Smart Grid Technologies Research Articles

Preface

International Conference on Energy Utilization and Automation originates from 2022 and has attracted promising researchers who are developing new directions in the field of energy utilization and automation. The 2023 2nd International Conference on Energy Utilization and Automation (ICEUA 2023), held via virtual form in Sanya, China from February 10th to 12th, 2023, is meant to unite researchers, professional experts, professors and academic staff as well as a wide range of participants of professional community from China and other countries concerned.The development of energy engineering and automation technology conforms to the national policy requirements of energy conservation and emission reduction, as well as renewable energy and clean energy development, and accelerates the development of energy industry, especially the development of large-scale utilization of solar energy and wind energy, power generation technology, smart grid and energy-saving technology. Focusing on the research fields of “energy development and utilization, energy conversion, chemical material preparation, electric power, automation and electrical engineering, automation engineering”, ICEUA 2023 provided an international exchange opportunity for about 80 related practitioners worldwide to share their professional experience, discuss the new development of disciplines, and display their research achievements.Highly eventful program of the Conference, the list of well-established organizations-participants and devoted engagement of many colleagues throughout all the stages of Conference preparation instill confidence in practical importance of mutual initiative. The framework of the Conference comprises keynote speeches, oral presentations, and academic investigation, discussing open and significant problems facing energy utilization, proposing innovative ideas and approaches to solution of the problems, and considering the new possibilities of application and development of cutting-edge energy utilization and automation.The Conference has become one of the venues for demonstrating scientific achievements of international class by leading scientists and young scholars and would facilitate the strengthening of academic cooperation, meanwhile the Conference proceedings would be expressed in the form of international scientific publishing. Various topics of the papers, gone through a vigorous peer review process, are covered in the proceedings, including: Carbon Capture and Storage, High Voltage Circuits, Power Electronics, Automation Technology Applications, Automatic Control Application Theory, etc.On behalf of the Conference Organizing Committee, we would like to thank the referees for their efficient and thoughtful actions. We are grateful to the members of the Technical Program Committee for their efforts in making and shaping the program for ICEUA 2023. Particularly, we acknowledge the publishing support from the members of Journal of Physics: Conference Series.We hope that the future ICEUA will be as successful and stimulating, as indicated with the contributions presented in this volume.The Committee of ICEUA 2023List of Committee Member are available in the pdf.

A Non-invasive Load Identification Method Based on V-I Trajectory Mixing Feature

Non-invasive load decomposition technology is an important part of the smart grid technology system. Aiming at the problem that traditional methods cannot accurately identify household loads containing high-order harmonics, a load identification method based on V-I trajectory matrix-power and high-order harmonics multi-feature fusion was proposed. First, the V-I trajectories, power characteristics, and harmonic characteristics of 11 typical household loads are analyzed, and a hybrid feature matrix construction method based on pixel image transformation is proposed. Through binary coding transformation, the power and high-order harmonic characteristics of the load are fused with the basic V-I pixel trajectory, enriching the characteristic information of the sample. Second, a recognition algorithm based on Gaussian Mixture Model (GMM) and Support Vector Machine (SVM) is established, and the probability distribution of the two algorithms is fused to generate the final recognition result. Finally, the Plug Level Appliance Identification Dataset (PLAID) was used to verify the proposed method, and the accurate identification rate of various household loads was over 93%. Experimental results show that the proposed method can accurately identify household load, including high harmonic load.

