Non-black Start Units Research Articles

Optimal Generation Start-Up Methodology for Power System Restoration Considering Conventional and Non-Conventional Renewable Energy Sources

Power system restoration must be accomplished as soon as possible after a blackout. In this process, available black-start (BS) units are used to provide cranking power to non-black-start (NBS) units so as to maximize the overall power system generation capacity. This procedure is known as the generation start-up problem, which is intrinsically combinatorial with complex non-linear constraints. This paper presents a new mixed integer linear programming (MILP) formulation for the generation start-up problem that integrates non-conventional renewable energy sources (NCRES) and battery energy storage systems (BESS). The main objective consists of determining an initial starting sequence for both BS and NBS units that would maximize the generation capacity of the system while meeting the non-served demand of the network. The nature of the proposed model leads to global optimal solutions, clearly outperforming heuristic and enumerative approaches, since the latter may take higher computational time while the former do not guarantee global optimal solutions. Several tests were carried out on the IEEE 39-bus test system considering BESS as well as wind and solar generation. The results showed the positive impact of NCRES in the restoration processes and evidenced the effectiveness and applicability of the proposed approach. It was found that including NCRES and BESS in the restoration process allows a reduction of 24.4% of the objective function compared to the classical restoration without these technologies.

Restoration duration estimation applying generally distributed transition stochastic Petri nets considering the switching failure of breakers

Once blackouts occur the system operators should re-energise the affected system in the shortest time. To attain this, restoration plans should be developed beforehand. A deliberate restoration plan considers the supply duration of the cranking power to non-black-start units (NBSUs), besides the static and dynamic constraints of the power system. Hence, there should be a method to estimate the restoration duration of NBSUs considering the failure in breakers operating mechanism and the stochastic nature of restoration actions. Accordingly, in this study, generally distributed transition stochastic Petri net is employed to calculate the supply duration of NBSUs, critical loads and the execution time of restoration actions. This is significant because the planners can validate their restoration plans from the NBSUs critical times’ point of view or determine energisation time of critical loads. The proposed method has been applied in three test cases, two of these are used for benchmarking, and the other one is a part of Iran bulk power system, which includes a real black-start test. The results show the effectiveness of the method in estimating the restoration duration.

Optimal generation units start-up sequence during restoration of power system considering network reliability using bi-level optimization

During recent years power systems are operated near the nominal capacity of system equipment with low stability margin. Operation of power systems in this condition is extremelyrisky and power systems lose their stability with any intense failure of system equipment. In bulk power system, it is more critical and may cause a partial or overall blackout. The capability of black start to bring back system to a normal condition in the case of partial or overall shut down is very important in each power system. When a shutdown occurs, power plants with black start capability supply cranking power for non-black start power plants, pick up critical loads and energize required transmission lines. These actions should be done in minimum time interval to maximize system provided energy during the restoration process. Most important decision making during restoration process is the determination of start-up sequence of generation units. During the restoration process, units with black start capability (BS units) start at the beginning of the process to provide cranking power for non-black start units (NBS units). Hence the determination of NBS units is decision variable in the restoration problem. In this paper, this problem has been described as a bi-level optimization problem which in upper level determines the optimal start-up sequence of NBS units by using a Teaching-Learning Based Optimization algorithm and in lower level determines the optimal transmission path with minimum number of switching and maximum reliability between any two necessary buses using the searching path graph-based algorithm. The proposed approach has been implemented successfully on IEEE 24-bus RTS and IEEE 118-bus test systems.

Fast network restoration by partitioning of parallel black start zones

The restoration of large electrical power systems after a blackout is often a challenging task. A typical restoration process includes the partitioning of the power systems into subsystems and the successive booting of large non-black start (NBS) units by black start (BS) units. A proper partitioning of the starting zone can reduce the restoration time significantly. This paper investigates a novel network partitioning algorithm to improve the restoration time and ratio of generation and load in each subsystem. The proposed algorithm consists of three stages. In the first stage, the number of subsystems is determined by the number of available BS units and their electrical distance. In the second stage, NBS units are assigned to each subsystem in the way that the rebooting time difference among subsystems is minimised. In the third stage, the substations are assigned to one of the subsystems to achieve the optimal ratio of generation and load in each subsystem. With the proposed algorithm, the switching transient and steady-state over-voltages at the receiving end of unload lines are kept within acceptable ranges and the self-excitation phenomenon does not occur in the subsystems. Furthermore, the start-up sequence of NBS units in each subsystem is determined simultaneously. The proposed algorithm is flexible and can be adjusted very easily according to the real status of the power system. The validity and performance of the proposed approach is demonstrated through simulations using a New England 39 Nodes network and a real network from south China.

