Load Restoration Research Articles

A Hierarchical Response-Based Approach to the Load Restoration Problem

Power system resilience is the ability of an electric power grid to withstand, absorb, and rapidly recover from low-probability high-impact disasters. In recent years, several major incidents all around the world have highlighted the need for operative solutions in order to materialize the resilience of the power grid in response to such catastrophic events. With the advent of synchrophasor technology in modern power systems, it has emerged as a promising measure to improve the resilience of power network. At the event of widespread outages, synchrophasor technology could facilitate the restoration procedure, reduce total outage duration, and mitigate damaging impacts to critical loads. This paper proposes a two-stage hierarchical approach to the transmission-level load restoration problem based on synchrophasors. The first stage determines the optimal amount and location of load pickups, and in the second stage, the predetermined decisions are implemented and the network stability is monitored until reaching a viable equilibrium point. The whole problem is decomposed into a set of tractable subproblems in order to improve the computational efficiency. The effectiveness of the proposed approach is further illustrated through a case study based on the IEEE 39-bus system.

Decision-making optimization of power system extended black-start coordinating unit restoration with load restoration

Summary The extended black-start strategy is new exploration for black-start restoration of power systems, in which more than one non–black-start unit can be restored simultaneously during the black-start stage. This paper presents a multiobjective optimization method coordinating unit restarting with load restoration for extended black-start decision making. The objective functions of the black-start restoration optimization are defined as restoring non–black-start units and unserved loads as much as possible under steady-state and transient system operation constraints. A hybrid algorithm combining the lexicographic method with the improved bacterial foraging algorithm is used to solve the defined optimization model. The proposed method has been tested on the IEEE 118-bus system and the southern Hebei power system of China, and the test results verify the effectiveness of the proposed decision-making method.

A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration

Recent severe power outages caused by extreme weather hazards have highlighted the importance and urgency of improving the resilience of electric distribution grids. Microgrids with various types of distributed generators (DGs) have the potential to enhance the electricity supply continuity and thus facilitate resilient distribution grids under natural disasters. In this paper, a novel load restoration optimization model is proposed to coordinate topology reconfiguration and microgrid formation while satisfying a variety of operational constraints. The proposed method exploits benefits of operational flexibility provided by grid modernization to enable more critical load pickup. Specifically, a mixed-integer second order cone programming is employed to reduce the computational complexity of the proposed optimization with optimality guaranteed. Finally, the effectiveness of the proposed method has been verified on an IEEE 33-bus test case and a modified 615-bus test system.

Resilience-Oriented Critical Load Restoration Using Microgrids in Distribution Systems

A resilience-oriented service restoration method using microgrids to restore critical load after natural disasters is proposed in this paper. Considering the scarcity of power generation resources, the concept of continuous operating time (COT) is introduced to determine the availability of microgrids for critical load restoration and to assess the service time. Uncertainties induced by intermittent energy sources and load are also taken into account. The critical load restoration problem is modeled as a chance-constrained stochastic program. A Markov chain-based operation model is designed to describe the stochastic energy variations within microgrids, based on which the COT is assessed. A two-stage heuristic is developed for the critical load restoration problem. First, a strategy table containing the information of all feasible restoration paths is established. Then the critical load restoration strategy is obtained by solving a linear integer program. Numerical simulations are performed on the IEEE 123-node feeder system under several scenarios to demonstrate the effectiveness of the proposed method. The impacts of fault locations, available generation resources, and load priority on the restoration strategy are discussed.

An Evaluation Strategy for Microgrid Reliability Considering the Effects of Protection System

Incorrect responses from protective devices weaken the reliability of microgrids. This paper investigates the effects of the protection system on the reliability performance of a microgrid integrated with weather-dependent microsources. It relies on a stochastic model to simulate the challenges existing in current protection schemes designed for microgrids. Abnormal operating conditions, including overcurrent, overvoltage, and undervoltage, which are detected by a deficient protection scheme, are analyzed by a defined fuzzy virtual setting value. Their contributions, along with the conventional random failure rate achieved by statistical results, are jointly used to evaluate the short-term outage rate of a feeder. A series of fuzzy reliability indices is further proposed for the short-term and periodical reliability of both microgrid system and customers. Subsequently, an evaluation strategy, combined with fuzzy simulation and load restoration, is presented as a solution tool. Simulations on a test system are provided to support the necessity of considering the effects of protection operation in evaluating microgrid reliability.

