scholarly journals Methodology for Estimating the Spatial and Temporal Power Demand of Private Electric Vehicles for an Entire Urban Region Using Open Data

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2081
Author(s):  
Florian Straub ◽  
Simon Streppel ◽  
Dietmar Göhlich
Keyword(s):  
Electric Vehicles ◽  
Energy Demand ◽  
Open Data ◽  
Temporal Distribution ◽  
Electrical Energy ◽  
Mobility Model ◽  
Total Power ◽  
Urban Region ◽  
Power Demand ◽  
Electrical Grid

With continuous proliferation of private battery electric vehicles (BEVs) in urban regions, the demand for electrical energy and power is constantly increasing. Electrical grid infrastructure operators are facing the question of where and to what extent they need to expand their infrastructure in order to meet the additional demand. Therefore, the aim of this paper is to develop an activity-based mobility model that supports electrical grid operators in detecting and evaluating possible overloads within the electrical grid, deriving from the aforementioned electrification. We apply our model, which fully relies on open data, to the urban area of Berlin. In addition to a household travel survey, statistics on the population density, the degree of motorisation, and the household income in fine spatial resolution are key data sources for generation of the model. The results show that the spatial distribution of the BEV charging energy demand is highly heterogeneous. The demand per capita is higher in peripheral areas of the city, while the demand per m2 area is higher in the inner city. For reference areas, we analysed the temporal distribution of the BEV charging power demand, by assuming that the vehicles are solely charged at their residential district. We show that the households’ power demand peak in the evening coincide with the BEV power demand peak while the total power demand can increase up to 77.9%.

scholarly journals A Sizing Method for PV–Battery–Generator Systems for Off-Grid Applications Based on the LCOE

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1988
Author(s):  
Ioannis E. Kosmadakis ◽  
Costas Elmasides
Keyword(s):  
Renewable Energy ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Temporal Distribution ◽  
Electrical Energy ◽  
Optimal Number ◽  
Diesel Generator ◽  
Levelized Cost Of Electricity ◽  
Sufficient Power ◽  
Battery Energy

Electricity supply in nonelectrified areas can be covered by distributed renewable energy systems. The main disadvantage of these systems is the intermittent and often unpredictable nature of renewable energy sources. Moreover, the temporal distribution of renewable energy may not match that of energy demand. Systems that combine photovoltaic modules with electrical energy storage (EES) can eliminate the above disadvantages. However, the adoption of such solutions is often financially prohibitive. Therefore, all parameters that lead to a functionally reliable and self-sufficient power generation system should be carefully considered during the design phase of such systems. This study proposes a sizing method for off-grid electrification systems consisting of photovoltaics (PV), batteries, and a diesel generator set. The method is based on the optimal number of PV panels and battery energy capacity whilst minimizing the levelized cost of electricity (LCOE) for a period of 25 years. Validations against a synthesized load profile produced grid-independent systems backed by different accumulator technologies, with LCOEs ranging from 0.34 EUR/kWh to 0.46 EUR/kWh. The applied algorithm emphasizes a parameter of useful energy as a key output parameter for which the solar harvest is maximized in parallel with the minimization of the LCOE.

Robotic Expert System for Energy Management in Distributed Grid Ecosystem

2020 ◽  
Vol 9 (1) ◽  
pp. 1-26
Author(s):  
Ononiwu Gordon Chiagozie ◽  
Kennedy Chinedu Okafor ◽  
Nwaokolo F I
Keyword(s):  
Expert System ◽  
Energy Management ◽  
Energy Demand ◽  
Dimensional Space ◽  
Total Power ◽  
Support Vector ◽  
Self Healing ◽  
Power Demand ◽  
Look Ahead ◽  
Micro Grid

A robotic expert system (RES) for energy management (EM) in community-based micro-grids is developed using a fuzzy computational scheme. Within the micro-grid multi-dimensional space, embedded algorithms for residential homes, sectors and central controller units are introduced to perform EM in a collaborative manner. Demand response and load shedding are carried out within the community micro-grid to ascertain the behavioral responses based on changes in power demand levels. Various tests are carried out with an observable low error margin. It was observed that the system reduced the total power demand on the micro-grid by 20% of the total distributed power. Micro-grid RES, neuro-fuzzy control (NFC), and support vector regression (SVR) evaluations are compared considering the home units at 40kW of the generated capacity. The results gave a 35.79%, 31.58% and 32.63% energy demand, respectively. Consequently, RES provides a grid look-ahead prediction, annotated-self healing, and stability restoration.

