scholarly journals Moth flame optimizer-based solution approach for unit commitment and generation scheduling problem of electric power system

2020 ◽  
Vol 7 (5) ◽  
pp. 668-683
Author(s):  
Ashutosh Bhadoria ◽  
Sanjay Marwaha
Keyword(s):  
Unit Commitment ◽  
Electric Power System ◽  
Mixed Integer ◽  
Unit Commitment Problem ◽  
Spinning Reserve ◽  
Priority List ◽  
Solution Approach ◽  
Generation Scheduling ◽  
Integer Quadratic Programming ◽  
Continuous And Discrete Variables

Abstract This paper proposes a new approach based on the moth flame optimizer algorithm. Moth flame optimizer simulates the natural fervent navigation technique adopted by moths looking for a source of light. The proposed method is further improved by priority list-based ordering; the unit commitment problem (UCP) is a non-linear, non-convex, and combinatorial complex optimization problem. It contains both continuous and discrete variables. This further increases its complexity. Moth flame optimizer is very good at obtaining a commitment pattern: allocation of power on the committed units obtained by mixed-integer quadratic programming method. Heuristic search strategies are used to adopt for the repair of minimum up and downtime, and spinning reserve constraints. MFO effectiveness is tested on the standard UCP reference IEEE model buses 14 and 30, and 10 and 20 units. The efficiency of the projected algorithms is compared to classical PSO, PSOLR, HPSO, PSOSQP, hybrid MPSO, IBPSO, LCA-PSO, NPSO, PSO-GWO, and various other evolutionary algorithms. The comparison result shows that MFO can lead to all methods reported earlier in literature.

scholarly journals A meliorated Harris Hawks optimizer for combinatorial unit commitment problem with photovoltaic applications

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ayani Nandi ◽  
Vikram Kumar Kamboj
Keyword(s):  
Power Generation ◽  
Power System ◽  
Electric Power ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Electric Power System ◽  
Unit Commitment Problem ◽  
Spinning Reserve ◽  
Commitment Problem ◽  
Sine Cosine Algorithm

AbstractConventional unit commitment problem (UCP) consists of thermal generating units and its participation schedule, which is a stimulating and significant responsibility of assigning produced electricity among the committed generating units matter to frequent limitations over a scheduled period view to achieve the least price of power generation. However, modern power system consists of various integrated power generating units including nuclear, thermal, hydro, solar and wind. The scheduling of these generating units in optimal condition is a tedious task and involves lot of uncertainty constraints due to time carrying weather conditions. This difficulties come to be too difficult by growing the scope of electrical power sector day by day, so that UCP has connection with problem in the field of optimization, it has both continuous and binary variables which is the furthermost exciting problem that needs to be solved. In the proposed research, a newly created optimizer, i.e., Harris Hawks optimizer (HHO), has been hybridized with sine–cosine algorithm (SCA) using memetic algorithm approach and named as meliorated Harris Hawks optimizer and it is applied to solve the photovoltaic constrained UCP of electric power system. In this research paper, sine–cosine Algorithm is used for provision of power generation (generating units which contribute in electric power generation for upload) and economic load dispatch (ELD) is completed by Harris Hawks optimizer. The feasibility and efficacy of operation of the hybrid algorithm are verified for small, medium power systems and large system considering renewable energy sources in summer and winter, and the percentage of cost saving for power generation is found. The results for 4 generating units, 5 generating units, 6 generating units, 7 generating units, 10 generating units, 19 generating units, 20 generating units, 40 generating units and 60 generating units are evaluated. The 10 generating units are evaluated with 5% and 10% spinning reserve. The efficacy of the offered optimizer has been verified for several standard benchmark problem including unit commitment problem, and it has been observed that the suggested optimizer is too effective to solve continuous, discrete and nonlinear optimization problems.

Research on Applied Technology with a Continues Method for Unit Commitment Problem

2014 ◽  
Vol 952 ◽  
pp. 319-322
Author(s):  
Lin Feng Yang ◽  
Jie Li ◽  
Zhi Hui Ge
Keyword(s):  
Interior Point ◽  
Interior Point Method ◽  
Unit Commitment ◽  
Mixed Integer ◽  
Unit Commitment Problem ◽  
Integer Quadratic Programming ◽  
Applied Technology ◽  
Commitment Problem ◽  
Mixed Integer Quadratic Programming ◽  
Integer Constraints

A continue method based on relaxation is applied to solve the unit commitment problem (UCP). At first, the primal UCP is reformulated as a simple mixed integer quadratic programming (MIQP), and then the MIQP is solved by interior point method (IPM) and commercial software CPLEX. The first continues problem, UCP without integer constraints, can be solved by IPM to get the no integer solution. The second continues problem, an equivalent continues problem of UCP, can be solved starting from the solution obtained in first problem.