Blackstart capability planning for power system restoration

Blackstart capability is essential for power system restoration following a blackout. System restoration planners determine the restoration sequences to provide cranking power from blackstart units (BSUs) to non-blackstart units (NBSUs), pick up critical loads, and energize the necessary transmission paths. This paper proposes a new algorithm for optimization of the restoration actions. An optimal search algorithm is proposed to determine the plan to crank NBSUs through the selected paths of transmission lines. Assuming that the generation capability of a BSU is constant, the method is used to optimize the overall system MWHr generation capabilities from NBSUs. To reduce the computational complexity of system restoration planning, a new generator model is proposed that results in a linear integer programming (IP) formulation. Linearity of the IP problem formulation ensures that the global optimality is achieved. The optimal power flow (OPF) is used to examine the feasibility of planned restoration actions. Test cases from the IEEE 39-bus system, ISO New England system, and Duke-Indiana system are used to validate the proposed algorithm. Numerical simulations demonstrate that the proposed method is computationally efficient for real-world power system cases.

Integration of wind power for optimal power system black-start restoration

Integration of wind farms into power systems may increase the risk of power system blackouts due to the uncertain nature of their output power. In the meantime, wind turbines have relatively short starting time when compared to non-black-start (NBS) generating units. For this reason, wind farms need to participate in power system restoration after blackouts. The decision of restoring a wind farm depends on its output power and the characteristics of the power system. The power system restoration should be accomplished as soon as possible. For complete power system restoration, three stages must be completed: generation restoration, transmission system restoration, and load pick up. To achieve a faster restoration process, an optimal schedule for the black-start units to crank the NBS units is required with optimal transmission path selection. During the restoration process, to maintain the stability of the system and satisfy the system's operational constraints, an optimal load pick up sequence is required. In this paper, the firefly optimization algorithm is used to find the optimal final sequence of NBS unit restoration, the optimal transmission paths, and the optimal load pick up sequence with and without integration of wind farms in the system. The objective is to minimize the overall restoration time and the unserved load, which maximizes the energy capability and improves the sustainability of the system. The proposed algorithm is applied successfully to the IEEE 39-bus system.

Fast Cut Back Thermal Power Plant Load Rejection and Black Start Field Test Analysis

Fast and reliable black start plays a key role in improving the ability of the power system to resist the risk of large-scale blackouts. For a black start with high voltage and long-distance transmission lines, it is much easier to cause phenomena such as self-excitation and power frequency/operating overvoltage, which may lead to black start failure and impact the reliability of the system’s restoration. Meanwhile, the long time needed to crank up the non-black start units will impact the speed of the restoration. This paper addresses the advantages of using a thermal power unit with a fast cut back (FCB) function as a black start unit, and studies the transient process of the FCB unit during the restoration. Firstly, key problems in the power system black start process are analyzed and a practical engineering criterion of self-excitation is proposed. Secondly, the dynamic model of the FCB unit is presented. Thirdly, the field test of the FCB unit load rejection and black start is introduced, which is the first successful field test of black start with 500 kV long-distance lines in China Southern Power Grid (CSG). Finally, the transient process of this test is simulated using the PSCAD/EMTDC software, and the simulation results accord well with the field test results, which verifies the correctness of the FCB model and the self-excitation engineering criterion proposed.

Increasing Black Start Capacity by Fast Cut Back Function of Thermal Power Plants

Power system restoration is well recognized as one of the most important tasks for electric power grids. During the restoration process, preparation is the first stage, in which time is critical, and many non-blackstart units need to be cranked. The black start capacity plays a key role in preparation stage. This paper addresses thermal units with fast cut back (FCB) function as black start units. The model of FCB unit and algorithm for black start capacity assessment accounting for FCB unit is proposed. First, the general restoration process is briefly introduced. Second, the general restoration process is introduced by summarizing the industrial restoration practice. A piece of software entitled as “System Restoration Navigator” (SRN) is developed and used as a computational tool for restoration strategy assessment. Third, the model of FCB units and algorithm for assessment of FCB function in system restoration are proposed. Fourth, case studies show that FCB units increase black start capacity and reduce restoration time considerably. The proposed method has been successfully applied in Guangdong Power Company, China Southern Power Grid (CSG), where hydro power plants are limited and reliability requirement is critical.

Optimal Generator Start-Up Strategy for Bulk Power System Restoration

During system restoration, it is critical to utilize the available black-start (BS) units to provide cranking power to non-black-start (NBS) units in such a way that the overall system generation capability will be maximized. The corresponding optimization problem is combinatorial with complex practical constraints that can vary with time. This paper provides a new formulation of generator start-up sequencing as a mixed integer linear programming (MILP) problem. The linear formulation leads to an optimal solution to this important problem that clearly outperforms heuristic or enumerative techniques in quality of solutions or computational speed. The proposed generator start-up strategy is intended to provide an initial starting sequence of all BS or NBS units. The method can provide updates on the system MW generation capability as the restoration process progresses. The IEEE 39-Bus system, American Electric Power (AEP), and Entergy test cases are used for validation of the generation capability optimization. Simulation results demonstrate that the proposed MILP-based generator start-up sequencing algorithm is highly efficient.