1,720,954 research outputs found
Optimizing EV charger participation across different power markets: a multi-market approach to aFRR, mFRR, and local flexibility markets
No full textAs Europe accelerates toward carbon neutrality under the European Green Deal and Fit for 55 framework, electric vehicles (EVs) are emerging as a cornerstone of the decarbonized transport sector. To meet ambitious emissions targets, the European Union expects tens of millions of EVs on the road by 2030, necessitating a rapid and large-scale rollout of EV charging infrastructure. While this transition offers a path to a cleaner energy future, it simultaneously presents technical and economic challenges for electricity networks, such as grid congestion and increased demand. However, with the advent of smart charging and aggregated optimization strategies, EV chargers can shift from being passive loads to becoming active, revenue-generating assets participating in electricity and flexibility markets, and relieving the grid from congestion. This study explores the multi-market revenue optimization potential of EV chargers through a custom-built optimizer using Python designed to simulate realistic charger participation in four key markets: mFRR, aFRR, FCR-D, and Local Flexibility Markets. Using historical real-world data from Denmark and Sweden, the optimizer allocates available EV charging capacity across these markets with the objective of maximizing revenue, while adhering to operational constraints such as minimum bid size, market price and volumes, market exclusivity and participation rules, availability windows and priority allocation logic, in addition to limitations related to the EV chargers’ available power capacity. Simulation results show that mFRR consistently outperformed other markets across all zones in terms of normalized revenue (EUR/MW), with DK2, SE3, and SE4 offering the highest potential due to their deeper, more volatile market structures. LFMs also demonstrated substantial value, particularly in SE3 and SE4 during periods of congestion, reinforcing their role as a strategic addition to the revenue portfolio. Meanwhile, FCR-D was found to act primarily as a fallback option, utilized only when other markets’ volume or revenue thresholds could not be met. Importantly, zones with richer market dynamics and volatility saw the highest uplift from optimized multi-market participation. The optimizer outperformed static single-market strategies by 31% in DK2 and 21% in SE4, validating the case for integrated, intelligent trading strategies. Temporal analysis across hours of the day and days of the week further revealed correlations between EV charger availability and market price signals, with revenue peaks aligning with grid stress periods (even though available f lexible charging capacity decreases during that period) and with available flexible capacity. In particular, weekday vs. weekend comparisons for aFRR and LFM participation highlighted nuanced trends, reinforcing the importance of temporal granularity in optimization models. In addition, actual mFRR EAM (Energy Activation Market) activation data was used in the analysis, enabling a realistic assessment of charging disruption due to energy dispatch. The EAM activation analysis provides granular insights into the frequency and magnitude of disruptions per activation price, revealing important trends regarding revenue-maximizing strategies that minimize customer impact (i.e a halt in charging). For instance, DK1 and DK2 demonstrated the highest simulated revenues at the highest energy activation price point of 100 EUR, incurring a charging disruption rate of 12% and 7% for DK1 and DK2 respectively. This suggests a more lucrative and mature EAM revenue potential, particularly in DK1, which benefits from cross-border integration with Germany and the Central European market, where mFRR activations are more frequent and better compensated. In contrast, the Swedish zones (SE1–SE4) showed a markedly different behavior, with earlier (relative to increasing activation prices with increments of 5 EUR between 5 and 100 EUR) bid rejections and fewer high-price activations. In these zones, the highest revenues were achieved at lower activation price ranges between 35 and 50 EUR, beyond which revenues declined due to reduced activation rates. This pattern indicates a less mature but developing EAM market in Sweden, where optimization opportunities are growing but still constrained by market dynamics and activation frequency. Bycombining technical feasibility, economic optimization, and behavioral insights from real-world activation data, this work shows how aggregated EV charging infrastructure can be systematically leveraged to support grid stability while unlocking new value streams. The optimizer framework helps aggregators, DSOs, and CPOs seeking to participate effectively in flexibility and frequency ancillary services markets, particularly as EU-wide market harmonization efforts like PICASSO and MARI continue to evolve. Ultimately, intelligent optimization stands as a crucial enabler for EVs to function not only as transport devices, but also as flexible, market-participating grid resources
