scholarly journals Stochastic Optimization for Network-Constrained Power System Scheduling Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
D. F. Teshome ◽  
P. F. Correia ◽  
K. L. Lian
Keyword(s):  
Power System ◽  
Load Shedding ◽  
Mixed Integer ◽  
Piecewise Linear Approximation ◽  
Computational Time ◽  
Forecast Errors ◽  
Scheduling Problem ◽  
Generation System ◽  
Network Constraints ◽  
The Impact

The stochastic nature of demand and wind generation has a considerable effect on solving the scheduling problem of a modern power system. Network constraints such as power flow equations and transmission capacities also need to be considered for a comprehensive approach to model renewable energy integration and analyze generation system flexibility. Firstly, this paper accounts for the stochastic inputs in such a way that the uncertainties are modeled as normally distributed forecast errors. The forecast errors are then superimposed on the outputs of load and wind forecasting tools. Secondly, it efficiently models the network constraints and tests an iterative algorithm and a piecewise linear approximation for representing transmission losses in mixed integer linear programming (MILP). It also integrates load shedding according to priority factors set by the system operator. Moreover, the different interactions among stochastic programming, network constraints, and prioritized load shedding are thoroughly investigated in the paper. The stochastic model is tested on a power system adopted from Jeju Island, South Korea. Results demonstrate the impact of wind speed variability and network constraints on the flexibility of the generation system. Further analysis shows the effect of loss modeling approaches on total cost, accuracy, computational time, and memory requirement.

scholarly journals A Bilevel Attacker-Defender Model for Enhancing Power Systems Resilience with Distributed Generation

2020 ◽  
Vol 25 (4) ◽  
pp. 540-547
Author(s):  
Jesús María López Lezama ◽  
Bonie Johana Restrepo Cuestas ◽  
Juan Pablo Hernández Valencia
Keyword(s):  
Power Systems ◽  
Power System ◽  
Distributed Generation ◽  
Distribution Systems ◽  
Programming Model ◽  
Hybrid Genetic Algorithm ◽  
Load Shedding ◽  
Mixed Integer ◽  
System Operator ◽  
The Impact

Electric transmission and distribution systems are subject not only to natural occurring outages but also to intentional attacks. These lasts performed by malicious agents that aim at maximizing the load shedding of the system. Intentional attacks are counteracted by the reaction of the system operator which deploys strategies to minimize the damage caused by such attacks. This paper presents a bilevel modeling approach for enhancing resilience of power systems with high participation of distributed generation (DG). The model describes the interaction of a disruptive agent that aims at maximizing damage to a power system and the system operator that resorts to different strategies to minimize system damage. The proposed mixed integer nonlinear programming model is solved with a hybrid genetic algorithm. Results are presented on a benchmark power system showing the optimal responses of the system operator for a set of deliberate attacks. It was observed that the higher the participation of DG the lower the impact of the attacks was. The presence of DG also influenced the optimal strategies of the attacker which in some cases deviated from optimal attack plans to suboptimal solutions. This allows concluding that the presence of DG benefits the power system in terms of less expected load shedding under intentional attacks.     

scholarly journals Impact of the Generation System Parameters on the Frequency Response of the Power System: A UK Grid Case Study

Electricity ◽  
2021 ◽  
Vol 2 (2) ◽  
pp. 143-157
Author(s):  
Jovi Atkinson ◽  
Ibrahim M. Albayati
Keyword(s):  
Power System ◽  
Frequency Response ◽  
Power Grid ◽  
Sudden Increase ◽  
Generation System ◽  
System Parameters ◽  
Primary Frequency ◽  
Primary Frequency Response ◽  
The Impact ◽  
System Inertia

The operation and the development of power system networks introduce new types of stability problems. The effect of the power generation and consumption on the frequency of the power system can be described as a demand/generation imbalance resulting from a sudden increase/decrease in the demand and/or generation. This paper investigates the impact of a loss of generation on the transient behaviour of the power grid frequency. A simplified power system model is proposed to examine the impact of change of the main generation system parameters (system inertia, governor droop setting, load damping constant, and the high-pressure steam turbine power fraction), on the primary frequency response in responding to the disturbance of a 1.32 GW generation loss on the UK power grid. Various rates of primary frequency responses are simulated via adjusting system parameters of the synchronous generators to enable the controlled generators providing a fast-reliable primary frequency response within 10 s after a loss of generation. It is concluded that a generation system inertia and a governor droop setting are the most dominant parameters that effect the system frequency response after a loss of generation. Therefore, for different levels of generation loss, the recovery rate will be dependent on the changes of the governor droop setting values. The proposed model offers a fundamental basis for a further investigation to be carried on how a power system will react during a secondary frequency response.

scholarly journals Optimal Reactive Power Scheduling Using Cuckoo Search Algorithm

