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Alejandro Pena-Bello

Researcher at University of Geneva

Publications -  10
Citations -  440

Alejandro Pena-Bello is an academic researcher from University of Geneva. The author has contributed to research in topics: Battery (electricity) & Electricity. The author has an hindex of 6, co-authored 9 publications receiving 202 citations.

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Becoming prosumer: Revealing trading preferences and decision-making strategies in peer-to-peer energy communities

TL;DR: In this article, the authors analyzed homeowners' trading decisions in simulated P2P electricity trading scenarios and identified four target groups that systematically differed in their decision-making strategies ranging from price-focused prosumers (38.9%) to classic non-trading consumers (22.6%).
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Optimizing PV and grid charging in combined applications to improve the profitability of residential batteries

TL;DR: In this article, an economic optimization of the operation of a residential battery for two different applications, namely PV self-consumption and demand-load shifting under different dynamic tariff structures, is presented.
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Additional Emissions and Cost from Storing Electricity in Stationary Battery Systems.

TL;DR: A new battery production- and use-phase lifecycle emissions and cost analysis is performed to calculate the additional lifecycle greenhoues gas emissions (LCE) and costs (LCC) that arise from storing electricity in six different battery technologies, five applications, and three different geographies.
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Spatial analysis of distribution grid capacity and costs to enable massive deployment of PV, electric mobility and electric heating

TL;DR: In this paper, the impact of the deployment of PV, HP and EV on a lowvoltage distribution grid network serving 170'000 households in Switzerland, and analyse scenarios for their penetration in the years 2035 and 2050 using a detailed grid model in collaboration with a distribution system operator.
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Optimized PV-coupled battery systems for combining applications: Impact of battery technology and geography

TL;DR: In this paper, an open-source optimization framework was developed to determine the best-suited battery technology depending on the size and the applications combined, including PV self-consumption, demand load-shifting, demand peak shaving and avoidance of PV curtailment.