Efficient Integration of Renewable Energy for Electric Vehicle Charging: A Hybrid System Approach

Recent years have seen the development of a cutting-edge hybrid renewable energy charging station for electric cars (EVs). In order to provide an effective and long-lasting charging infrastructure for EVs, the project focuses on merging various renewable energy technologies, such as solar and wind power, with energy storage systems. Electric vehicles (EVs) are crucial in lowering carbon emissions and dependence on fossil fuels as the shift to sustainable transportation gathers steam. However, the creation of a reliable charging infrastructure is necessary for the broad adoption of EVs. In this project, a hybrid renewable energy-based electric vehicle charging station (HREB-EVCS) is designed and put into operation. The HREB-EVCS leverages the integration of renewable energy sources, such as solar and wind power, along with energy storage systems to ensure uninterrupted and sustainable charging for EVs. The project focuses on optimizing the utilization of renewable energy resources and managing the charging process efficiently. The charging station incorporates advanced control algorithms and smart grid technologies to intelligently distribute power among EVs based on demand, renewable energy availability, and grid conditions. The project aims to demonstrate the viability and effectiveness of the HREB-EVCS in providing clean, reliable, and cost-effective charging solutions for EVs. The results of the project will contribute to the advancement of sustainable transportation infrastructure and facilitate the wider adoption of EVs by addressing the challenges associated with charging infrastructure and renewable energy integration.

Review of Deep Reinforcement Learning and Its Application in Modern Renewable Power System Control

With the ongoing transformation of electricity generation from large thermal power plants to smaller renewable energy sources (RESs), such as wind and solar, modern renewable power systems need to address the new challenge of the increasing uncertainty and complexity caused by the deployment of electricity generation from RESs and the integration of flexible loads and new technologies. At present, a high volume of available data is provided by smart grid technologies, energy management systems (EMSs), and wide-area measurement systems (WAMSs), bringing more opportunities for data-driven methods. Deep reinforcement learning (DRL), as one of the state-of-the-art data-driven methods, is applied to learn optimal or near-optimal control policy by formulating the power system as a Markov decision process (MDP). This paper reviews the recent DRL algorithms and the existing work of operational control or emergency control based on DRL algorithms for modern renewable power systems and control-related problems for small signal stability. The fundamentals of DRL and several commonly used DRL algorithms are briefly introduced. Current issues and expected future directions are discussed.

Artificial intelligence and blockchain technology for secure smart grid and power distribution Automation: A State-of-the-Art Review

Artificial Intelligence (AI) integrated with Blockchain distributed ledger technology (BDLT) has become the most attractive research area in the domain of renewable energy and related power automations. However, the increased use of renewable energy-enabled devices raised various challenging problems, such as smart grid-based control management, power distribution, and automations. In this manner, the collaborative approach of blockchain, AI, and wireless sensor networks (WSN) provides a secure platform for control centers to estimate state, which helps to detect and analysis of bad data movement. There are various emerging issues in the field of Blockchain-AI in a renewable environment that poses a serious impact on the technological evaluation, for example, monitoring of contingency, optimal power flow, network reconfiguration, and the commitment of security-constrained units, and control auto-generation. So, in this paper, we perform a systematic review of the state-of-the-art integrated artificial intelligence and blockchain-enabled scheduling, management, optimization, privacy, and security of the smart grid and power distribution automation. One of the focusing aspects of this research is the real-time analysis of the physical layer of the smart grid. However, in this paper, we design a framework of a unified and abstracted state-space, in which the system analysis involves malicious attacks and maintain an effective generalized defense hierarchy in real-time. The current mechanism of analysis of smart grid-enabled physical layer-based malicious attacks is categorized into their associative and targeted components. Thus, we present three different pseudo-smart contracts and digital signatures with consensus policies; that provide an understanding of the new registry of renewable smart grids details, participating stakeholders and their roles, and an updated power distribution automation ledger. We then highlighted the list of emerging power distribution automation-related limitations along with the informational management approaches that present the existing state-of-the-art in this domain, including data-driven, target defense, computation, preservation, etc. Finally, we discuss open research issues and future directions of the smart grid and automation of power distribution security and privacy.

