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Golshani, Amir

Publications and source records attributed to Golshani, Amir.

Real-Time Optimized Load Recovery Considering Frequency Constraints

A self-healing power grid can mitigate the impact of power outages and recover the affected area swiftly. To properly size the optimal amount and location of de-energized loads in the presence of both conventional and renewable sources, a precise optimization-based load recovery tool is proposed herein. The steady-state and transient behaviors of loads have been taken into account. The proposed tool contains three separate problems that interact with each other during the restoration period. The first-level problem determines the dispatching of generation units. The second-level problem comprises the non-linear algebraic equations, whose task is to provide the initial conditions for the third-level problem. Finally, the third-level problem intends to determine the optimal location and amount of load pickup through modeling the governor of generators as well as loads' dynamic behaviors. To examine the effectiveness of the proposed tool, a modified IEEE 39-system under a partial blackout condition has been tested. The results are verified by a commercial time-domain simulation software (PSS/E) to demonstrate the accuracy of the proposed approach. Ultimately, the impact of wind turbine frequency control on the load recovery process has been studied under different penetration levels.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimal distribution system restoration using PHEVs

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.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimal self-healing strategy for microgrid islanding

Renewable resource based microgrids provide reliable and cost-effective electricity with low carbon emissions. The flexibility of operating in grid-connected or islanded modes enables a microgrid to serve loads reliably. In the case of unexpected events happening to the main grid, the microgrid will isolate itself and operate in islanded mode to prevent any adversary impacts. The availability of renewable generation in the microgrid has significant impacts on the islanding strategy and different scenarios need to be considered. This study proposes a comprehensive microgrid self-healing strategy under different circumstances. The proposed strategy encompasses generation re-dispatch, network reconfiguration, and load shedding. The microgrid self-healing problem is formulated as a mixed-integer quadratic programming problem, which provides a globally optimal solution to facilitate smooth islanding of the microgrid. A modified Consortium for Electric Reliability Technology Solutions microgrid is used to conduct simulation under various scenarios. The simulation results demonstrate the efficiency of the proposed self-healing strategy in minimising costs of load shedding and generation with optimal switching actions.

optimal self-healing strategy↗

Integrated Transmission and Distribution Systems Restoration with Distributed Generation Scheduling

The self-healing smart grids enable system operators to quickly and efficiently recover transmission and distribution systems from outages and blackouts. The current restoration procedure solves the transmission and distribution system restoration problems separately without considering their impacts on each other, which may prolong the restoration process. However, with the emerging active distribution networks, distributed generators can contribute into the bottom-up restoration strategy. The interaction between the restoration of two interconnected systems should be taken into account. In this paper, a hybrid model of transmission and distribution systems restoration (HTDSR) is proposed by exchanging data of power and voltage between two separate optimization problems. The effectiveness of the HTDSR algorithm is demonstrated through case studies of the integrated IEEE 13-bus distribution network and IEEE 39-bus transmission grid. Simulation results demonstrate that the integrated restoration strategy with optimal scheduling of distributed generation sources can expedite the restoration process.

Distributed generation↗

Coordination of Wind Farm and Pumped-Storage Hydro for a Self-Healing Power Grid

The increasing penetration of wind energy poses great challenges to the operation of power systems in normal and emergency states. However, energy storage technologies can help accommodate wind power uncertainty and variability due to their flexible characteristics. This paper focuses on the restoration phase, and provides a novel coordination strategy of wind and pumped-storage hydro (PSH) units for a faster and reliable self-healing process. The wind-PSH assisted power system restoration is formulated as a two-stage adaptive robust optimization problem. The first-stage problem determines the start-up sequence of generators and the energization times of transmission paths; and the second-stage problem decides load pickup sequences, wind power dispatch levels, and PSH units' operating modes. The column-and-constraint generation decomposition algorithm is applied to solve the two-stage adaptive robust optimization problem, which has a mixed-integer optimization in the inner-level problem. The developed coordination strategy is tested on the modified IEEE 39-bus system. Numerical results demonstrate that the coordinated wind and PSH units can increase the total energy served, enhance wind power dispatchability, and reduce wind power curtailment.

17 WIND ENERGY↗

Incorporating Wind Energy in Power System Restoration Planning

Wind energy is rapidly growing. While wind brings us clean and inexpensive energy, its inherent variability and uncertainty present challenges for the power grid. In particular, employing wind energy for power system restoration is very challenging. A fast and reliable restoration plays a vital role to achieve the self-healing power grid. This paper develops a novel offline restoration planning tool for harnessing wind energy to enhance grid resilience. The Wind-for-Restoration problem is formulated as a stochastic mixed-integer linear programming problem with generated wind energy scenarios. The problem is then decomposed into two stages and solved with the integer Lshaped algorithm. Numerical experiments have been conducted through different case studies using the modified IEEE 57-bus system. The developed tool can provide the scheduled wind power at each restoration time. The impact of wind energy is investigated from the aspects of location and inertia capability, as well as wind penetration, fluctuation, and uncertainty. Moreover, a dynamic response validation tool is developed to validate the results of optimization problem in a dynamic simulation software. Finally, simulation results demonstrate that the optimal wind harnessing strategy can help improve system restoration process and enhance system resilience.

17 WIND ENERGY↗

Two-Stage Adaptive Restoration Decision Support System for a Self-Healing Power Grid

Power outages cost American industries and businesses billions of dollars and jeopardize the lives of hospital patients. The losses can be greatly reduced with a fast, reliable, and flexible self-healing tool. This paper is aimed to tackle the challenging task of developing an adaptive restoration decision support system (RDSS). The proposed RDSS determines restoration actions both in planning and real-time phases and adapts to constantly changing system conditions. The comprehensive formulation encompasses practical constraints including ac power flow, dynamic reserve, and load modeling. Here, the combinatorial problem is decomposed into a two-stage formulation solved by an integer L-shaped algorithm. The two stages are then executed online in the RDSS framework employing a sliding window method. The IEEE 39-bus system has been studied under normal and contingency conditions to demonstrate the effectiveness and efficiency of the proposed online RDSS.

24 POWER TRANSMISSION AND DISTRIBUTION↗