Power system restoration: a literature review from 2006 to 2016

Power system restoration has attracted more attention and made great progress recently. Research progress of the power system restoration from 2006 to 2016 is reviewed in this paper, including black-start, network reconfiguration and load restoration. Some emerging methods and key techniques are also discussed in the context of the integration of variable renewable energy and development of the smart grid. There is a long way to go to achieve automatic self-healing in bulk power systems because of its extreme complexity. However, rapidly developing artificial intelligence technology will eventually enable the step-by-step dynamic decision-making based on the situation awareness of supervisory control and data acquisition systems (SCADA) and wide area measurement systems (WAMS) in the near future.

Non-Disruptive Load-Side Control for Frequency Regulation in Power Systems

This paper studies frequency regulation of power systems by using both automatic generation control (AGC) and load-side control. A switched distributed controller is designed for each load bus in a transmission network. The targets of the designed controller are twofold. First, it makes controllable loads work together with generators to restore the system frequency quickly after a real power mismatch occurs in the grid. Second, it restores controllable loads to their nominal working conditions. To achieve the first target, a consensus-based distributed load-side controller is designed. Peer-to-peer communication between loads is used to achieve an average consensus according to which controllable load reacts to the frequency deviation. To achieve the second target, the load-side controller shifts its duties to AGC slowly after the frequency goes back into an ideal region, and hence, controllable loads will restore to their nominal conditions gradually. A switching signal is designed to detect time instants when the load-side controller should work in the mode of frequency restoration or in the mode of load restoration.

OPTIMAL OFF POINT DETERMINATION IN ELECTRICAL POWER DISTRIBUTION SYSTEM USING RISK ASSESSMENT

In normal operation of distribution systems, protection systems are important for reliability and efficiency measures. For reliability enhancement of primary loop distribution systems, off points are normally located in midway between substations. Off point in networks allow the continued supply of electric to customer during faults as the feeder is separated into two sections, between two substations. Once a fault is cleared, then the faulted section can be reconfigured to accept supply from the unfaulted section. This is known as load restoration in network distribution system. Currently, off points are allocated using load flows and based on the engineer’s experience. However this method does not optimize the reliability to customers, as it does not take into account the risk allocation to customers. To overcome this, the research proposed a risk-based analysis, which can determine an optimal off point location. The analysis used a real network between PMU Kota Setar and PMU Kota Sarang Semut, Kedah, Malaysia. Actual field data from varying utilities were used for completion of this project. Six scenarios were developed to get a clear view of the total impact of risk with varying locations of off point. It is shown that the method proposed in this project gives a better indication for the optimal determination off point in electrical power distribution systems compared to the commonly used method.

A framework for analyzing cascading failure in large interconnected power systems: A post-contingency evolution simulator

The power system protection against different threats has become a key and growing concern. A materialized threat provokes a sequence of chained events and counteractions in the grid. The simulation and analysis of the cascades leading to blackouts are extremely intricate due to various time scales, multiple interacting automatic and human-driving actions, and the large set of possible countermeasures. The possibility to simulate the cascading events, considering both behaviors of the system and human/automatic actions, is crucial for designing protective strategies, guiding investments and supporting policy decision making on reinforcing the system. In this paper, we present a simulation framework which, with a steady-state approach, provides system snapshots during cascading failures, taking into account the actions for minimizing the load-shedding or maximizing the restoration of the unserved loads. The conceptual framework is implemented as a software tool to simulate system behaviors and actions like automatic countermeasures, human interventions and optimal operational strategies to defend and restore the system. Combined with a suitable economic assessment method, it can be used to evaluate investments in countermeasures and the potential costs of different threats. It has been applied to study the countermeasures to enhance the security of the EU power transmission network.

Coordinating generation and load pickup during load restoration with discrete load increments and reserve constraints

After a major outage happens, the independent system operator, transmission owners (TOs), generation owners (GOs), and distribution owners (DOs) should coordinate control actions to restore the power system timely and reliably. This study proposes a methodology to establish load restoration plans for the coordination among these participants. This methodology models the load restoration as a multi-stage decision-making process. At each stage, a mixed-integer nonlinear load restoration model (MINLR) is formulated to maximise load pickup subject to AC power flow and reserve constraints. Comprehensive load characteristics are considered in this model. The solution of the MINLR model provides power set points for GOs/TOs and load pickup amount for DOs. A complete load restoration plan is obtained by solving a series of MINLR models. To solve MINLR models efficiently, a branch-and-cut solver is constructed by identifying efficient cutting planes and a reliable problem-specific branching method. The applicability of cutting planes is proven. This methodology is tested using a 24-bus system with 170 interrupted load increments, and a 118-bus system with 637 interrupted load increments. The simulation results show that the proposed methodology can be efficiently applied to aid restoration participants pickup load increments within the TO’s islands, while maintaining adequate reserve margins.

Long-Term Impacts of Bacteria-Sediment Interactions in Watershed-Scale Microbial Fate and Transport Modeling.

