In response to climate change concerns, most of the industrialised countries have committed in recent years to increase their share of Renewable Energy Sources to reduce Greenhouse Gas emissions. ...Therefore, the rapid deployment of small-scale photovoltaic (PV) systems, mainly in residential applications, is starting to represent a considerable portion of the available electrical power generation and, for this reason, the stochastic and intermittent nature of these systems are affecting the operation of centralised generation (CG) resources. Network operators are constantly changing their approach to both short-term and long-term forecasting activities due to the higher complexity of the scenario in which more and more stakeholders have active roles in the network. An increasing number of customers must be treated as prosumers and no longer only as consumers. In this context, storage technologies are considered the suitable solution. These can be necessary in order to solve and fill the problems of the renewable distributed sources are introducing in the management of the network infrastructure. The aim of this work was to create a model in order to evaluate the impact of power generation considering PV systems in Australia along with a model to simulate Battery Energy Storage Systems (BESSs) and Electric Vehicles future contributions using MATLAB. The methodology used to develop these models was based on statistical assumptions concerning the available details about PV systems installed and current storage technologies. It has been shown that in all the scenarios analysed, the future adoption of rooftop PV panels and impact on the CG is incredibly higher than the uptake of energy storage systems. Hence, the influence on the demand will be driven by the behaviour of the PV systems. Only in the hypothetical scenario in which the installations of BESSs will assume comparable levels of the PV systems, it will be possible to better manage the centralised resources.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Among Renewable Energy Sources (RES), wind energy is emerging as one of the largest installed renewable-power-generating capacities. The technological maturity of wind turbines, together with the ...large marine wind resource, is currently boosting the development of offshore wind turbines, which can reduce the visual and noise impacts and produce more power due to higher wind speeds. Nevertheless, the increasing penetration of wind energy, as well as other renewable sources, is still a great concern due to their fluctuating and intermittent behavior. Therefore, in order to cover the mismatch between power generation and load demand, the stochastic nature of renewables has to be mitigated. Among proposed solutions, the integration of energy storage systems in wind power plants is one of the most effective. In this paper, a Hybrid Energy Storage System (HESS) is integrated into an offshore wind turbine generator with the aim of demonstrating the benefits in terms of fluctuation reduction of the active power and voltage waveform frequency, specifically at the Point of Common Coupling (PCC). A MATLAB®/SimPowerSystems model composed of an offshore wind turbine interfaced with the grid through a full-scale back-to-back converter and a flywheel-battery-based HESS connected to the converter DC-link has been developed and compared with the case of storage absence. Simulations were carried out in reference to the wind turbine’s stress conditions and were selected—according to our previous work—in terms of the wind power step. Specifically, the main outcomes of this paper show that HESS integration allows for a reduction in the active power variation, when the wind power step is applied, to about 3% and 4.8%, respectively, for the simulated scenarios, in relation to more than 30% and 42% obtained for the no-storage case. Furthermore, HESS is able to reduce the transient time of the frequency of the three-phase voltage waveform at the PCC by more than 89% for both the investigated cases. Hence, this research demonstrates how HESS, coupled with renewable power plants, can strongly enhance grid safety and stability issues in order to meet the stringent requirements relating to the massive RES penetration expected in the coming years.
Innovating Multi-agent Systems Applied to Smart City Longo, Michela; Roscia, Mariacristina; Cristian Lazaroiu, George
Research Journal of Applied Sciences, Engineering and Technology,
05/2014, Volume:
7, Issue:
20
Journal Article
Reshaping transportation offer in metropolitan and suburban areas plays a fundamental role in complying with environmental commitment. A sustainable public transportation system is crucial to reduce ...air pollution and the overall environmental impact of transportation sector, going beyond mere displacement solutions offered. This paper presents how to implement a sustainable transportation solution starting from green shift investments in a small citizen centre. Two new bus lines were examined and planned to adapt the actual service to a potentially-evolving demand. Electric vehicle types were selected to compare full-electric with hydrogen traction systems. Moreover, particular attention was paid to the energy supply chain through Well-To-Tank analysis. Battery vehicles appear to be preferred, at the moment, when reliance on the national grid is prevailing showing affordable costs 1.8 €/km, ＋0.5 €/km with respect to the actual Diesel operations. However, also hydrogen energy vector resulted a competitive choice. Uncertainty in the market demand plays a great role and if reduced progressively, it allows to recover the heavy investments, given the high cost of ownership of 2.8 €/km. The research is enriched by the collaboration of a managerial representative of Arriva Italia, operator of local public transportation and an exponent of the scientific community.
