Penetration of advanced sensor systems such as advanced metering infrastructure (AMI), high-frequency overhead and underground current and voltage sensors have been increasing significantly in power distribution systems over the past few years. According to U.S. energy information administration (EIA), the aggregated AMI installation experienced a 17 times increase from 2007 to 2012. The AMI usually collects electricity usage data every 15 minute, instead of once a month. This is a 3,000 fold increase in the amount of data utilities would have processed in the past. To unleash full value of the complex data sets, innovative big data algorithms need to be developed to transform the way we operate and plan for the smart grid.
Enhanced distribution system modeling
Distribution network topology identification (phase connectivity identification, customer to transformer association estimation)
Distribution network parameter estimation
Spatio-temporal load forecast and renewable generation forecast
Energy theft detection
Three-phase state estimation in power distribution systems
Predictive equipment maintenance
Valuation and optimization of DERs in power distribution network
Diversification factor and load factor estimation
Solar PV adoption forecast and EV adoption forecast
In the past 20 years, wholesale power markets operating in transmission systems have been effective at coordinating the operations of thousands of centralized power plants. This coordination needs to be extended to the operations of millions of DERs. To do this efficiently, a Distribution system operator (DSO) managed electricity market seems to be a viable solution. Although the concept of a DSO-managed electricity market has been introduced, a key algorithm for operating the market is still in its infancy. This algorithm is three-phase optimal power flow (OPF), and it needs significant development.
Design Integrated wholesale and retail market. The integrated market architecture is shown in the figure below.
Develop DSO market, three-phase DCOPF and ACOPF.
The proposed three-phase ACOPF algorithm is not only computationally efficient but also guarantees global optimality on all IEEE distribution test circuitsRead more →
Driven by environmental regulations and rapidly falling renewable prices, the share of renewable generation in global electrical energy mix is expected to increase significantly over time. The intermittency of renewable resources has created new challenges in the transmission system operations.
Energy storage system is well poised to mitigate uncertainties of renewable generation outputs. However, there are several challenges to the widespread deployment of energy storage. As identified in the U.S. Department of Energy report, the most crucial hurdle to storage adoption is how to ensure energy storage are cost competitive with other energy resources. To overcome this hurdle my research group developed a comprehensive optimization and valuation model (ESVOT) which allows energy storage to provide multiple electricity market products simultaneously.
ESVOT allows the user to conduct a comprehensive stochastic valuation of energy storage systems. In addition, ESVOT identifies the optimal energy storage integration location, size and technology for each customer.Read more →