Preface

It is our great pleasure to welcome you to the 2022 3rd International Conference on Smart Grid and Energy Engineering (SGEE 2022), held during November 25th-27th, 2022 in Nanjing, China (virtual conference). The conference is a continuation of the international academic conferences in 2020 and 2021, respectively.The primary goal of SGEE 2022 is to provide an international forum for researcher and practitioner to share ideas in all aspect of how to enhance the vocational capability related to Smart Grid and Energy Engineering under the changing and advancing domestic and international situation. Besides, the conference promoted scientific and academic information interchange among all the participants working all over the world. And it will be held every year to make it an ideal platform for people to share views and experiences in related fields.During the conference, we had about 100 participations both as speakers and participants, including researchers, teachers, students, industrial experts, and professionals. To make this conference on schedule, we had a three-part plenary including a keynote speech delivered by resources persons from different parts of China and other countries. All the keynote speakers have delivered expertise lectures by imparting the latest findings from their respective research domains. Among them, Prof. Yifei Wu from Xi’an Jiaotong University, China addressed a keynote speech on the title Research on Economical DC Interruption Technology. In his presentation, the economical DC interruption technology based on arc voltage enhancement was proposed, in which the complex current commutation module was avoided and reduced the cost and volume by more than 30% compared with the existing schemes. Base on the research, a series of 10kV DC circuit breakers based on arc voltage enhancement have been developed and applied in Jiangsu and other DC distribution demonstration projects. It was a wonderful opportunity for all the participants to interact with the experts and specialists to get their advice or suggestions.The proceedings of SGEE 2022 contain quantities of excellent papers grouped by topics. All submissions were performed double blind review to check their quality of content, level of innovation, significance, originality and legibility, covering but not limited to the following topics: Smart Grid Technologies, Power Transmission and Distribution, Renewable Energy, Electricity and Energy System Applications, etc.We would like to express our gratitude to all the participants for their fruitful work and excellent contribution to the success of SGEE 2022. Especially, we appreciate the enormous work of the editorial board and reviewers in the preparation of this volume. Also, our heartfelt thanks and appreciation go to the Editors and Managers, Journal of Physics: Conference Series for their help and kind cooperation during the preparation of the proceedings. We hope you will benefit from all the manuscripts of the proceedings and learn new and novel ideas.The Committee of SGEE 2022List of Committee member is available in this pdf.

Preface

Nowadays, global energy industry is facing much more challenges ever. On the one hand, speeding up the transition to clean, renewable energy is one of the best ways to curb the dangerous carbon pollution that causes environment issue. On the other hand, smart grid and micro grid technology in the power systems are widely expected to improve sustainable energy efficiency. The International Conference on Energy and Electrical Power Systems is a leading academic conference, aiming at building a platform for communication and academic exchange in related fields.This volume contains the papers presented at the 2022 International Conference on Energy and Electrical Power Systems (ICEEPS 2022), held on November 25th-27th, 2022 in Guangzhou, China (virtual event). Everyone interested in this field were welcomed to join the online conference and to give comments and raise questions to the speeches and presentations.The online conference was composed of keynote speeches, oral presentations, and academic investigation, attracting about 150 individuals from all over the world. We have invited four sophisticated professors to perform keynote speeches. Among them, Prof. Kai Wang from Qingdao University, China is one of our keynote speakers and delivered a dramatic speech on the title Research on Life Prediction of Supercapacitor based on Improved Long-Term and Short-Term Memory Neural Network. Next, Prof. Huajun Dong from Dalian Jiaotong University, China performed a speech on Researches on Characteristics of Vacuum Switching Arc and Actuator. And then, Assoc. Prof. Yongzhi Ma from Qingdao University, China made a report on Research on Innovative Design of Split-Type All-Air Air Conditioning in Middle Apartment of Tall Buildings. Last but not the least, Prof. Abdul Hasib Chowdhury from Bangladesh University of Engineering and Technology, China shared with us his study A Talk on Stability and Resiliency of the Bangladesh Power System. All the keynote speakers made brilliant speeches combing their own research domains and experiences, and shared unique experience and insights, creating a great platform for academic communication.ICEEPS 2022 received a great many submissions in the areas of power electronics and advanced control. Each submission was reviewed by at least two expert reviewers and the committee picked out some excellent papers that are included in the proceedings, including but not limited to the following topics: Advanced Power Semiconductors, Control Science and Control Engineering, Electromagnetic Compatibility, Power Electronics and Power Drives, Power System Stability, etc.On behalf of the Conference Organizing Committee, we would like to extend our sincere acknowledgement to all the keynote speakers, peer reviewers, and all the participants. In particular, our heartfelt thanks and appreciation go to the Editors and Managers, Journal of Physics: Conference Series for their help and kind cooperation during the preparation of the proceedings. Hopefully, all participants and other interested readers can benefit significantly from the proceedings and find it rewarding.The Committee of ICEEPS 2022List of Committee member is available in this pdf.

