Distributed Renewable Energy Advanced Management System (DREAMS)
DREAMS with Smart Inverter
In response to the policy of energy transition in our country, a huge amount of renewable energy will be connected to the power distribution system in the future. In order to solve the problem of the maximum grid hosting capability of power distribution system limited by strength of power grid and intermittent power generation characteristic of renewable energy system, the “Distribution Renewable Energy Advanced Management System (DREAMS, shown in Figure)” can be used in coordination with smart inverter to adjust the power factor of renewable energy system to absorb the reactive power in order to maintain the voltage quality. In addition to the effective management of the impact of renewable energy on the power distribution system, the simulation analysis of power distribution feeder can verify that, under the same voltage variation constraint, the incorporation of DREAMS in conjunction with the self-adjustment function of smart inverter can enhance the permissible hosting capacity of renewable energy system of the feeder by more than 20%.
Figure 1. Distribution Renewable Energy Advanced Management System (DREAMS)
DREAMS Planning and Construction Schedule
- The power generation information of the sites with renewable energy system installation of more than 500kW will be collected according to TPC DNP3.0 communication protocol. The information shall include power generation volume of active and reactive power, power factor, voltage at Point of Common Coupling (PCC), and relevant setting values. The aforementioned information should be sent back to DREAMS via 4G communication system.
- In the medium-term, in response to the diversification of distributed energy resources, DREAMS management functions will be expandIn the future, it will collect real-time power information from distribution-level photovoltaic energy storage systems, electric vehicle charging pile management systems, and microgrid systems to provide timely dispatching reference for the dispatch center and also have load Integration and demand control functions.
- In long-term, DREAMS is expected to be interfaced with “Advanced Distribution Management System (ADMS)” to execute remote monitoring of renewable energy site via transmission of control command to the smart inverter of renewable energy in order to enhance the grid resilience and to maintain good power supply quality based on maximization of renewable energy.
DREAMS Planning in Future
The future plan is to adopt DREAMS in coordination with ADMS, so the network topology architecture can be updated in real time according to the switching operation decision of dispatch of power distribution system. And the system impact analysis can be conducted based on the power generation information of renewable energy collected by the renewable energy management system in order to derive the control decision of renewable energy smart inverter. In the end the control station and download the aforementioned control decision to the smart inverter via 4G communication system to achieve the modulation of renewable energy system power output in order to provide the auxiliary service function required by maintaining the safe operation of power grid.
Green Energy Estimate and Monitor System (GEMS)
Taiwan has a maritime island climate, characterized by distinct seasons and frequent afternoon thunderstorms. These weather patterns significantly impact solar photovoltaic (PV) power generation. To quickly detect deviations between actual PV power output and predicted values, visualizations are essential.
Therefore, on the existing Green Energy Estimate Monitor System (GEMS), a new solar photovoltaic standard deviation feature has been developed. It incorporates the concept of standard deviation mathematical models and utilizes historical and current solar photovoltaic generation data. The system calculates the average hourly power generation and the hourly variation in power generation (as indicated by the gray and black dashed lines in the diagram). It then presents the variation by adding or subtracting 1.64 times the standard deviation to create upper and lower trajectories (shown as light green dashed lines). Additionally, the standard deviation of historical hourly power generation variations (represented by the light blue area) is displayed as the range interval. The ramp of power generation every half hour on the monitoring day (that day) is normalized (multiplied by 2) to hourly, and the current situation is displayed quickly through real-time display (green bar).
Analyzing the standard deviation of each period through historical data of different days, the results suggested that 60 days is better. Calculated based on the changes in photovoltaic power generation for each hour in the past 60 days, there is a 90% chance that photovoltaic ramp of power generation for each hour of the day within the upper and lower trajectory of the standard deviation. It can be used as a reference for preparing Fast Responsive Reserve units to prepare Fast Responsive Reserve Units in advance to cope with the impact of photovoltaic power generation by seasonal changes.
