The EU's Global Gateway plan is challenging China's Belt and Road Initiative to influence Africa, by providing funding that will expand access to electricity. Nearly 600 million Africans--half the continent's population--are without electricity, largely because of the continent's limited distribution network, and Africans make up the vast majority of those worldwide without electricity access. But the European Union wants to change this. At the end of September, the president of the European Commission, Ursula von der Leyen, announced a €545 million ($636 million) investment package to support renewable energy and electrification in Africa. New EU-funded projects will include a high-voltage transmission line in Côte d'Ivoire, the electrification of hundreds of rural communities in Cameroon, the exploitation of wind and hydro energy in Lesotho, and the installation of mini-grids in remote areas of Madagascar.

Electrifying space and water heating is a critical priority for the energy transition. The necessary widespread adoption of heat pumps will have significant impacts on the power grid. Studies report heating electrification may increase winter peak electricity demand by up to 70%, with some colder regions experiencing a more than fourfold increase in peak demand. The process of upgrading the grid has a critical spatial dimension, as heating demand, electricity demand, and the capacity of existing grid infrastructure vary significantly across regions. Grid planning also involves a critical temporal dimension: short-term weather patterns and long-term climate change introduce complexities and uncertainties that can be di fficult to quantify. However, most existing demand forecasts are provided and validated only at aggregated spatial scales, lack temporal detail, and provide single-valued predictions. Without accurate, probabilistic, and spatially and temporally resolved demand forecasts, planners risk misallocating scarce resources. We present a novel framework for high-resolution forecasting of residential heating and electricity demand using probabilistic deep learning models. We focus specifically on providing hourly building-level electricity and heating demand forecasts for the residential sector. Leveraging multimodal building-level information - including data on building footprint areas, heights, nearby building density, nearby building size, land use patterns, and high-resolution weather data - and probabilistic modeling, our methods provide granular insights into demand heterogeneity. V alida-tion at the building level underscores a step change improvement in performance relative to NREL's ResStock model, which has emerged as a research community standard for residential heating and electricity demand characterization. In building-level heating and electricity estimation backtests, our probabilistic models respectively achieve RMSE scores 18.3% and 35.1% lower than those based on ResStock. Introduction Electrifying space and water heating is a critical priority for the energy transition [1, 2]. Residential and commercial buildings make up 13% of all U.S. emissions [3], with fossil-fueled space heating representing the single greatest constituent of this share [4]. The necessary widespread adoption of heat pumps will have significant impacts on the power grid.

This story was originally published on the author's substack, Field Notes with Alexander C Kaufman, to which you can subscribe here. Artificial intelligence is driving up demand for electricity--the only question is how much, and what provides the power. Over the next three years, the Lawrence Berkeley National Laboratory estimates, AI's thirst for power will double or triple. Last month, OpenAI unveiled its Stargate Project, a plan to invest 500 billion in the infrastructure for artificial intelligence over the next four years that includes adding 25 gigawatts of new electricity capacity. Right now, the most likely source of electricity to power those data centers is gas.

Honda's all-electric Prologue, a collaboration vehicle manufactured in tandem with GM, has been a serious hit for the brand. The Prologue was the best-selling non-Tesla EV in the US in Q4. Using Tesla as a touchstone seems telling, revealing Honda's intentions in the industry. However, Honda isn't limiting itself and plans to offer vehicles with an array of powertrain options--gas-powered, hybrid, and electric--to please a wide spectrum of customers. After all, as Honda America's vice president of sales Lance Woelfer asserts, "electrification is a marathon, not a sprint." "The road to electrification will have some twists and turns," concedes Jay Joseph, vice president of American Honda's Sustainability and Business Development business unit.

V.EV, Vitol's fleet electrification business, offers a turnkey fleet electrification solution to fleets of all vehicle types. By offering an end to end service to identify the right solution to enable fleets to decarbonise, the provision and installation of charging infrastructure and the subsequent operation of your fleet's chargepoints, battery storage and onsite generation through our software solution we can accelerate the rate the UK's fleets decarbonise. Our parent company is the world's largest independent energy and commodities trading company. From 40 offices worldwide, Vitol seek to add value across the energy supply chain, including deploying its scale and market understanding to help facilitate the energy transition. To date, Vitol committed over $2.2 billion of capital to renewable projects, and are identifying and developing low-carbon opportunities around the world.

AEM presented 10 top trends for the future of building construction, among them alternative power, the electrification of compact equipment, autonomous machinery and sensors for increased safety. Referencing recent aviation fuel regulations plans, the California Air Resources Board's (CARB) ban on small engines on new equipment starting in 2024, the Environmental Protection Agency's (EPA) new greenhouse gas emissions rules for 2023–2026 passenger vehicles and light-duty trucks and the EPA's plan to reduce greenhouse gas emissions from heavy-duty trucks starting with 2027 models, the AEM whitepaper asserts that construction companies will see their fleets change over the next decade, as well. Major corporations continue to invest in renewable energy like biofuels, solar and wind power, as construction companies and large contractors commit to net-zero impact pledges for new buildings and infrastructure. The United States' commitment to cutting carbon emissions by 50% by 2030 will spur "the electrification of many segments of the compact construction equipment market" over the next 10 years, according to AEM. Thanks to the advanced 5G network and cloud systems, equipment tracking will allow real-time visibility into productivity and maintenance on a Jobsite, so operators and contractors can make sure they queue properly and have the most efficient job flow they can.