Survey of Electricity Demand Forecasting and Demand Side Management Techniques in Different Sectors to Identify Scope for Improvement

Electricity demand is increasing at a rapid rate. Sustainability related challenges are posing an immediate cause of concern for the planet. Smart Grid provides an efficient way to manage the complex scenario. The challenge of enhancing energy efficiency and integration of renewables effectively is addressed by utilizing smart grid technology. Accurate demand forecasting and demand side management are needed to balance the demand and supply gaps over time of day and season related variations. This survey paper aims to provide a comprehensive overview of the various techniques and approaches used for demand forecasting in the residential, industrial, and agricultural sectors. It also examines the role of demand response in managing peak electricity demand and maintaining grid stability through the shifting of usage to off-peak hours. The aim is to understand the nuances and prevailing practices in these sectors to identify potential areas for improvement.

Protection Challenges on Integration of Distributed Sources to Power system network: A Review

— Electricity generation has to be increased to meet various type of future load demand like LED lightning, Electrical 
 Vehicles, mobiles, communication network, non linear load etc. Automation is essential requirement now a days in each sector. 
 To provide automation at residential, commercial and industrial sectors electrical energy is required. To meet energy 
 requirement of various sector utility grid is integrated with DG Sources, which mainly include renewable energy sources like 
 solar, wind and other environment friendly sources either in large scale or small scale depends on the location and availability. 
 This type of technology leads power system to era of smart grid. Smart grid technology provides features like digitization, two 
 way communication, distributed generation, adaptive islanding, self monitoring and self mitigating, fully controllable compare to 
 conventional Grid. Though smart grid technology is advantageous but due to integration of distributed generation at 
 transmission and distribution system will increase protection challenges in the power network. This paper gives an insight of 
 different protection issues which occur at transmission, distribution and Micro grid network. The paper also focuses on the 
 techniques and solution of the various protection challenges.

Day-ahead to intraday energy scheduling operation considering extreme events using risk-based approaches

Demand response programs, energy storage systems, electric vehicles, and local electricity markets are appropriate solutions to offset the uncertainty associated with the high penetration of distributed energy resources. It aims to enhance efficiency by adding such technologies to the energy resource management problem while also addressing current concerns using smart grid technologies and optimization methodologies. This paper presents an efficient intraday energy resource management starting from the day-ahead time horizon, which considers the uncertainty associated with load consumption, renewable generation, electric vehicles, electricity market prices, and the existence of extreme events in a 13-bus distribution network with high integration of renewables and electric vehicles. A risk analysis is implemented through conditional value-at-risk to address these extreme events. In the intraday model, we assume that an extreme event will occur to analyze the outcome of the developed solution. We analyze the solution’s impact departing from the day-ahead, considering different risk aversion levels. Multiple metaheuristics optimize the day-ahead problem, and the best-performing algorithm is used for the intraday problem. Results show that HyDE gives the best day-ahead solution compared to the other algorithms, achieving a reduction of around 37% in the cost of the worst scenarios. For the intraday model, considering risk aversion also reduces the impact of the extreme scenarios.