2017 ◽  
Vol 7 (5) ◽  
pp. 2349 ◽  
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Optimization Techniques ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Scheduling Problem ◽  
Power Scheduling

<p>This paper solves an optimal reactive power scheduling problem in the deregulated power system using the evolutionary based Cuckoo Search Algorithm (CSA). Reactive power scheduling is a very important problem in the power system operation, which is a nonlinear and mixed integer programming problem. It optimizes a specific objective function while satisfying all the equality and inequality constraints. In this paper, CSA is used to determine the optimal settings of control variables such as generator voltages, transformer tap positions and the amount of reactive compensation required to optimize the certain objective functions. The CSA algorithm has been developed from the inspiration that the obligate brood parasitism of some Cuckoo species lay their eggs in nests of other host birds which are of other species. The performance of CSA for solving the proposed optimal reactive power scheduling problem is examined on standard Ward Hale 6 bus, IEEE 30 bus, 57 bus, 118 bus and 300 bus test systems. The simulation results show that the proposed approach is more suitable, effective and efficient compared to other optimization techniques presented in the literature.</p>

scholarly journals Peak load minimization of an e-bus depot: impacts of user-set conditions in optimization algorithms

2021 ◽  
Vol 4 (S3) ◽  
Author(s):  
Enrico Toniato ◽  
Prakhar Mehta ◽  
Stevan Marinkovic ◽  
Verena Tiefenbeck
Keyword(s):  
Optimization Algorithm ◽  
Peak Load ◽  
Mixed Integer ◽  
Computational Time ◽  
Transport Sector ◽  
Fleet Management ◽  
Peak Reduction ◽  
Management Options ◽  
Power Load ◽  
The Impact

AbstractThe transport sector is responsible for 25% of global CO2 emissions. To reduce emissions in the EU, a shift from the currently 745,000 operating public buses to electric buses (EBs) is expected in the coming years. Large-scale deployments of EBs and the electrification of bus depots will have a considerable impact on the local electric grid, potentially creating network congestion problems and spikes in the local energy load. In this work, we implement an exact, offline, modular multi-variable mixed-integer linear optimization algorithm to minimize the daily power load profile peak and optimally plan an electric bus depot. The algorithm accepts a bus depot schedule as input, and depending on the user input on optimization conditions, accounts for varying time granularity, preemption of the charging phase, vehicle-to-grid (V2G) charging capabilities and varying fleet size. The primary objective of this work is the analysis of the impact of each of these input conditions on the resulting minimized peak load. The results show that our optimization algorithm can reduce peak load by 83% on average. Time granularity and V2G have the greatest impact on peak reduction, whereas preemption and fleet splitting have the greatest impact on the computational time but an insignificant impact on peak reduction. The results bear relevance for mobility planners to account for innovative fleet management options. Depot infrastructure costs can be minimized by optimally sizing the infrastructure needs, by relying on split-fleet management or V2G options.

scholarly journals Load shedding scheme based metaheuristic technique for power system controlled islanding

2021 ◽  
Vol 23 (3) ◽  
pp. 1306
Author(s):  
N. Z. Saharuddin ◽  
I. Zainal Abidin ◽  
H. Mokhlis ◽  
E. F. Shair
Keyword(s):  
Power System ◽  
Evolutionary Programming ◽  
Exhaustive Search ◽  
Load Shedding ◽  
Computational Time ◽  
Power Balance ◽  
Optimal Amount ◽  
Search Techniques ◽  
Controlled Islanding ◽  
Mitigation Techniques

<p>Power system-controlled islanding is one of the mitigation techniques taken to prevent blackouts during severe outage. The implementation of controlled islanding will lead to the formation of few islands, that can operate as a stand-alone island. However, some of these islands may not be balanced in terms of generation and load after the islanding execution. Therefore, a good load shedding scheme is required to meet the power balance criterion so that it can operate as a balanced stand-alone island. Thus, this paper developed a load shedding scheme-based metaheuristics technique namely modified discrete evolutionary programming (MDEP) technique to determine the optimal amount of load to be shed in order to produce balanced stand-alone islands. The developed load shedding scheme is evaluated and validated with two other load shedding techniques which are conventional EP and exhaustive search techniques. The IEEE 30-bus and 39-bus test systems were utilized for this purpose. The results proves that the load shedding based MDEP technique produces the optimal amount of loads to be shed with shortest computational time as compared with the conventional EP and exhaustive search techniques.</p>

scholarly journals Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs

2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Wenming Cheng ◽  
Peng Guo ◽  
Zeqiang Zhang ◽  
Ming Zeng ◽  
Jian Liang
Keyword(s):  
Variable Neighborhood Search ◽  
Parallel Machines ◽  
Programming Model ◽  
Search Algorithm ◽  
Optimal Schedule ◽  
Deteriorating Jobs ◽  
Mixed Integer ◽  
Computational Time ◽  
Neighborhood Search ◽  
Scheduling Problem

