Data Incubator Proposal. Figure 2.

Tail Number of NY Flights, May 2014. Data source: BTS.
Figure 2a constructed by Ivonne Pena. Tail Number of NY Flights, May 2014. Data source: BTS.
Figure 2b. Fuel consumption of all engine types of aircrafts. Data Source: ICAO.
Figure 2b constructed by Ivonne Pena. Fuel consumption of all engine types of aircrafts. Data Source: ICAO.
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Daily power generation comparison between two renewable energy portfolios and a diesel system.

Analysis performed by Ivonne Peña and Westeva, for a village in Latin America. The figure shows interactively the moment of the day in which each of the systems (represented by bars) are meeting a hypothetical 24-hour demand that meets all the needs in the village (represented as a vertical yellow line). The diesel system can only provide electricity for four hours per day, approximately between 10 am and 2 pm. The solar-battery system is able to meet demand at most moments and with flexible demand-response mechanisms, it can shift some load peaks at moments when the system is more reliable. The wind-solar-battery system is more expensive but can support the allocation of some reserves. It can encourage economic development by the provision of more power at all times. Graphic design support by Nathalie Ospina.

Power generation of three power systems, and comparison with hypothetical demand profile, in an off-grid large village of Colombia.
Power generation of three power systems, and comparison with hypothetical demand profile, in an off-grid large village of Colombia.

LCOE comparison in a rural location in Colombia, for different Renewable Energy Portfolios.

Analysis performed by Ivonne Peña and Westeva. This graph shows the electricity costs for different renewable power systems of a rural village in Latin America.

Levelized cost of electricity ($/kWh) for different portfolios of renewable energy, in one off-grid location in Colombia.
Levelized cost of electricity ($/kWh) for different portfolios of renewable energy, in one off-grid location in Colombia. [Solar and wind speed data, investment data and technology performance data from Westeva, 2014.] Infographic developed by Ivonne Peña with graphic support from Nathalie Ospina.

Graphics developed for the analysis of wind power output and grid congestion in Portugal. June 2014.

As part of my Ph.D. thesis, I conducted an analysis on grid congestion, to determine the best substations where to connect more wind parks.

These are some of the graphics that show that congestion is not an immediate issue for wind power developers in some places in Portugal.

Graph 1 shows wind power output and the resulting grid congestion as more wind power capacity is added:

Conceptual graph of the wind power curtailment that results from the addition of more wind power capacity, in one region of Portugal.
Graph 1. Conceptual graph of the wind power curtailment that results from the addition of more wind power capacity, in one region of Portugal.

Graph 2 shows the daily variations of power demand over a year, in a region of Portugal. The variations in power demand impact grid congestion. If power demand is large when non-dispatchable units (as wind parks in Portugal) are producing large amounts of power, there will be no grid congestion -assuming grid capacity is at least equal to the peak of power demand. But if for example, power demand is low when wind blows the most (say at 2 in the morning), grid can get congested because not all power produced is consumed.

Graph 2. Daily variations of Power demand over a year.
Graph 2. Daily variations of Power demand over a year.

Finally, graph 3 shows wind power and demand frequency plots. Grid capacity is a function of these two variables and others (not shown here).

Graph 3. Power demand and wind power output in a region in Portugal.
Graph 3. Power demand and wind power output in a region in Portugal.

Timeline comparing renewable energy incentives in some E.U. countries. August 2014.

Timeline developed for Ph.D. thesis @Carnegie Mellon University, “Retrospective and prospective analysis of wind power policies in Portugal,” by Ivonne Peña.

Timeline developed by Ivonne Peña. Graphic support by Nathalie Ospina
Timeline developed by Ivonne Peña. Graphic support by Nathalie Ospina

Timeline of renewable energy incentives in Portugal and the E.U. August 2014.

Timeline developed for Ph.D. thesis @Carnegie Mellon University, “Retrospective and prospective analysis of wind power policies in Portugal,” by Ivonne Peña.

Timeline developed by Ivonne Peña. Graphic support by Nathalie Ospina.
Timeline developed by Ivonne Peña. Graphic support by Nathalie Ospina.