A novel hybrid Harris hawk optimization and sine cosine algorithm based home energy management system for residential buildings

Smart grid technology has given users the ability to regulate their home energy in a much more effective manner. In such scenarios, Home Energy Management (HEM) potentially becomes an arduous task, as it necessitates the optimal scheduling of smart appliances in order to reduce energy usage. In this research, a hybrid Harris Hawk Optimization-Sine Cosine Algorithm (hHHO-SCA) has been proposed to develop a meta-heuristic-based HEM system. The hybridization of HHO with SCA has been done to enhance the exploration and exploitation stages of HHO, hence improving its global search phase and effectively optimizing the energy usages. In addition to this, several knapsacks are utilized to guarantee that load demand for power users does not surpass a certain level during the peak hours. In terms of electricity prices and Peak to Average Ratio (PAR) reduction, the hybridization is demonstrated to be beneficial in achieving the objectives. Simulations are performed for a multi-family housing complex with a range of smart equipment. The results achieved with the proposed approach suggest that hHHO-SCA has been comparatively efficient in terms of cost reduction, and PAR, when compared to the other optimization techniques. Practical Application. This home energy management system can be applied to optimally schedule all the smart appliances in a building to minimize electricity consumption and provide the consumer with potential savings in electricity costs.

Are cities venturing green? A global analysis of the impact of green entrepreneurship on city air pollution

Situated at the intersection between environmental entrepreneurship and urban sustainability, our paper seeks to investigate the links between city-level green venture ecosystems and the ability of urban centres to reduce air pollution. Using a large dataset of 12,834 urban centres from around the world and their associated yearly average particulate matter (PM2.5), we show that an increase in the cumulative number of green start-ups drives the lowering of PM2.5 levels. Looking closely at the subsectors that drive the results, we observe that the urban centres which hosted increased numbers of innovators in smart grid technologies, energy efficiency and wind energy generation (the low carbon energy sector overall) also experienced a decrease in air pollution over the 2010–2019 period. Thus, our study is a global analysis of the environmental impact of green entrepreneurship on local air pollution.

Data Analysis for Smart Grid and Communication Technologies

Smart grids and communication technologies are among the significant advancements in theenergy sector. These technologies improve energy efficiency by increasing the use of renewable energysources. However, the integration of these technologies also creates a vast amount of data that requiresanalysis to optimize energy management and improve system performance. In this context, data analysisplays a crucial role in identifying patterns, predicting energy demand, and managing energy supply. Thispaper provides an overview of the importance of data analysis in smart grids and communicationtechnologies and discusses various data analysis techniques used in energy management systems.Additionally, it highlights the challenges and opportunities associated with data analysis in the context ofsmart grids and communication technologies.

A Super-Efficient GSM Triplexer for 5G-Enabled IoT in Sustainable Smart Grid Edge Computing and the Metaverse.

Global concerns regarding environmental preservation and energy sustainability have emerged due to the various impacts of constantly increasing energy demands and climate changes. With advancements in smart grid, edge computing, and Metaverse-based technologies, it has become apparent that conventional private power networks are insufficient to meet the demanding requirements of industrial applications. The unique capabilities of 5G, such as numerous connections, high reliability, low latency, and large bandwidth, make it an excellent choice for smart grid services. The 5G network industry will heavily rely on the Internet of Things (IoT) to progress, which will act as a catalyst for the development of the future smart grid. This comprehensive platform will not only include communication infrastructure for smart grid edge computing, but also Metaverse platforms. Therefore, optimizing the IoT is crucial to achieve a sustainable edge computing network. This paper presents the design, fabrication, and evaluation of a super-efficient GSM triplexer for 5G-enabled IoT in sustainable smart grid edge computing and the Metaverse. This component is intended to operate at 0.815/1.58/2.65 GHz for 5G applications. The physical layout of our triplexer is new, and it is presented for the first time in this work. The overall size of our triplexer is only 0.007 λg2, which is the smallest compared to the previous works. The proposed triplexer has very low insertion losses of 0.12 dB, 0.09 dB, and 0.42 dB at the first, second, and third channels, respectively. We achieved the minimum insertion losses compared to previous triplexers. Additionally, the common port return losses (RLs) were better than 26 dB at all channels.

