Reserve Capability Assessment Considering Correlated Uncertainty in Future Distribution System
Under the scenario assumption at the Electra project the distribution systems of future shall require active monitoring and control for addressing challenges and achieving climate targets. There is a transition towards smart distribution system that shall become a strong enabler in INCREASing the share of renewable energy sources. The fluctuating nature of such sources causes imbalance in real and reactive power (supply != demand) and hence creates frequency and voltage problems. The flexibility offered by the resource in distribution network can play an important role in maintaining the energy balance in the network. These resources can include generators, active demand response and others. USEF defines the roles, responsibilities and standardizes the approaches for handling this flexibility among players like distribution network operator, aggregator, balancing authority, transmission system operator, producers, suppliers and customers. The framework is a guiding beacon in addressing the technical and economic challenges in the smart distribution.
Among many hurdles on the way, an important challenge is the limited monitoring and control infrastructure for a relatively large geographical area. Among control approaches proposed in literature, a CELL based approach is becoming popular for decreasing the complexity of this challenge. The cell is defined as a control area with well defined boundaries in MV and LV networks and having a dedicated cell controller. The control mechanism in a cell is obliged to perform assessment, aggregation and the allocation of the flexibility from distribution system resources. This activity needs to be performed while considering the uncertainty in resource availability and dispatch. During research, we have found that the state of the art applications in power systems for demand and reserve allocation are conservative and costly. Particularly, the decisions about the demand and reserve are based on interval theory which specifies the requirements based on uncertainty intervals. This has motivated the development of novel geometric optimization methods for this purpose. The algorithm captures the correlated nature of demand and uncertainty in the first order dynamics i.e. power capacity, required ramp-rate and energy using an envelope representation. The allocation of demand and reserves from this envelope among the resource capability models has lead to decrease in the operational costs. The technical advantages spans from support for the correlated uncertain variables to defining the probabilistic confidence on the results.
For detail please see,
Reserve Capability Assessment Considering Correlated Uncertainty in Microgrid