Looking ahead is always a tricky business. While the turn of the year presents an opportunity to take a fresh look at your strategy and plan where to focus your energies, it can be hard to sort real trends from hype. This is especially true when it comes to tech. Think about this time last year, and the excitement around NFTs, crypto, and the metaverse. By fall of 2022, NFT markets were down 90%, we'd entered a cold crypto winter, and a bustling metaverse was still more of a dream than reality.

Governments and international organizations the world over are investing towards the goal of achieving universal energy access for improving socio-economic development. However, in developing settings, monitoring electrification efforts is typically inaccurate, infrequent, and expensive. In this work, we develop and present techniques for high-resolution monitoring of electrification progress at scale. Specifically, our 3 unique contributions are: (i) identifying areas with(out) electricity access, (ii) quantifying the extent of electrification in electrified areas (percentage/number of electrified structures), and (iii) differentiating between customer types in electrified regions (estimating the percentage/number of residential/non-residential electrified structures). We combine high-resolution 50 cm daytime satellite images with Convolutional Neural Networks (CNNs) to train a series of classification and regression models. We evaluate our models using unique ground truth datasets on building locations, building types (residential/non-residential), and building electrification status. Our classification models show a 92% accuracy in identifying electrified regions, 85% accuracy in estimating percent of (low/high) electrified buildings within the region, and 69% accuracy in differentiating between (low/high) percentage of electrified residential buildings. Our regressions show $R^2$ scores of 78% and 80% in estimating the number of electrified buildings and number of residential electrified building in images respectively. We also demonstrate the generalizability of our models in never-before-seen regions to assess their potential for consistent and high-resolution measurements of electrification in emerging economies, and conclude by highlighting opportunities for improvement.

This research provides a novel framework to estimate the economic, environmental, and social values of electrifying public transit buses, for cities across the world, based on open-source data. Electric buses are a compelling candidate to replace diesel buses for the environmental and social benefits. However, the state-of-art models to evaluate the value of bus electrification are limited in applicability because they require granular and bespoke data on bus operation that can be difficult to procure. Our valuation tool uses General Transit Feed Specification, a standard data format used by transit agencies worldwide, to provide high-level guidance on developing a prioritization strategy for electrifying a bus fleet. We develop physics-informed machine learning models to evaluate the energy consumption, the carbon emissions, the health impacts, and the total cost of ownership for each transit route. We demonstrate the scalability of our tool with a case study of the bus lines in the Greater Boston and Milan metropolitan areas. Detailed Affiliation: U.Vijay, S.Woo, and S.J.Moura are at Department of Civil and Environmental Engineering, University of California-Berkeley, Davis Hall, Berkeley, California, 94720, USA. A.Jain is at Department of Electrical Engineering and Computer Sciences, University of California-Berkeley, Soda Hall, Berkeley, California, 94720, USA. D.Rodriguez and E.Mellekas are at Enel X, North America, Inc., One Marina Park Drive, Boston, 02210, MA, USA. S. Gambacorta is at Enel X, Innovation and Sustainability Global, Smart City, Viale Tor di Quinto, Rome, 00191, Italy. G.Ferrara is at Enel X, Innovation and Sustainability Global, Smart City, Passo Martino, Catania, 95121, Italy. L.Lanuzza is at Enel X, Innovation and Sustainability B2C & B2B Innovation Factory, Viale Tor di Quinto, Rome, 00191, Italy. C.Zulberti and C.Papa are at Enel Foundation, Via Bellini, Rome, 00198, Italy. Vehicle electrification is crucial for reducing the climate impact of the transportation sector, which currently accounts for 16.2% of the global greenhouse gas emissions [22]. Zero-emission electric vehicles can significantly improve the air quality, health, and environmental equity [23], [24].

'Urban Mobility' is emerging as the backbone of the entire city ecosystem ensuring its growth and overall success. Today's call for a greener planet and active'Climate Change' combatting agenda inevitably encourages the need for smarter, greener, and safer urban mobility channels. The emerging smart cities today are increasingly integrating mobility solutions that are based on cleaner energy usage and shared resources with an elevated level of infrastructure integration among its inhabitants. None of this can be achieved without a substantial focus on the design, planning, and delivery of urban infrastructure that enables greater efficiency in urban mobility. According to World Bank –'Traditionally, urban mobility is about moving people from one location to another location within or between urban areas.