Elevated levels of fecal indicator bacteria (FIB) remain the leading cause of surface water-quality impairments in the United States. Under the Clean Water Act, basin-specific total maximum daily load (TMDL) restoration plans are responsible for bringing identified water impairments in compliance with applicable standards. Watershed-scale model predictions of FIB concentrations that facilitate the development of TMDLs are associated with considerable uncertainty. An increasingly cited criticism of existing modeling practice is the common strategy that assumes bacteria behave similarly to "free-phase" contaminants, although many field evidence indicates a nontrivial number of cells preferentially associate with particulates. Few attempts have been made to evaluate the impacts of sediment on the predictions of in-stream FIB concentrations at the watershed scale, with limited observational data available for model development, calibration, and validation. This study evaluates the impacts of bacteria-sediment interactions in a continuous, watershed-scale model widely used in TMDL development. In addition to observed FIB concentrations in the water column, streambed sediment-associated FIB concentrations were available for model calibration. While improved model performance was achieved compared with previous studies, model performance under a "sediment-attached" scenario was essentially equivalent to the simpler "free-phase" scenario. Watershed-specific characteristics (e.g., steep slope, high imperviousness) likely contributed to the dominance of wet-weather pollutant loading in the water column, which may have obscured sediment impacts. As adding a module accounting for bacteria-sediment interactions would increase the model complexity considerably, site evaluation preceding modeling efforts is needed to determine whether the additional model complexity and effort associated with partitioning phases of FIB is sufficiently offset by gains in predictive capacity.

A disaster-triggered life-support load restoration framework based on Multi-Agent Consensus System

To guarantee the life-support line unblocked under extreme disasters, a life-support load emergency restoration problem is studied. A life-support load restoration framework is proposed for an efficient restoration, which consists of a hybrid triggering mechanism and a Multi-Agent Consensus System (MACS). The hybrid triggering mechanism is proposed to identify life-support loads rapidly, as a disaster-caused blackout occurs. Meanwhile, communication network bandwidth is saved greatly. The novel MACS is developed as a restoration operator. Multi-agent consensus algorithm, as an Action Consensus Protocol of Agents (ACPA), is firstly applied in power systems restoration. Based on the proposed ACPA, the emergency restoration can be quantized precisely. Simulation results on IEEE-30 bus system are provided to validate the performance of the proposed approach.

Sectionalizing strategies for minimizing outage durations of critical loads in parallel power system restoration with bi-level programming

Fast restoration of critical loads and non-black-start generators can significantly reduce the economic losses caused by power system blackouts. In a parallel power system restoration scenario, the sectionalization of restoration subsystems plays a very important role in determining the pickup of critical loads before synchronization. Most existing research mainly focuses on the startup of non-black-start generators. The restoration of critical loads, especially the loads with cold load characteristics, has not yet been addressed in optimizing the subsystem divisions. As a result, sectionalized restoration subsystems cannot achieve the best coordination between the pickup of loads and the ramping of generators. In order to generate sectionalizing strategies considering the pickup of critical loads in parallel power system restoration scenarios, an optimization model considering power system constraints, the characteristics of the cold load pickup and the features of generator startup is proposed in this paper. A bi-level programming approach is employed to solve the proposed sectionalizing model. In the upper level the optimal sectionalizing problem for the restoration subsystems is addressed, while in the lower level the objective is to minimize the outage durations of critical loads. The proposed sectionalizing model has been validated by the New-England 39-bus system and the IEEE 118-bus system. Further comparisons with some existing methods are carried out as well.

DC Microgrids: Economic Operation and Enhancement of Resilience by Hierarchical Control

The additional deployment of distributed energy resources (DERs) has attracted further attention to dc microgrid applications. The objective of the study is to discuss the possibilities and the merits of adopting a dc control system for enhancing the economics and the resilient operation of a dc microgrid, and to test the proposed hierarchical control strategy that applies to a dc microgrid. This paper provides case studies in which an existing microgrid at the Illinois Institute of Technology (IIT) is operated as a dc microgrid and the results for each case are compared with the ac model. The structure, components, and control strategies of IIT dc microgrids are discussed and the economic operation of a grid-connected dc microgrid through tertiary control, as well as islanding, load restoration, and resynchronization of the dc microgrid are simulated. The dc microgrid simulation results are compared with those of an ac microgrid, which demonstrate that the proposed coordinated dc strategy for the optimal operation of DERs is an effective way of ensuring the resilient response of dc microgrid to emergencies and its economic operation at steady state.