scholarly journals GWO-SA: A Novel Hybrid Grey Wolf Optimizer-Simulated Annealing algorithm for Multidisciplinary Design Optimization Problems

2019 ◽  
Vol 8 (4) ◽  
pp. 1279-1299 ◽  
Keyword(s):  
Simulated Annealing ◽  
Simulated Annealing Algorithm ◽  
Unit Commitment ◽  
Electric Power System ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Unit Commitment Problem ◽  
Spinning Reserve ◽  
Commitment Problem ◽  
Annealing Algorithm

The improved variants of Grey wolf optimizer has good exploration capability for global optimum solution. However, the exploitation competence of the existing variants of grey wolf optimizer is very poor. Researchers are continuously trying to improve the exploitation phase of the existing grey wolf optimizer, but still the improved variants of grey wolf optimizer are lacking in local search capability. In the proposed research, the exploitation phase of the existing grey wolf optimizer has been further improved using simulated annealing algorithm and the proposed hybrid optimizer has been named as hGWO-SA algorithm. The effectiveness of the proposed hybrid variant has been tested for various benchmark problems including multi-disciplinary optimization and design engineering problems and unit commitment problem of electric power system and it has been experimentally found that the proposed optimizer performs much better than existing variants of grey wolf optimizer. The feasibility of hGWO-SA algorithm has been tested for small & medium scale power systems unit commitment problem. In which, the results for 4 unit, 5 unit, 6 unit, 7 unit, 10 units, 19 unit, 20 unit, 40 unit and 60 units are evaluated. The 10-generating units are evaluated with 5% and 10% spinning reserve. The results obviously show that the suggested method gives the superior type of solutions as compared to other algorithms.

scholarly journals Outer Approximation Method for the Unit Commitment Problem with Wind Curtailment and Pollutant Emission

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2686
Author(s):  
Xiali Pang ◽  
Haiyan Zheng ◽  
Liying Huang ◽  
Yumei Liang
Keyword(s):  
Approximation Method ◽  
Unit Commitment ◽  
Outer Approximation ◽  
Mixed Integer ◽  
Pollutant Emission ◽  
Master Problem ◽  
Unit Commitment Problem ◽  
Outer Approximation Method ◽  
Integer Quadratic Programming ◽  
Wind Curtailment

This paper considers the fast and effective solving method for the unit commitment (UC) problem with wind curtailment and pollutant emission in power systems. Firstly, a suitable mixed-integer quadratic programming (MIQP) model of the corresponding UC problem is presented by some linearization techniques, which is difficult to solve directly. Then, the MIQP model is solved by the outer approximation method (OAM), which decomposes the MIQP into a mixed-integer linear programming (MILP) master problem and a nonlinear programming (NLP) subproblem for alternate iterative solving. Finally, simulation results for six systems with up to 100 thermal units and one wind unit in 24 periods are presented, which show the practicality of MIQP model and the effectiveness of OAM.

scholarly journals Practical Robust Optimization Method for Unit Commitment of a System with Integrated Wind Resource

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yuanchao Yang
Keyword(s):  
Power System ◽  
Large Scale ◽  
Unit Commitment ◽  
Optimization Method ◽  
Northwest China ◽  
Mixed Integer ◽  
Problem Solution ◽  
Unit Commitment Problem ◽  
Solution Approach ◽  
Commitment Problem

Unit commitment, one of the significant tasks in power system operations, faces new challenges as the system uncertainty increases dramatically due to the integration of time-varying resources, such as wind. To address these challenges, we propose the formulation and solution of a generalized unit commitment problem for a system with integrated wind resources. Given the prespecified interval information acquired from real central wind forecasting system for uncertainty representation of nodal wind injections with their correlation information, the proposed unit commitment problem solution is computationally tractable and robust against all uncertain wind power injection realizations. We provide a solution approach to tackle this problem with complex mathematical basics and illustrate the capabilities of the proposed mixed integer solution approach on the large-scale power system of the Northwest China Grid. The numerical results demonstrate that the approach is realistic and not overly conservative in terms of the resulting dispatch cost outcomes.

scholarly journals Profit-Based Unit Commitment for a GENCO Equipped with Compressed Air Energy Storage and Concentrating Solar Power Units

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 576
Author(s):  
Mostafa Nasouri Gilvaei ◽  
Mahmood Hosseini Imani ◽  
Mojtaba Jabbari Ghadi ◽  
Li Li ◽  
Anahita Golrang
Keyword(s):  
Energy Storage ◽  
Solar Power ◽  
Unit Commitment ◽  
Thermal Power ◽  
System Structure ◽  
Compressed Air ◽  
Mixed Integer ◽  
Compressed Air Energy Storage ◽  
Concentrating Solar Power ◽  
Unit Commitment Problem