•Public transportation systems have high impact on air pollution.•Design of a sustainable bus line in a small city to reduce pollution in the area.•Different energy vectors and supply chains assessed under economic indicators.•Comparison between electric traction and hydrogen fuel-cells.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPUK
Photovoltaic (PV) power generation is associated with volatility and randomness due to susceptibility to meteorological parameters intermittency. This poses difficulty in achieving the desired ...accuracy of PV power prediction with traditional models. Thus, this paper proposes a new predictive model based on deep learning techniques, optimized by the Bayesian optimization algorithm, to forecast a day-ahead PV power generation in high-resolution time steps. A systematic algorithm is introduced to improve time-series data quality via identifying missing samples in high-frequency datasets and imputing the missing values through the LASSO regression technique. The two data transformers for time and wind features are proposed to enhance their contributions, while other weather information, such as temperature and humidity, are considered. The proposed hybrid model incorporates CNN and BiLSTM to learn spatial and temporal patterns; moreover, the attention mechanism determines the weight values for input series and puts explicit attention on more essential parts to improve accuracy. Finally, the performance of the proposed model is compared with nine deep learning models, which are all optimized by the Bayesian optimization technique. The prediction performance comparison on actual data for a year reveals the superiority of the proposed model with the overall performance of 0,247, 0,232, 1,58%, and 0,461 in MAE, MSE, MAPE, and RMSE, respectively.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Photovoltaic system prototype with sun tracking.•Energy analysis of fixed and sun tracking built prototypes.•Experimental tests in different environmental conditions.•Theoretical and experimental ...validation of the prototype.
Photovoltaic technology allows to directly convert solar energy into electrical energy with clear advantages: no environmental impact during operation, reliability and durability of the systems, reduced operating costs and maintenance, ability to both supply remote customers and simply connect to the electrical network. This paper evaluates the performance of two photovoltaic systems: one fixed and one equipped with a sun tracker. The objective of this research is to analyze the increase of daily produced energy by using the sun tracking system. The analysis accounts also the energy consumption of the sun tracker. An analytical approach is proposed. To validate the results through experimental tests, two alternative low power PV systems were built. Each system consists of a PV source, a MPPT (Maximum Power Point Tracker) power converter and a 12V–40Ah electrochemical battery, which is used as electric load. The sun tracker system evidenced an important growth of power production during morning and evening.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPUK
The strong growth of the solar power generation industry requires an increasing need to predict the profile of solar power production over a day and develop highly efficient and optimized stand-alone ...and grid-connected photovoltaic systems. Moreover, the opportunities offered by battery energy storage systems (BESSs) coupled with photovoltaic (PV) systems require an ability to forecast the load power to optimize the size of the entire system composed of PV panels and storage devices. This paper presents a sizing and control strategy of BESSs for dispatching a photovoltaic generation farm in the 1-h ahead and day-ahead markets. The forecasting of the solar irradiation and load power consumption is performed by developing a predictive model based on a feed-forward neural network trained with the Levenberg-Marquardt back-propagation learning algorithm.
Smart grids can be a good challenge for the near future if they are intelligently managed. Therefore, the exploitation of the energy resources distributed into a network is one of the most discussed ...themes in actual scientific literature, together with the attention paid to power quality (PQ) improvement. This paper aims to provide a possible solution to some common and dangerous PQ problems and voltage sags, considering the large diffusion of electric vehicles. A deep energy and power analysis to evaluate the feasibility of the vehicle-to-grid (V2G) function to compensate for PQ disturbances will be presented.
PDF
