Optimal distribution system restoration using PHEVs

Abstract

Power outages cost billions of dollars every year and jeopardise the lives of hospital patients. Traditionally, power distribution system takes a long time to recover after a major blackout, due to its top-down operation strategy. New technologies in modern distribution systems bring opportunities and challenges to distribution system restoration. As fast response energy resources, plug-in hybrid electric vehicles (PHEVs) can accelerate the load pickup by compensating the imbalance between available generation and distribution system load. This study provides a bottom-up restoration strategy to use PHEVs for reliable load pickup and faster restoration process. The optimisation problem of finding load pickup sequence to maximise restored energy is formulated as a mixed integer linear programming (MILP) problem. Moreover, the coordination between transmission and distribution restoration is developed to efficiently restore the entire system back to normal operating conditions. Simulation results on one 100-feeder test system demonstrate the efficiency of MILP-based restoration strategy and the benefit from PHEVs to restore more energy in given restoration time. The proposed restoration strategy has great potential to facilitate system operators to achieve efficient system restoration plans. It also provides incentives to deploy a large amount of PHEVs to improve system resiliency.

Proactive Rolling-Horizon based Scheduling of Hydrogen Systems for Resilient Power Grids

“…The operational costs including capital expenditures (CAPEX) are considered for generation assets based on National Renewable Energy Laboratory's (NREL) advanced technology baseline [23]. The H2 demand requested by FCEVs is calculated based on the method presented in [24]. These FCEVs are considered as Honda Clarity models [25] assuming that these cars arrive at the H2 fueling station with 45% H2 fuel in their tanks.…”

“…To show the flexibility of H2 systems during the normal and emergency operations, three CBDRS are considered. In (23) and (24), CBDR signals, shown as P DR Sgl , are expressed for electrolyzers and FC units. In the case of any external signal from DSO, based on their available capacity (electrolyzer, storage tank, and FC units), H2 systems follow the signal and act as load or generation asset based on equations (23) and (24).…”

“…In (23) and (24), CBDR signals, shown as P DR Sgl , are expressed for electrolyzers and FC units. In the case of any external signal from DSO, based on their available capacity (electrolyzer, storage tank, and FC units), H2 systems follow the signal and act as load or generation asset based on equations (23) and (24). Accordingly, in the case of N − m contingencies, H2 systems can act as long-term energy storage with longduration times compared to batteries.…”

Smart Scheduling of Household Appliances to Decarbonise Domestic Energy Consumption

“…In (5) and (6), x represents the data points of the detected signal and y represents the template appliance data points. R must be greater than the given threshold value, α, to verify the appliance detection method as shown in (7). This value α can be increased or reduced which would result in the detection of more or fewer appliances.…”

“…Ozturk et al used a ToU tariff within a self organising home energy network to reduce prices for the customer [5]. DSR can help to reduce peak demand through the coordinated control of electric vehicles (EVs), and PVs [6], [7]. Amongst the literature, there are papers which model specific appliances, for example Good et al considered DSR based on thermal energy storage in the form of hot water storage [8].…”