In many real scheduling environments, a job processed later needs longer time than the same job when it starts earlier. This phenomenon is known as scheduling with deteriorating jobs to many industrial applications. In this paper, we study a scheduling problem of minimizing the total completion time on identical parallel machines where the processing time of a job is a step function of its starting time and a deteriorating date that is individual to all jobs. Firstly, a mixed integer programming model is presented for the problem. And then, a modified weight-combination search algorithm and a variable neighborhood search are employed to yield optimal or near-optimal schedule. To evaluate the performance of the proposed algorithms, computational experiments are performed on randomly generated test instances. Finally, computational results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time even for large-sized problems.

General lot-sizing and scheduling for perishable food products

2020 ◽  
Vol 54 (3) ◽  
pp. 913-931 ◽  
Author(s):  
Zohreh Alipour ◽  
Fariborz Jolai ◽  
Ehsan Monabbati ◽  
Nima Zaerpour
Keyword(s):  
Lot Sizing ◽  
Food Products ◽  
Production Costs ◽  
Mixed Integer ◽  
Computational Time ◽  
Scheduling Problem ◽  
Solution Quality ◽  
Perishable Product ◽  
Tactical Decision ◽  
Lot Sizing And Scheduling

General lot-sizing and scheduling is a well-studied problem in the literature, but for perishable or time-sensitive products is less investigated. Also, most of studies on perishable product supply chains focus on strategic and tactical decision levels rather than operational decision level and integrated operational and tactical decision levels. We focus on a general lot-sizing and scheduling problem faced by perishable food products. The lifespan and shelf life are two important key features of perishable products that are considered in the problem. This problem can be described as a multi-product, multi-parallel line, multi-period general lot-sizing and scheduling problem with sequence dependent change over time. The objective function is sum of production costs, inventory holding costs, waste costs, and lifespan related cost function. We apply two mixed-integer programming based heuristics to solve generated instances. The heuristics are compared in terms of solution quality and computational time. Also, the sensitivity analysis is presented to analyze the effects of parameters’ changes.

scholarly journals Evaluating the Economic Benefits of a Smart-Community Microgrid with Centralized Electrical Storage and Photovoltaic Systems

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1764 ◽  
Author(s):  
Jura Arkhangelski ◽  
Pierluigi Siano ◽  
Abdou-Tankari Mahamadou ◽  
Gilles Lefebvre
Keyword(s):  
Distribution System ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Short Term Memory ◽  
Storage System ◽  
Economic Benefits ◽  
Mixed Integer ◽  
Forecast Errors ◽  
Smart Community ◽  
The Impact

In this paper, an innovative method for managing a smart-community microgrid (SCM) with a centralized electrical storage system (CESS) is proposed. The method consists of day-ahead optimal power flow (DA–OPF) for day-ahead SCM managing and its subsequent evaluation, considering forecast uncertainties. The DA–OPF is based on a data forecast system that uses a deep learning (DL) long short-term memory (LSTM) network. The OPF problem is formulated as a mathematical mixed-integer nonlinear programming (MINLP) model. Following this, the developed DA–OPF strategy was evaluated under possible operations, using a Monte Carlo simulation (MCS). The MCS allowed us to obtain potential deviations of forecasted data during possible day-ahead operations and to evaluate the impact of the data forecast errors on the SCM, and that of unit limitation and the emergence of critical situations. Simulation results on a real existing rural conventional community endowed with a centralized community renewable generation (CCRG) and CESS, confirmed the effectiveness of the proposed operation method. The economic analysis showed significant benefits and an electricity price reduction for the considered community if compared to a conventional distribution system, as well as the easy applicability of the proposed method due to the CESS and the developed operating systems.

The Study on a Simplified Model of Photovoltaic Power System

2013 ◽  
Vol 860-863 ◽  
pp. 13-17
Author(s):  
Xin Shu ◽  
Shi Ping Zhou ◽  
Yong Jun Xia ◽  
Gang Hu ◽  
Yang Lei
Keyword(s):  
Power Generation ◽  
Power System ◽  
Flow Model ◽  
Simplified Model ◽  
Generation System ◽  
Photovoltaic Power ◽  
Power Generation System ◽  
Pv Generation ◽  
The Impact ◽  
Pv Power Generation

As the proportion of photovoltaic power increasing, the impact on the power system is evident. An accurate mathematical model for PV power generation system is necessary. This paper demonstrates the detailed mathematic models for PV power generation system consisted of PV cell, converters, flow model are summarized. This work might provide a generic PV power system models for the research of characteristics of PV generation system and its grid-connected operation.

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