Electric cars are so popular in the Netherlands that it would not be uncommon, say, for a Tesla to roll up as a taxi outside Amsterdam’s Schiphol Airport. And it is not tough to find charging stations for these cars in neighborhoods, parking lots, or even along the streets.
To reduce carbon emissions, national and local governments are taking various approaches—and, thus, electric cars, solar home systems, and energy-efficient solutions for buildings are booming in Europe. Cities like Amsterdam are front and center of this transformation. Netherlands, for instance, has an ambitious goal of reducing CO2 emissions by 80–95 percent by 2050 compared with 1990, making it an ideal venue for a Smart Cities Tour earlier this year, where a group of 26 representatives, including national and municipal officials and World Bank project teams, to learn from the Netherlands’ successful experience in energy sector transformation.
For instance, during a site visit to energy network company Alliander, we saw the pilot of a neighborhood battery system (NBS) in Rijsenhout, a town in the Western Netherlands near Amsterdam. The NBS is a local, community-level energy storage system that employs one large battery to stabilize neighborhood power distribution grids, particularly during peak hours. With a significant and increasing number of electric vehicle charging stations and solar panels installed in communities, electric networks are under increasing pressure to handle the variation between solar power during the day and concentrated peak electricity demand in the evenings and nights. Maintaining stable power supply and enhancing the resilience of the electricity grid to spikes in demand are fast becoming real challenges for these communities. While overhauling the power grids to prepare for these challenges could be costly and time-consuming, these small-scale NBS provide a low-cost, smart alternative solution.
In Jamaica, about a quarter of electricity produced is stolen or “lost” through non-paying customers and/or accounting errors. Manual detection has failed to make a difference in reducing this theft.
ESMAP’s technical assistance team implemented a machine learning model to help Jamaican utility JPS identify and decrease incidents of theft.
The machine learning model is based on an open source code, and is available for free to any utility.
About a quarter of the electricity produced by Jamaica’s energy utility, Jamaica Public Service (JPS) is stolen. When traditional, labor-intensive methods failed to produce lasting results, Jamaica tried a different approach: machine learning.
Globally, billions of dollars are lost every year due to electricity theft, wherein electricity is distributed to customers but is never paid for. In 2014 alone, Jamaica’s total power transmission and distribution system reported 27% of losses (due to technical and non-technical reasons), close to double the regional average. While the utility company absorbs a portion of the cost, it also passes some of that cost onto consumers. Both actors therefore have an incentive to want to change this.
To combat this, JPS would spend more than $10 million (USD) on anti-theft measures every year, only to see theft numbers temporarily dip before climbing back up again. The problem was, these measures relied primarily on human-intensive, manual detection, and customers stealing electricity used more and more sophisticated ways to go around regularly metered use. JPS employees would use their institutional knowledge of serial offenders and would spend hours poring over metering data to uncover irregular patterns in electricity usage to identify shady accounts. But it wasn’t enough to effectively quash incidents of theft.
Each city is unique, defined not only by the individuals who call it home but also by the energy it exudes…and consumes. Projections indicate that 5 billion people (60% of the world’s population) will live in cities by 2050 and, according to the International Energy Agency, the overall demand for lighting will be 80% higher by 2030 than in 2005. Street lighting energy consumption is an increasingly significant part of cities energy use and a growing burden on municipal budgets.
Evaluating the optimal way to expand electricity access across a country is difficult, especially in countries where energy related data is scarce and not centralized. Geospatial plans informing universal electricity access strategies and investments can easily take 18 to 24 months to complete.
A team working on a national electrification plan for Zambia last December did not have that much time.
They faced a six-month deadline to develop a plan, or they would miss out on a funding window, said Jenny Hasselsten, an energy specialist at the World Bank brought in to help with the electrification project in partnership with the government of Zambia.
L’accord de Paris sur le climat, conclu en 2015, a été précédé d’une analyse des données scientifiques et de la viabilité des mesures d’adaptation aux conséquences du changement climatique et d’atténuation des émissions de gaz à effet de serre (GES). Si ces mesures s’intéressent en général aux conséquences de la réduction des émissions sur l’économie, les politiques publiques, la technologie et la durabilité du développement, elles s’attachent relativement peu aux implications d’un avenir sobre en carbone.
C’est pourquoi la Banque mondiale a décidé de se pencher sur cette question et de déterminer quels seraient les minéraux et les métaux pour lesquels la demande pourrait augmenter. Avec le rapport The Growing Role of Minerals and Metals for a Low-Carbon Future, qui s’intéresse à l’éolien, au solaire et au stockage d’énergie par batteries, la Banque donne à ce sujet la place qu’il mérite dans le dialogue actuel sur le changement climatique.
S’appuyant sur les scénarios climatiques et technologiques élaborés à partir des Perspectives des technologies de l’énergie de l’Agence internationale de l’énergie (AIE), la Banque mondiale a réalisé un ensemble de projections de la demande de produits de base jusqu’en 2050. Nous avons utilisé pour ce faire les meilleures estimations concernant l’adoption de trois technologies discrètes et respectueuses du climat (l’éolien, le solaire et le stockage d’énergie par batteries), qui sont nécessaires pour satisfaire aux spécifications des trois scénarios de réchauffement de la planète, à savoir 20 C, 40 C et 6o C.
The 2015 Paris Agreement on Climate Change was preceded by analysis covering the science and viability of response measures, including both adaptation to the impacts of climate change and measures to mitigate greenhouse gas (GHG) emissions. Mitigation issues typically covered the economic, policy, technology and sustainability implications of reducing emissions, but relatively little towards understanding the implications of a low-carbon future.
For this reason, the World Bank decided to explore and study which minerals and metals will likely see an increase in demand to achieve a low-carbon future. Using wind, solar and energy storage batteries as proxies, “The Growing Role of Minerals and Metals for a Low-Carbon Future” report is one of the Bank’s contributions towards ensuring this topic is given its rightful place in the ongoing global climate change dialogue.
Based on climate and technology scenarios developed out of the International Energy Agency’s (IEA) Energy Technology Perspective, the World Bank developed a set of commodities demand projections up to 2050. We did so by providing best estimates on the uptake of three discrete climate-benefit technologies – wind, solar and energy storage batteries – required to help meet three different global warming scenarios of 20C, 40C, and 6oC.
These technologies represent only a sub-set of a much broader suite of technologies and transmission systems required to truly deliver on a low-carbon future. Nevertheless, the findings are significant.
China has performed well above the global average, shined as the regional leader in East Asia, matched, if not outperformed, OCED countries in many dimensions, many countries with much lower investments and capacity have scored higher on renewable energy indicators.
Villa 31, an iconic urban settlement in the heart of Buenos Aires, is home to about 43,000 of the city’s poor. In Argentina, paradoxically, urban slums are called ‘villas’ – a word usually tied with luxury in many parts of the world.