Andrew Keane
The electrification of demand is a global trend that is gaining momentum as countries take action to address climate change and decarbonize the energy system. To be effective as a decarbonization action, it involves two parallel tracks: shifting energy demand from fossil fuels to electricity and increasing renewable energy grid integration. Together, these parallel tracks form the cornerstone of many countries’ climate action plans. The past decade has seen strong progress in some countries in the grid integration of renewables. This progress and the promise to further increase renewables on the grid opens up the opportunity to decarbonize sections of our whole energy system via electrification.
One key area of the electrification of demand is the adoption of electric vehicles (EVs). EVs offer the dual benefits of climate change mitigation and the improvement of public health. They are generally responsible for fewer greenhouse gases than their gasoline-powered counterparts (power system plant mix dependent), reducing the carbon footprint of transportation. They also emit no harmful tailpipe emissions, such as particulate matter and nitrogen oxides, which can lead to respiratory and cardiovascular diseases. The public health benefits of a switch to zero-emission vehicles are firmly established but often overlooked in discussions on the topic.
In recent years, EVs have rapidly transitioned from a disruptive innovator to a mainstream offering of almost all car manufacturers. The technology is mature, and, while the adoption of EVs remains a technical challenge, it is also a social and behavioral challenge. In a noisy world of information and disinformation, the public needs clear and accurate facts about the benefits and challenges of EVs. Several previously mooted concerns about EVs, such as near-empty batteries in emergency situations or an inability to charge at all, have not come to pass. Home charging is generally highly reliable and the cheapest form of charging to undertake for those who have the space to install a home charger (generally single phase). A key challenge is ensuring that reliable and accessible charging infrastructure is available for those without access to home charging, a key challenge if EVs are to further penetrate the market. The benefit of the experience from countries such as South Korea and Norway is that there is clear objective evidence as to what is spurious or a nonissue and what actually are the key aspects of EV adoption and management at scale.
Engineers are at the heart of this important transition, delivering the systems and solutions necessary to support the mass adoption of EVs and their associated benefits. Such systems and solutions include the development of charging infrastructure, battery technology, and energy management systems. Governments also play a crucial role in incentivizing the adoption of EVs through policies, such as tax credits and rebates, and regulations to reduce emissions from the transportation sector. When it comes to the mass adoption of EVs, Norway can, again, be cited as an extremely successful example of their adoption. As a country with an extremely high renewable energy power system (mostly hydro), it is also highly successful with emissions reduction from the transport sector. A combination of incentives, such as tax exemptions and toll road exemptions, and a strong charging infrastructure has been an important factor in this success. Norway is a very good example of a country where the twin-track approach of renewable electricity and the electrification of demand has seen success.
In general, countries are now accelerating their renewable energy integration plans, and an important part of realizing this on power systems is demand flexibility. The inherent link between the role of demand-side management and energy storage and the operation of highly renewable grids is clear to all in the sector. This link is well flagged and leads to several research questions across almost the whole spectrum of power systems research. Demand flexibility at the residential level has long been the most difficult or expensive to access for demand aggregators or suppliers. In the minds of policy makers and governments, smart meters were often viewed as the conduit to achieve active residential demand response, but, as seen in several countries, smart or advanced meters often have limited computation and communication abilities. Dynamic pricing is possible with advanced metering infrastructure, and this may be successful in shifting a portion of demand to nighttime, e.g., EV charging.
However, as we know, the system requires a lot more than demand shifting to ensure a secure and reliable supply. For example, a spinning or primary operating reserve function built into the demand will be a valuable/essential resource for the operation of highly renewable systems. Considering the characteristics of the demand, which is increasingly interfaced with power electronic inverters, will be important in unlocking a fast-acting residential demand response. Similar functions arise with other reserve categories, and, indeed, demand response is relevant for longer term generation adequacy assessments, too. EVs with their battery storage (often 40–70 kWh) present a significant resource at the residential level that is sizeable (in terms of capacity and energy) and technically accessible. The resource is significant, even ignoring any potential vehicle-to-grid capability.
The Korean experience highlights what may be possible and reinforces the trend and the need for closer to real-time markets, such as balancing markets. Such markets seem inevitable in an increasingly stochastic system and will be important instruments for resolving near-real-time events on the power system, including the planned/unplanned curtailment of renewables, which is increasing on grids around the world. The curtailment of renewable energy generally comes down to system balancing requirements or congestion on the system. New market structures, appropriately designed, can help alleviate some of these issues, especially if resources, such as EVs, are successfully integrated into the demand response and associated market mechanisms.