Optimizing EV Charger Participation AcrossDifferent Power Markets : A Multi-MarketApproach to aFRR, mFRR, and LocalFlexibility Markets
No full textAs Europe accelerates toward carbon neutrality under the European Green Deal and Fit for 55 framework, electricvehicles (EVs) are emerging as a cornerstone of the decarbonized transport sector. To meet ambitious emissions targets, the European Union expects tens of millions of EVs on the road by 2030, necessitating a rapid and large-scale rollout of EV charging infrastructure. While this transition offers a path to a cleaner energy future, it simultaneously presents technical and economic challenges for electricity networks, such as grid congestion and increased demand. However, with the advent of smart charging and aggregated optimization strategies, EV chargers can shift from being passive loads to becoming active, revenue-generating assets participating in electricity and flexibility markets, and relieving the grid from congestion. This study explores the multi-market revenue optimization potential of EV chargers through a custom-built optimizer using Python designed to simulate realistic charger participation in four key markets: mFRR, aFRR, FCR-D, and Local Flexibility Markets. Using historical real-world data from Denmark and Sweden, the optimizer allocates available EV charging capacity across these markets with the objective of maximizing revenue, while adhering to operational constraints such as minimum bid size, market price and volumes, market exclusivity and participation rules, availability windows and priority allocation logic, in addition to limitations related to the EV chargers’ available power capacity. Simulation results show that mFRR consistently outperformed other markets across all zones in terms of normalized revenue (EUR/MW), with DK2, SE3, and SE4 offering the highest potential due to their deeper, more volatile market structures. LFMs also demonstrated substantial value, particularly in SE3 and SE4 during periods of congestion, reinforcing their role as a strategic addition to the revenue portfolio. Meanwhile, FCR-D was found to act primarily as a fallback option, utilized only when other markets’ volume or revenue thresholds could not be met. Importantly, zones with richer market dynamics and volatility saw the highest uplift from optimized multi-market participation. The optimizer outperformed static single-market strategies by 31% in DK2 and 21% in SE4, validating the case for integrated, intelligent trading strategies. Temporal analysis across hours of the day and days of the week further revealed correlations between EV charger availability and market price signals, with revenue peaks aligning with grid stress periods (even though available flexible charging capacity decreases during that period) and with available flexible capacity. In particular, weekday vs. weekend comparisons for aFRR and LFM participation highlighted nuanced trends, reinforcing the importance of temporal granularity in optimization models. In addition, actual mFRR EAM (Energy Activation Market) activation data was used in the analysis, enabling arealistic assessment of charging disruption due to energy dispatch. The EAM activation analysis provides granular insights into the frequency and magnitude of disruptions per activation price, revealing important trends regarding revenue-maximizing strategies that minimize customer impact (i.e a halt in charging). For instance, DK1 and DK2 demonstrated the highest simulated revenues at the highest energy activation price point of 100 EUR, incurring a charging disruption rate of 12% and 7% for DK1 and DK2 respectively. This suggests a more lucrative and mature EAM revenue potential, particularly in DK1, which benefits from cross-border integration with Germany and the Central European market, where mFRR activations are more frequent and better compensated. In contrast, the Swedish zones (SE1–SE4) showed a markedly different behavior, with earlier (relative to increasing activation prices with increments of 5 EUR between 5 and 100 EUR) bid rejections and fewer high-price activations. In these zones, the highest revenues were achieved at lower activation price ranges between 35 and 50 EUR, beyond which revenues declined due to reduced activation rates. This pattern indicates a less mature but developing EAM market in Sweden, where optimization opportunities are growing but still constrained by market dynamics and activation frequency. By combining technical feasibility, economic optimization, and behavioral insights from real-world activation