Privacy Preservation in Smart Meters: Current Status, Challenges and Future Directions.

Recent years have seen the rapid development of technologies in Smart Grids (SGs) to enhance electricity networks with digital and data communication technologies. SGs can proactively detect, react, and respond to dynamic changes in the network. SGs can also enhance the efficiency and reliability of electricity supplies and promote the integration of renewable energy sources. Smart Meters (SMs) are often seen as the first step to a successful implementation of SGs. While SMs enable Utility Providers and consumers to obtain near real-time information of energy consumption, they can also be exploited to infer sensitive consumer data. Therefore, privacy preservation in SMs is paramount in ensuring the widespread and successful deployment of SGs. In this paper, we present a comprehensive survey of the state-of-the-art SM privacy-preserving techniques published in the literature over the past decade. We categorize these techniques based on the attack types and their objectives. We aim to offer a unique perspective in this survey article through the lens of privacy preservation, cross-cutting the wide range of techniques presented in the literature. We conclude by identifying the challenges and highlighting key future research directions in the field.

An IOT based smart grid system for advanced cooperative transmission and communication

In the Internet of Things (IoT) ecosystem, devices will predominate, using it in a manner similar to how people used it. Devices will cooperating in a multicast network to collect, share, and forward information way while interacting with one another autonomously and without centralised supervision. The building of an intelligent environment the capability of real-time collection of data, which is crucial for maximising the value of the IoT, will make this possible. A typical electric grid is made up of many power plants that use various power generating units, such as coal-based units, gas-based units, hydro units, etc. The majority of the infrastructure and wires that make up the conventional electricity grid have been in existence for a long time, it should be mentioned. They require significant investments, so providing them could take years. As a result, many grid components are outmoded and must be maintained and monitored on a regular basis to keep power flowing. A sophisticated technology is the smart grid (SG) system that makes it easier to integrate green technology and environmental considerations. The SG cyber–physical system was implemented thanks to the advancement and use of communication technologies in the conventional power system. The Internet of Things (IoT) and essential devices are both present in the complicated architecture of the SG systems. The traditional electric grids are been transformed into smart and efficient grid known as “Smart grid”. The Internet of Things’ smart grid allows for two-way communications among connected devices and technology that can recognise and respond to human needs. The cost and reliability of a smart grid are superior to that of conventional power infrastructure. Through use and data maintenance, smart grid technology will assist in reducing energy use and costs. One of the primary contributions made to grids is the integration of IoT with producing facilities using sustainable energy at various levels. To enhance the smart grid for bidirectional information exchange, improve power quality, and increase reliability Internet of Things (IOT) devices are becoming an important part of smart electric grid. IOT Infrastructure (IOTI) provide a flexible, efficient and secure platform providing strategic management for monitoring and controlling of different operations under different working conditions. This paper discusses cyber security on IOT based infrastructure for electric power systems. A comprehensive study is highlighted which includes type of IOTs, architecture used for smart grid, and future challenges.

