. This study presents a quantitative taxonomy of RISC-V SoC and reveals the opportunities in future research in machine learning with RISC-V open-source hardware architectures.

Research on Industrial and Commercial User-Side Energy Storage Planning Considering Uncertainty and Multi-Market Joint Operation

With the continuous development of the Energy Internet, the demand for distributed energy storage is increasing. However, industrial and commercial users consume a large amount of electricity and have high requirements for energy quality; therefore, it is necessary to configure distributed energy storage. Based on this, a planning model of industrial and commercial user-side energy storage considering uncertainty and multi-market joint operation is proposed. Firstly, the total cost of the user-side energy storage system in the whole life cycle is taken as the upper-layer objective function, including investment cost, operation, and maintenance cost. The lower layer takes the economy and environment of energy storage operation as the goal, and considers the ancillary service market revenue, demand response constraints, and operational constraints. Secondly, considering the uncertainty of the power market price, and based on the robust optimization theory, the robust transformation is carried out to effectively deal with the impact of uncertain variables on the system operation. Finally, the model is verified in a typical IEEE 30-node system. The results show that the uncertainty of renewable energy will affect the optimal location and capacity of energy storage. From the results of energy storage location, energy storage will be configured in the important transmission nodes and renewable energy power generation access nodes in the power system.

Cost optimization in cloud environment based on task deadline

The popularity of cloud and fog services has raised the number of users exponentially. Main advantage of Cloud/fog infrastructure and services are crucial specially for commercial users from diverse areas. The variety of service requests with different deadlines makes the task of a service broker challenging. The fog and cloud users always lookfor a suitable compromise between cost and quality of service in terms of response time therefore, the cost optimization is vital for the cloud/fog service providers to capture the market. In this paper an algorithm, Cost Optimization in the cloud/fog environment based on Task Deadline (COTD) is proposed that optimizes cost without compromising the response time. In this algorithm the task deadline is considered as a constraint and an appropriate data center for task processing is selected. The proposed algorithm is suitable for runtime decision making due to its low complexity. The proposed algorithm is evluated using a well-known simulation tool Cloud Analyst. Our comprehensive testbed simulations show that COTD outperforms the existing schemes, Service Proximity Based Routing and Performance-Optimized Routing. The proposed algorithm successfully minimizes the cost by 35% on average while maintaining the response time.

Overview of the Global Electricity System in Oman Considering Energy Demand Model Forecast

Lately, in modern smart power grids, energy demand for accurate forecast of electricity is gaining attention, with increased interest of research. This is due to the fact that a good energy demand forecast would lead to proper responses for electricity demand. In addition, proper energy demand forecast would ensure efficient planning of the electricity industry and is critical in the scheduling of the power grid capacity and management of the entire power network. As most power systems are been deregulated and with the rapid introduction and development of smart-metering technologies in Oman, new opportunities may arise considering the efficiency and reliability of the power system; like price-based demand response programs. These programs could either be a large scale for household, commercial or industrial users. However, excellent demand forecasting models are crucial for the deployment of these smart metering in the power grid based on good knowledge of the electricity market structure. Consequently, in this paper, an overview of the Oman regulatory regime, financial mechanism, price control, and distribution system security standard were presented. More so, the energy demand forecast in Oman was analysed, using the econometric model to forecasts its energy peak demand. The energy econometric analysis in this study describes the relationship between the growth of historical electricity consumption and macro-economic parameters (by region, and by tariff), considering a case study of Mazoon Electricity Distribution Company (MZEC), which is one of the major power distribution companies in Oman, for effective energy demand in the power grid.