Technical Economic Analysis of a Low Power Hybrid Wind-Solar System Grid Connected

2014 ◽  
Vol 704 ◽  
pp. 204-208
Author(s):  
Jorge Serván Sócola ◽  
Daniel Marcelo Aldana
Keyword(s):  
Energy Demand ◽  
Financial Analysis ◽  
Renewable Energy Sources ◽  
Electrical Energy ◽  
Residential Areas ◽  
Electrical Grid ◽  
Sizing System ◽  
Residential House ◽  
The Government ◽  
Main Components

The main aim of this work is to develop a methodology that allows performing an economic technical analysis of an energy generation system in base to renewable sources, with the capacity to feed to an average residential house connected to the electrical grid. As a first step should be to determine the energy demand for a residential user of the study area. Later, it performs an analysis in steady state of the energetic resources, in order to evaluate the energetic potential and right-sizing system available for energy demand estimated. Once dimensioned, the system proceeds to select the main components that conform it, makes the calculations for the dimensioning of the electrical system, and selects the type of structures of support as well as the location with a better provision inside the location area. Following each step of this methodology, it has been selected like a better alternative: a wind turbine of 2 kW and four photovoltaic panels of 240 Wp like main energetic sources of the hybrid, which will produce a total of 4055.24 kWh yearly, covering the annual demand with an surplus energy of 609.64 kWh a year and to a cost of 0.361 $/kWh, which is higher than the average cost of the electrical energy inside the residential areas. What concludes by the economic-financial analysis, the need of a co-financing and a policy of incentives from the government that benefits to the small auto-producers to use renewable energy sources.

scholarly journals Compressed Air Energy Storage Installation for Renewable Energy Generation

2019 ◽  
Vol 112 ◽  
pp. 02010
Author(s):  
Claudia Borzea ◽  
Iulian Vlăducă ◽  
Dan Ionescu ◽  
Valentin Petrescu ◽  
Filip Niculescu ◽  
...  
Keyword(s):  
Energy Storage ◽  
Energy Demand ◽  
Electrical Power ◽  
Electrical Energy ◽  
Compressed Air ◽  
Compressed Air Energy Storage ◽  
Electrical Grid ◽  
Air Supply ◽  
Asynchronous Generator ◽  
Renewable Energy Generation

Compressed Air Energy Storage (CAES) installations are used for storing electrical power, under the form of potential energy from compressed air. The heat generated during compression can be stored to improve the efficiency of compression-expansion cycle. The solution presented consists of a 100 kW screw compressor driven by a 110 kW asynchronous three-phase motor. The compressor supplies air into vessels which store it until a high electrical energy demand arises. At that time, the compressed air is released into a 132 kW screw expander whose shaft spins a 132 kW asynchronous generator, producing electric power and supplying it into the electrical grid. Before expansion, the air must be preheated in order to avoid the freezing of expansion equipment. If the heat generated during compression is used for air preheating before expansion, the process is adiabatic. A demonstrative model of the installation is currently being developed, with the expander part being completed so far. The maximum power to be produced was calculated to be around 100 kW. During expander commissioning tests with air supply from a 250 kW high pressure compressor, a maximum generated power of 49.7 kW was attained, expected to be higher when releasing air from the reservoirs.

Robotic Expert System for Energy Management in Distributed Grid Ecosystem

2022 ◽  
pp. 736-763
Author(s):  
Ononiwu Gordon Chiagozie ◽  
Kennedy Chinedu Okafor ◽  
Nwaokolo F I
Keyword(s):  
Expert System ◽  
Energy Management ◽  
Energy Demand ◽  
Dimensional Space ◽  
Total Power ◽  
Support Vector ◽  
Self Healing ◽  
Power Demand ◽  
Look Ahead ◽  
Micro Grid

A robotic expert system (RES) for energy management (EM) in community-based micro-grids is developed using a fuzzy computational scheme. Within the micro-grid multi-dimensional space, embedded algorithms for residential homes, sectors and central controller units are introduced to perform EM in a collaborative manner. Demand response and load shedding are carried out within the community micro-grid to ascertain the behavioral responses based on changes in power demand levels. Various tests are carried out with an observable low error margin. It was observed that the system reduced the total power demand on the micro-grid by 20% of the total distributed power. Micro-grid RES, neuro-fuzzy control (NFC), and support vector regression (SVR) evaluations are compared considering the home units at 40kW of the generated capacity. The results gave a 35.79%, 31.58% and 32.63% energy demand, respectively. Consequently, RES provides a grid look-ahead prediction, annotated-self healing, and stability restoration.

scholarly journals Walking on sunshine: Pairing electric vehicles with solar energy for sustainable informal public transport in sub-Saharan Africa