The Facilitating a Sustainable Transition to EVs in the Region (FASTER) project in Scotland highlights the requirement to develop widespread charging infrastructure right across countries, including into areas far from the motorway/highway network where fast charging can be found. If EVs are to penetrate fully into personal vehicle transport across society, this kind of “journey”-focused approach to charging infrastructure in rural areas will be necessary and needs to be accelerated. To plan and operate mass EV charging effectively, the accurate modeling of distribution networks is vital. However, a data gap exists in terms of available quality network data. Filling this gap and meeting the essential functions of the distribution network have been the focus of much research on topics such as distribution state estimation techniques, sensor placement, the potential of smart meter data, and more. All are relevant and can play a role in delivering the services that consumers and system operators need.
Assumptions around what data are available, when, and of what quality are often important starting points in the consideration of such methods, and so the now-ubiquitous question of data and their analyses arises. The question of access to data for research and development is extremely important and will remain so. Globally, a growing movement exists for open data, in particular when related to the environment arising from the United Nations Aarhus convention. With an ever-growing focus on climate and environmental matters, this convention, adopted back in 1998, is gaining renewed attention and leading to further legislative instruments in Europe and elsewhere.
The case for and benefits of open data (where possible) are well established. They promote collaboration and knowledge sharing across different sectors and organizations, enabling researchers to build on each other’s work. In addition, open data initiatives can help to reduce the duplication of efforts as well as increase efficiency and transparency in research and development. Open data also have the potential to accelerate innovation by providing businesses with the information they need to develop new products and services. By sharing datasets with industry, researchers can help businesses to identify new opportunities and improve their products and services, ultimately leading to economic growth. For electric grids, all of these benefits apply, but there is an emerging need for open data specific to the electricity sector and that are for the grid connection of renewable energy, storage, fast EV charging stations, and more.
When considering any network integration challenge, the question of data—their availability and quality—almost immediately presents itself. The Scottish experience outlined from the FASTER project highlights this challenge, especially as we again consider continued development outside motorway and highway networks. The task of processing, analyzing, and delivering secure, cost-effective grid connections falls to the distribution companies and system operators. The great wave of electrification that is upon us immediately highlights and reveals any bottlenecks in grid planning. In general, delays are not due to a lack of expertise in distribution companies but due to the complexity and interdependent nature of the grid connection process. This process is time-consuming and can risk the viability of a developer’s project pipeline and, at best, cause longer lead times for connection. The article in this issue from Kevala and Vote Solar in the United States [A1] neatly highlights that the electrical network is central to the development of EV charging facilities but also that land use and land characteristics are important considerations. It is also a good example of how commercial actors are stepping in to provide solutions aimed at accelerating the integration of renewable energy and technology, such as EVs.
Making use of what open data are available combined with specific artificial intelligence techniques may be indicative of future trends in network management and analysis. When we consider making data available publicly, in several cases, the ideal dataset simply doesn’t exist, e.g., residential networks. Advanced metering data may address this in time, but, again, considering government targets around the world and the growing list of imperatives for decarbonization, it seems progress cannot wait for this data gap to be filled. In the case where long-term advanced metering data are available, recent work from the University of Melbourne in particular highlights how artificial intelligence techniques utilized in combination with advanced metering data can reveal the network characteristics.
The rollout of EV charging infrastructure presents numerous challenges, from technical and logistical issues to social and behavioral ones. EV charging will require significant investments in infrastructure and technology as well as a shift in mindset and behavior among consumers and businesses. It is an example of a case where almost all of the technology required is ready and available. How the system of components functions and interacts remains unresolved, notwithstanding the interesting and valuable case studies presented in this issue. The interaction and physical makeup of the grid can be an easy feature to ignore for the many interested in this topic from outside the power and energy community, but, as we may appreciate, the complex physical reality of the power system will need to be reckoned with sooner or later. While we might quite rightly focus on the challenges, it is important to recognize the many benefits of EVs, from reduced greenhouse gas emissions and improved air quality to a contribution to the integration of renewables. Either way, it is clear that the electrification of transport will continue at pace, as will the need for utilities and regulators to effect a once-in-a-generation upgrade and rollout of grid infrastructure.
Digital Object Identifier 10.1109/MPE.2023.3308249
Date of current version: 19 October 2023
1540-7977/23©2023IEEE