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Fig. 3 Spot and hourly mean power in a wind generator. The outline of the generic model of a RES producer coupled to a energy storage and connected to a public grid is shown in Figure 2. The RES provides a power P(t) speed or sun radiation. The in the hourly period that varies according the wind forecasting procedure before planned and the fed power; t the measurement systems of system. These values wil power planned to be sent to the grid is P’, its value had been computed by means of some being sent to the TSO. The power that the system is effectively sending to the grid is Po(t). The difference Po(t)-P' is the deviation between the his difference is logged by the TSO and the control provide parameters that will reduce the economic billing of the RES producer. Although we have high quality prediction, the power of the RES is varying strongly in a hourly period as is illustrated in Figure 3. some quality

Figure 3 Spot and hourly mean power in a wind generator. The outline of the generic model of a RES producer coupled to a energy storage and connected to a public grid is shown in Figure 2. The RES provides a power P(t) speed or sun radiation. The in the hourly period that varies according the wind forecasting procedure before planned and the fed power; t the measurement systems of system. These values wil power planned to be sent to the grid is P’, its value had been computed by means of some being sent to the TSO. The power that the system is effectively sending to the grid is Po(t). The difference Po(t)-P' is the deviation between the his difference is logged by the TSO and the control provide parameters that will reduce the economic billing of the RES producer. Although we have high quality prediction, the power of the RES is varying strongly in a hourly period as is illustrated in Figure 3. some quality

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This paper focuses on the modelling and simulation of energy storage systems coupled to RES producers to increase the quality of the energy feed to the public grids. Our approach is to study the energy and power management rather than the modelling and simulation associated with any specific technology, device or technical solution. We agree that a first level of a simulation can be a general one based on the power and energy flows and transfer, while a more detailed simulation of a defined solution, which must use defined models for wind farms[6] and grid interaction[7], can be achieved after the analysis of the results obtained in the power and energy oriented simulation. For example, a general simulation can provide the total amount of energy storage needed for an RES system based on its logged power data. At this stage, it does not matter which kind of technology is used in a more detailed forward modelling. This paper includes a mathematical model of power and energy transfer between the RES source, the energy storage and the public grid. A simulation based on Simulink is carried out and the results for different strategies and configurations are provided.
This paper focuses on the modelling and simulation of energy storage systems coupled to RES producers to increase the quality of the energy feed to the public grids. Our approach is to study the energy and power management rather than the modelling and simulation associated with any specific technology, device or technical solution. We agree that a first level of a simulation can be a general one based on the power and energy flows and transfer, while a more detailed simulation of a defined solution, which must use defined models for wind farms[6] and grid interaction[7], can be achieved after the analysis of the results obtained in the power and energy oriented simulation. For example, a general simulation can provide the total amount of energy storage needed for an RES system based on its logged power data. At this stage, it does not matter which kind of technology is used in a more detailed forward modelling. This paper includes a mathematical model of power and energy transfer between the RES source, the energy storage and the public grid. A simulation based on Simulink is carried out and the results for different strategies and configurations are provided.
forecast error. This is because even if the actual infeed deviates from the forecast level on only a few days of the year, the TSO must also be prepared for this improbable eventuality and have sufficient capacity available, spinning reserve, for a reliable supply to still guaranteed and the correct balance between generation and load to be restored.
forecast error. This is because even if the actual infeed deviates from the forecast level on only a few days of the year, the TSO must also be prepared for this improbable eventuality and have sufficient capacity available, spinning reserve, for a reliable supply to still guaranteed and the correct balance between generation and load to be restored.
Fig. 4 Simulink blocks to test the storage system. that implements the feedback innovation term to correct the states of bias.
Fig. 4 Simulink blocks to test the storage system. that implements the feedback innovation term to correct the states of bias.
In the columns without the innovation term, the Reference Model performs better than the other forecasting. It has the lowest values in out band and deviation energy. However, it was the more unstable because the storage became full and empty in the simulation. The last three columns have the best performance in quality. The storage was neither full nor empty, and also the final storage capacity was also close to the initial one. This means that the storage was always in the linear zone and the out band and deviation energies were null. However, the energy amount fed to the grid was lower in the three cases than in the same strategies in the previously considered groups. 5. Conclusion
In the columns without the innovation term, the Reference Model performs better than the other forecasting. It has the lowest values in out band and deviation energy. However, it was the more unstable because the storage became full and empty in the simulation. The last three columns have the best performance in quality. The storage was neither full nor empty, and also the final storage capacity was also close to the initial one. This means that the storage was always in the linear zone and the out band and deviation energies were null. However, the energy amount fed to the grid was lower in the three cases than in the same strategies in the previously considered groups. 5. Conclusion
Fig. 6 Planned power sent to TSO efficiency. The simulator provides precise data about the increase in quality parameters and the corresponding decreasing in the amount of energy fed to the grid.
Fig. 6 Planned power sent to TSO efficiency. The simulator provides precise data about the increase in quality parameters and the corresponding decreasing in the amount of energy fed to the grid.
Table 1 Quality parameters by using different forecasting strategies: P (persitence), R(Reference model) and I(ideal), as well as NS (no storage) and (in )innovation filter. [7] A.D. Hansen, P. Sorensen, F. Blaabjerg and J. Becho, “Dynamic modelling of wind farm grid interaction”, Wind Engineering, Vol. 26, No. 4, pp 191-208, 2002. [8] Simulink 7 Reference, The MathWorks Inc., 2008
Table 1 Quality parameters by using different forecasting strategies: P (persitence), R(Reference model) and I(ideal), as well as NS (no storage) and (in )innovation filter. [7] A.D. Hansen, P. Sorensen, F. Blaabjerg and J. Becho, “Dynamic modelling of wind farm grid interaction”, Wind Engineering, Vol. 26, No. 4, pp 191-208, 2002. [8] Simulink 7 Reference, The MathWorks Inc., 2008
References [1] I. Erlich, W. Winter and A. Dittrich, “Advanced requirements for the integration of wind turbines into the German transmission system” in JEEE Power Engineering Society General Meeting, 2006, pp 7-13.
References [1] I. Erlich, W. Winter and A. Dittrich, “Advanced requirements for the integration of wind turbines into the German transmission system” in JEEE Power Engineering Society General Meeting, 2006, pp 7-13.
Related topics:
Environmental ScienceRenewable EnergyPower QualitySystems SimulationModelling and Simulation of Power Systems
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