Biomechanics of periimplantitis—winged implant, the ultimate solution for post extraction immediate loading and D5 bone type

The desire for immediate load restoration of dental implants, particularly in the anterior esthetic zone, requires specific implant design strategies to enhance primary stability. In the presence of extraction sites, often with compromised bone, implant fixation is obtained apically and palatally. Surface roughness is a factor in early osseointegration (Alberktsson et al.). However, it is the macro-architectural design of the implant that establishes initial mechanical fixation, which is crucial in minimizing implant mobility in the first 3–4 weeks of function.

A wide area monitoring system based load restoration method

Restoring a large-scale power system has always been a complicated and important issue. A lot of research work has been done on different aspects of the whole power system restoration procedure. However, more time will be required to complete the power system restoration process in an actual situation if accurate and real-time system data cannot be obtained. With the development of the wide area monitoring system (WAMS), power system operators are capable of accessing to more accurate data in the restoration stage after a major outage. The ultimate goal of the system restoration is to restore as much load as possible while in the shortest period of time after a blackout, and the restorable load can be estimated by employing WAMS. Moreover, discrete restorable loads are employed considering the limited number of circuit-breaker operations and the practical topology of distribution systems. In this work, a restorable load estimation method is proposed employing WAMS data after the network frame has been reenergized, and WAMS is also employed to monitor the system parameters in case the newly recovered system becomes unstable again. The proposed method has been validated with the New England 39-Bus system and an actual power system in Guangzhou, China.

Effective Method for Load Restoration

In our country power demand is a major problem so we are going to introduce an algorithm based on genetic algorithm is proposed to solve service restoration problem in power distribution systems with priority customers. In genetic algorithm new solutions are found in every next generation with probability of getting the better solution till the optimal solution is not found. Service restoration problem is formulated as multi objective multi-constraint combinatorial optimization problem. The integer permutation scheme is used to generate the offspring in genetic algorithm. Integer permutation does not allow the hamming cliff problem. In case of partial restoration, including micro grid action that increases the power transfer capacity reduces out-of-service area. The operating time of manual and automatic controlled switches is significantly different. Therefore both type of switches are considered separately. The comprehensive simulation results of proposed method including three phase and load side fault are presented for 5 bus test systems.

Load transfer capability analysis considering interconnection of distributed generation and energy storage system

SUMMARY This paper presents an N-1 restoration model and optimization algorithm for the solution of maximizing load transfer capability with the interconnection of DG and DESS in distribution networks. Through a deep analysis of the time-varying characteristics of DG and DESS, the load restoration model is established and LTC indicator is proposed. With the application of searching area expansion and network topology simplification in consideration of topology connectivity constraint, LTC indicator can be conveniently obtained. Case study results show that the proposed LTC indicator effectively assesses the power supply capability in distribution networks under different circumstances of DG and DESS interconnection. Copyright © 2012 John Wiley & Sons, Ltd.

Optimisation of network reconfiguration based on a two-layer unit-restarting framework for power system restoration

An optimisation method of network reconfiguration is proposed by introducing a two-layer unit-restarting framework for power system restoration. The unit restarting during the network reconfiguration is treated as a two-layer restoration process–network-layer unit restarting and plant-layer unit restarting. Based on the two-layer framework, the optimisation of the network reconfiguration is modelled as a multi-objective optimisation problem, in which the network-layer unit restarting, the plant-layer unit restarting and restoration of the important loads are separately modelled as three optimisation sub-problems with their own models and solving algorithms. The lexicographic optimisation method is then used to solve the multi-objective optimisation problem by integrating the solving processes of the three sub-problems. The proposed optimisation method of network reconfiguration can determine the restarting sequence of all the units and realise the coordinative optimisation of the unit restarting and restoration of the important loads. The effectiveness of the proposed method is validated by the numerical results of a restoration example based on the New England 10-unit 39-bus power system.

Novel Multiagent Based Load Restoration Algorithm for Microgrids

Once a fault in microgrids has been cleared, it is necessary to restore the unfaulted but out-of-service loads as much as possible in a timely manner. This paper proposes a novel fully distributed multiagent based load restoration algorithm. According to the algorithm, each agent makes synchronized load restoration decision according to discovered information. During the information discovery process, agents only communicate with their direct neighbors, and the global information is discovered based on the Average-Consensus Theorem. In this way, total net power, indexes and demands of loads that are ready for restoration can be obtained. Then the load restoration problem can be modeled and solved using existing algorithms for the 0–1 Knapsack problem. To achieve adaptivity and stability, a distributed algorithm for coefficient setting is proposed and compared against existing algorithms and a particle swarm optimization based algorithm. Theoretically, the proposed load restoration algorithm can be applied to systems of any size and structure. Simulation studies with power systems of different scale demonstrate the effectiveness of the proposed algorithm.