2021 ◽  
Author(s):  
MJ Booysen ◽  
Chris Abraham ◽  
Arnold Rix ◽  
Innocent Ndibatya
Keyword(s):  
Electric Vehicles ◽  
Public Transport ◽  
Energy Demand ◽  
Sub Saharan Africa ◽  
Solar Pv ◽  
Mobility Patterns ◽  
Electrical Grid ◽  
Spatio Temporal ◽  
Sub Saharan ◽  
The Impact

Minibus taxi public transport is a seemingly chaotic phenomenon in the developing cities of the Global South with unique mobility and operational characteristics. Eventually this wide-spread fleet of minibus taxis will have to transition to electric vehicles. This paper examines the impact of this inevitable evolution on a city-wide scale in Kampala, Uganda. We present a generic simulation environment to assess the grid impact and charging opportunities, given the unique paratransit mobility patterns. We used floating car data to assess the energy requirements of electric minibus taxis, which will have a knock-on effect on the region's already fragile electrical grid. We used spatio-temporal and solar photovoltaic analyses to assess the informal and formal stops that would be needed for the taxis to recharge from solar PV in the region's abundant sunshine. The results showed energy demand from a median of 224 kWh/day to a maximum of 491 kWh/day, with a median charging potential (stationary time) across taxis of 8 h/day to 12 h/day. The potential for charging from solar PV was 0.24 kWh/m^2 to 0.52 kWh/m^2. Our simulator and results will allow traffic planners and grid operators to assess and plan for looming electric vehicle roll-outs to the most-used mode of transport in Africa.

scholarly journals A Provisional Model for the Optimal Management of a Charging Station Assisted by Photovoltaic Panels for Plug-In Electric Vehicles

2021 ◽  
Vol 8 ◽  
pp. 105-117
Author(s):  
Rizzo Gianfranco ◽  
Tiano Francesco Antonio ◽  
Marino Matteo
Keyword(s):  
Electric Vehicles ◽  
Hybrid Electric Vehicles ◽  
Co2 Reduction ◽  
Electrical Energy ◽  
Primary Energy ◽  
Optimal Management ◽  
Nonlinear Constrained Optimization ◽  
Electrical Grid ◽  
Charging Station ◽  
Battery Capacity

There is a strongly increasing diffusion of Electric Vehicles (EV) and Plug-in Hybrid Electric Vehicles (PHEV), in order to reduce air pollution in urban environment and to mitigate the global warming issues. Anyway, the achievement of this latter goal strictly depends on the source of primary energy used to generate electrical energy. In the paper, a model for the optimal design and operation of a charging station for EV and PHEV assisted by a PhotoVoltaic (PV) plant is presented. A provisional model for the estimation of the incoming insolation, based on cloudiness prevision, is integrated with a nonlinear constrained optimization algorithm, in order to satisfy the load while minimizing the recourse to electrical grid for battery storage charging. Simulations on different locations and charging loads for various size of PV plant and battery capacity are presented, and the benefits in terms of CO2 reduction discussed.

scholarly journals Car-Access Attractiveness of Urban Districts Regarding Shopping and Working Trips for Usage in E-Mobility Traffic Simulations

2021 ◽  
Vol 13 (20) ◽  
pp. 11345
Author(s):  
Florian Straub ◽  
Otto Maier ◽  
Dietmar Göhlich
Keyword(s):  
Energy Demand ◽  
Electrical Energy ◽  
City Centre ◽  
Traffic Flows ◽  
New Approach ◽  
Electrical Grid ◽  
Car Traffic ◽  
Conventional Models ◽  
The City ◽  
Traffic Simulations

With the continuous proliferation of private battery electric vehicles, the demand for electrical energy and power is constantly increasing. As a result, the electrical grid may need to be expanded. To plan for such expansion, information about the spatial distribution of the energy demand is necessary. This can be determined from e-mobility traffic simulations, where travel schedules of individuals are combined with an attractiveness rating of locations to estimate traffic flows. Typically, attractiveness is determined from the “size” of locations (e.g., number of employees or sales area), which is applicable when all modes of transportation are considered. This approach leads to inaccuracies for the estimation of car traffic flows, since the parking situation is neglected. To overcome these inaccuracies and fill this research gap, we have developed a method to determine the car-access attractiveness of districts for shopping and working trips. Our method consists of two steps. First, we determine the car-access attractiveness of buildings within a district based on the parking situation of each individual building and then aggregate the results at the district level. The approach is demonstrated for the city of Berlin. The results confirm that conventional models cannot be used to determine the car-access attractiveness of districts. According to these models, attractive districts are predominantly located in the city centre due to the large amount of sales areas or the large number of employees. However, due to the high density of buildings, only limited space is available for parking. Attractive districts rated according to our new approach are mainly located in the outer areas of the city and thus match the parking situation.

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