data, this work shows how aggregated EV charging infrastructure can be systematically leveraged to support grid stability while unlocking new value streams. The optimizer framework helps aggregators, DSOs, and CPOs seeking to participate effectively in flexibility and frequency ancillary services markets, particularly as EU-wide market harmonization efforts like PICASSO and MARI continue to evolve. Ultimately, intelligent optimization stands as a crucial enabler for EVs to function not only as transport devices, but also as flexible, market-participating grid resources.När Europa accelererar mot koldioxidneutralitet inom ramen för European Green Deal och Fit for 55-paketet framträder elfordon (EV) som en hörnsten i transportsektorns omställning. För att nå de ambitiösa utsläppsmålen förväntar sig EU tiotals miljoner elfordon på vägarna till år 2030, vilket kräver en snabb och omfattande utbyggnad av laddinfrastrukturen. Denna övergång erbjuder en väg mot en renare energiframtid men medför samtidigt tekniska och ekonomiska utmaningar för elnäten, såsom nätkapacitetsbrist och ökad efterfrågan. Med smart laddning och aggregerade optimeringsstrategier kan dock laddstationer gå från att vara passiva laster till att bli aktiva, intäktsgenererande resurser som deltar i el- och flexibilitetsmarknader samt avlastar nätet. Denna studie undersöker potentialen för intäktsoptimering genom flexibel elfordonsladdning via en specialbyggd optimeringsmodell i Python, utvecklad för att simulera realistiskt deltagande på fyra centrala marknader: mFRR, aFRR, FCR-D och lokala flexibilitetsmarknader (LFM). Med hjälp av historiska data från Danmark och Sverige fördelar optimeraren tillgänglig laddkapacitet mellan marknaderna med målet att maximera intäkterna, samtidigt som den beaktar operativa begränsningar såsom minsta budstorlek, marknadspriser och volymer, marknadsexklusivitet och deltagarregler, tillgänglighetsfönster samt logik för prioritetsallokering – utöver begränsningar kopplade till den faktiska tillgängliga laddkapaciteten. Resultaten visar att mFRR konsekvent överträffade de övriga marknaderna i alla zoner vad gäller normaliserade intäkter (EUR/MW), där DK2, SE3 och SE4 visade högst potential tack vare djupare och mer volatila marknadsstrukturer. LFM uppvisade också betydande värde, särskilt i SE3 och SE4 under perioder av nätkapacitetsbrist, vilket stärker dess roll som ett strategiskt komplement i intäktsportföljen. FCR-D fungerade däremot främst som en “fallback”-marknad, använd endast när övriga marknader inte kunde uppfylla volym- eller intäktskraven. Zoner med mer dynamiska och volatila marknader visade störst nytta av optimerad fler-marknadsstrategi. Optimeraren överträffade statiska enskilda marknadsstrategier med exempelvis 31 % högre intäkter i DK2 och 21 % i SE4, vilket understryker värdet av integrerad och intelligent marknadsoptimering. Tidsanalysen visade dessutom tydliga samband mellan laddtillgänglighet och prissignaler, där intäktoppar sammanföll med perioder av hög nätbelastning – även när den tillgängliga flexibla effekten samtidigt minskade. Skillnader mellan vardag och helg, särskilt för aFRR och LFM, visade på ytterligare trender som framhäver vikten av temporal granularitet i modellerna. Utöver detta användes faktisk aktiveringsdata från mFRR:s Energy Activation Market (EAM), vilket möjliggjorde en realistisk bedömning av laddavbrott kopplade till energileverans. Analysen visade viktiga mönster kring intäktsmaximering med minimerad påverkan på användarna. Till exempel gav DK1 och DK2 högst simulerade intäkter vid högsta aktiveringspriset (100 EUR), samtidigt som laddavbrotten hölls på 12 % respektive 7 %. Detta antyder en mer mogen och lukrativ EAM-marknad, särskilt i DK1 som gynnas av gränsöverskridande integration med Tyskland och Centraleuropa, där mFRR-aktiveringar är både vanligare och bättre kompenserade. De svenska zonerna (SE1–SE4) visade däremot tidigare budavvisningar och färre högprisaktiveringar, med toppintäkter i spannet 35–50 EUR. Därefter minskade intäkterna till följd av färre aktiveringar, vilket tyder på en ännu omogen men växande EAM-marknad. Genom att kombinera teknisk genomförbarhet, ekonomisk optimering och insikter från faktisk aktiveringsdata visar denna studie hur laddinfrastruktur kan utnyttjas systematiskt för att både stärka nätstabiliteten och generera nya intäktsströmmar. Optimeringsramverket är därmed ett värdefullt verktyg för aggregatorer, nätägare och laddoperatörer som vill delta effektivt i flexibilitets- och frekvensmarknaderna, särskilt i takt med EU:s harmoniseringsinitiativ såsom PICASSO och MARI. Intelligenta optimeringsstrategier framstår därmed som en nyckel för att elfordon inte enbart ska fungera som transportmedel, utan även som flexibla resurser i framtidens elsystem
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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