Risk-Based Active Distribution System Planning for Resilience Against Extreme Weather Events

Enhancing the resilience of power distribution systems to extreme weather events is of critical concern. Upgrading the distribution system infrastructure by system hardening and investing in smart grid technologies effectively enhances grid resilience. Existing distribution system planning methods primarily consider the persistent cost of the expected events (such as faults and outages likely to occur) and aim at improving system reliability. The resilience to extreme weather events requires reducing the impacts of the high impact low probability (HILP) events that are characterized by the tail probability of the event impact distribution. Thus, the resilience-oriented system upgrades solutions need to be driven by the risks imposed by extreme weather events on the power grid infrastructure rather than persistent costs. This paper aims to develop a risk-based approach for the long-term resilience planning of active power distribution systems against extreme weather events. The proposed approach explicitly models (1) the impacts of HILP events using a two-stage risk-averse stochastic optimization framework, thus, explicitly incorporating the risks of HILP events in long-term planning decisions, and (2) the advanced distribution grid operations (in the aftermath of the event) such as intentional islanding into infrastructure planning problem. The inclusion of risk in the planning objective provides additional flexibility to the grid planners to analyze the trade-off between risk-neutral and risk-averse planning strategies.

Hydrogen‐powered smart grid resilience

AbstractWith an increasing frequency of natural disasters and security attacks, the safe and stable operation of smart grid has been challenged unprecedently. To reduce the economic loss and social impact caused by power outage accidents, it is urgent to develop and improve the smart grid technology, and strengthen the disaster resistance and recovery capability of smart grids when faced with extreme events. As an efficient and flexible secondary energy source, hydrogen is crucial in improving the resilience of smart grid and supporting energy security. To further promote the deep integration of hydrogen systems and smart grid and improve the energy system resilience, the resilience of smart grids supported by hydrogen is assessed in this study. First, a technical framework of hydrogen‐powered smart grid resilience is established, and the value of hydrogen‐powered smart grid resilience is analysed considering different time frames (before, during and after an extreme event) of smart grids facing extreme events. Then, hydrogen‐powered smart grid resilience is investigated from perspectives of pre‐prevention regulation, in‐process correction regulation, and post‐recovery regulation. Finally, future direction for hydrogen‐powered smart grid resilience is investigated and related policy suggestions are provided.

DIGITALIZATION PROCESSES IN THE ENERGY COMPLEX OF UZBEKISTAN

The energy sector in Uzbekistan has been undergoing digitalization processes to improve efficiency, reduce costs, and enhance the reliability and security of energy supply. This article explores the digitalization efforts in Uzbekistans energy sector, with a focus on smart grid technologies and the adoption of advanced metering infrastructure (AMI) for gas and electricity. Uzbekistan has been deploying smart grid technologies to modernize its energy infrastructure, integrate renewable energy sources, and optimize energy generation, transmission, and distribution processes. The adoption of AMI has improved billing accuracy and reduced operating costs. Uzbekistan is investing in renewable energy sources, with a goal to increase its renewable energy capacity to 25% of total electricity generation by 2030. The country is developing a digital energy platform that will use advanced data analytics and machine learning algorithms to optimize energy use and improve the efficiency and reliability of the energy system. KEYWORDS: Digitalization, Smart Grid, Advanced Metering Infrastructure, Renewable Energy, Energy Efficiency, Energy Security, and Uzbekistan.

Innovation in complementary energy technologies from renewable energy policies

Complementary renewable technologies support renewable energy use as they can help balance the intermittency of solar and wind generation. Previous research has shown that environmental policies directly targeting renewable energy can drive innovation in solar PV and wind technology. This study explores the impact of renewable policies on innovation in complementary renewable technology that assists with integration, including combustion with mitigation potential, efficient power transmission or distribution, and enabling technologies. We use negative binomial models and a panel of 25 OECD countries from 1997 to 2015 to evaluate these relationships. We are not able to find evidence that renewable policies incentivize innovation in complementary combustion or transmission and distribution technologies, and only limited evidence that demand-pull instruments are associated with increased innovation in smart grid technology. Technology-push policies, such as public research and development funds for renewable energy, have had limited impact on grid-supporting energy storage innovation. Our findings suggest that policymakers wishing to accelerate these complementary technologies need to go beyond policies targeting renewable energy in order to drive innovation in complementary fields.