With the advent of restructuring in the power industry, the conventional unit commitment problem in power systems, involving the minimization of operation costs in a traditional vertically integrated system structure, has been transformed to the profit-based unit commitment (PBUC) approach, whereby generation companies (GENCOs) perform scheduling of the available production units with the aim of profit maximization. Generally, a GENCO solves the PBUC problem for participation in the day-ahead market (DAM) through determining the commitment and scheduling of fossil-fuel-based units to maximize their own profit according to a set of forecasted price and load data. This study presents a methodology to achieve optimal offering curves for a price-taker GENCO owning compressed air energy storage (CAES) and concentrating solar power (CSP) units, in addition to conventional thermal power plants. Various technical and physical constraints regarding the generation units are considered in the provided model. The proposed framework is mathematically described as a mixed-integer linear programming (MILP) problem, which is solved by using commercial software packages. Meanwhile, several cases are analyzed to evaluate the impacts of CAES and CSP units on the optimal solution of the PBUC problem. The achieved results demonstrate that incorporating the CAES and CSP units into the self-scheduling problem faced by the GENCO would increase its profitability in the DAM to a great extent.

Modeling and Solution Techniques Used for Hydro Generation Scheduling

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1392 ◽  
Author(s):  
Iram Parvez ◽  
JianJian Shen ◽  
Mehran Khan ◽  
Chuntian Cheng
Keyword(s):  
Genetic Algorithm ◽  
Dynamic Programming ◽  
Stochastic Programming ◽  
Short Interval ◽  
Optimization Techniques ◽  
Mixed Integer ◽  
Fuzzy Logics ◽  
Spinning Reserve ◽  
Lagrange Relaxation ◽  
Generation Scheduling

The hydro generation scheduling problem has a unit commitment sub-problem which deals with start-up/shut-down costs related hydropower units. Hydro power is the only renewable energy source for many countries, so there is a need to find better methods which give optimal hydro scheduling. In this paper, the different optimization techniques like lagrange relaxation, augmented lagrange relaxation, mixed integer programming methods, heuristic methods like genetic algorithm, fuzzy logics, nonlinear approach, stochastic programming and dynamic programming techniques are discussed. The lagrange relaxation approach deals with constraints of pumped storage hydro plants and gives efficient results. Dynamic programming handles simple constraints and it is easily adaptable but its major drawback is curse of dimensionality. However, the mixed integer nonlinear programming, mixed integer linear programming, sequential lagrange and non-linear approach deals with network constraints and head sensitive cascaded hydropower plants. The stochastic programming, fuzzy logics and simulated annealing is helpful in satisfying the ramping rate, spinning reserve and power balance constraints. Genetic algorithm has the ability to obtain the results in a short interval. Fuzzy logic never needs a mathematical formulation but it is very complex. Future work is also suggested.

scholarly journals Flexibility Reserve of Self-Consumption Optimized Energy Systems in the Household Sector

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3017
Author(s):  
Elias Dörre ◽  
Sebastian Pfaffel ◽  
Alexander Dreher ◽  
Pedro Girón ◽  
Svenja Heising ◽  
...  
Keyword(s):  
Unit Commitment ◽  
Programming Model ◽  
Weighted Average ◽  
Heat Pumps ◽  
Mixed Integer ◽  
Single Family ◽  
Unit Commitment Problem ◽  
Household Sector ◽  
The Future ◽  
The Individual

Energy generation and consumption in the power grid must be balanced at every single moment. Within the synchronous area of continental Europe, flexible generators and loads can provide Frequency Containment Reserve and Frequency Restoration Reserve marketed through the balancing markets. The Transmission System Operators use these flexibilities to maintain or restore the grid frequency when there are deviations. This paper shows the future flexibility potential of Germany’s household sector, in particular for single-family and twin homes in 2025 and 2030 with the assumption that households primarily optimize their self-consumption. The primary focus is directed to the flexibility potential of Electric Vehicles, Heat Pumps, Photovoltaics and Battery Storage Systems. A total of 10 different household system configurations were considered and combined in a weighted average based on the scenario framework of the German Grid Development Plan. The household generation, consumption and storage units were simulated in a mixed-integer linear programming model to create the time series for the self-consumption optimized households. This solved the unit commitment problem for each of the decentralized households in their individual configurations. Finally, the individual household flexibilities were evaluated and then aggregated to a Germany-wide flexibility profile for single-family and twin homes. The results indicate that the household sector can contribute significantly to system stabilization with an average potential of 30 negative and 3 positive flexibility in 2025. In 2030, the corresponding flexibilities potentially increase to 90 and 30 , respectively. This underlines that considerable flexibility reserves could be provided by single-family and twin homes in the future.

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