scholarly journals Multi-objective coordinated dispatch of high wind-penetrated power systems against transient instability

2020 ◽  
Vol 14 (19) ◽  
pp. 4079-4088 ◽  
Author(s):  
Xuekuan Xie ◽  
Yan Xu ◽  
Zhao Yang Dong ◽  
Yuchen Zhang ◽  
Junwei Liu
Keyword(s):  
Power Systems ◽  
High Wind ◽  
Multi Objective ◽  
Transient Instability

Robust Dispatch of High Wind Power-Penetrated Power Systems Against Transient Instability

2018 ◽  
Vol 33 (1) ◽  
pp. 174-186 ◽  
Author(s):  
Yan Xu ◽  
Minghui Yin ◽  
Zhao Yang Dong ◽  
Rui Zhang ◽  
David J. Hill ◽  
...  
Keyword(s):  
Power Systems ◽  
Wind Power ◽  
High Wind ◽  
Transient Instability

scholarly journals Eco-Emission Analysis of Multi-Carrier Microgrid Integrated with Compressed Air and Power-to-Gas Energy Storage Technologies

2021 ◽  
Vol 13 (9) ◽  
pp. 4681
Author(s):  
Khashayar Hamedi ◽  
Shahrbanoo Sadeghi ◽  
Saeed Esfandi ◽  
Mahdi Azimian ◽  
Hessam Golmohamadi
Keyword(s):  
Energy Storage ◽  
Power Systems ◽  
High Efficiency ◽  
Objective Assessment ◽  
Energy Systems ◽  
Vital Role ◽  
Compressed Air ◽  
Emission Analysis ◽  
Multi Objective ◽  
Power To Gas

Growing concerns about global greenhouse gas emissions have led power systems to utilize clean and highly efficient resources. In the meantime, renewable energy plays a vital role in energy prospects worldwide. However, the random nature of these resources has increased the demand for energy storage systems. On the other hand, due to the higher efficiency of multi-energy systems compared to single-energy systems, the development of such systems, which are based on different types of energy carriers, will be more attractive for the utilities. Thus, this paper represents a multi-objective assessment for the operation of a multi-carrier microgrid (MCMG) in the presence of high-efficiency technologies comprising compressed air energy storage (CAES) and power-to-gas (P2G) systems. The objective of the model is to minimize the operation cost and environmental pollution. CAES has a simple-cycle mode operation besides the charging and discharging modes to provide more flexibility in the system. Furthermore, the demand response program is employed in the model to mitigate the peaks. The proposed system participates in both electricity and gas markets to supply the energy requirements. The weighted sum approach and fuzzy-based decision-making are employed to compromise the optimum solutions for conflicting objective functions. The multi-objective model is examined on a sample system, and the results for different cases are discussed. The results show that coupling CAES and P2G systems mitigate the wind power curtailment and minimize the cost and pollution up to 14.2% and 9.6%, respectively.

scholarly journals Multi-Objective Electrical Power System Design Optimization Using a Modified Bat Algorithm

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3956
Author(s):  
Khaled Guerraiche ◽  
Latifa Dekhici ◽  
Eric Chatelet ◽  
Abdelkader Zeblah
Keyword(s):  
Power Systems ◽  
Electrical Power ◽  
Bat Algorithm ◽  
Moment Generating Function ◽  
Electrical Power System ◽  
System Availability ◽  
Reliability Indices ◽  
Multi Objective ◽  
Investment Cost ◽  
Modified Bat Algorithm

The design of energy systems is very important in order to reduce operating costs and guarantee the reliability of a system. This paper proposes a new algorithm to solve the design problem of optimal multi-objective redundancy of series-parallel power systems. The chosen algorithm is based on the hybridization of two metaheuristics, which are the bat algorithm (BA) and the generalized evolutionary walk algorithm (GEWA), also called BAG (bat algorithm with generalized flight). The approach is combined with the Ushakov method, the universal moment generating function (UMGF), to evaluate the reliability of the multi-state series-parallel system. The multi-objective design aims to minimize the design cost, and to maximize the reliability and the performance of the electric power generation system from solar and gas generators by taking into account the reliability indices. Power subsystem devices are labeled according to their reliabilities, costs and performances. Reliability hangs on an operational system, and implies likewise satisfying customer demand, so it depends on the amassed batch curve. Two different design allocation problems, commonly found in power systems planning, are solved to show the performance of the algorithm. The first is a bi-objective formulation that corresponds to the minimization of system investment cost and maximization of system availability. In the second, the multi-objective formulation seeks to maximize system availability, minimize system investment cost, and maximize the capacity of the system.

scholarly journals Multi-Objective Optimization of Autonomous Microgrids with Reliability Consideration

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4466
Author(s):  
Maël Riou ◽  
Florian Dupriez-Robin ◽  
Dominique Grondin ◽  
Christophe Le Loup ◽  
Michel Benne ◽  
...  
Keyword(s):  
Power Systems ◽  
Rural Areas ◽  
Energy System ◽  
Design Stage ◽  
Multi Objective Optimization ◽  
Renewable Energy Resources ◽  
Nsga Ii ◽  
Renewable Integration ◽  
Multi Objective ◽  
Trade Offs

Microgrids operating on renewable energy resources have potential for powering rural areas located far from existing grid infrastructures. These small power systems typically host a hybrid energy system of diverse architecture and size. An effective integration of renewable energies resources requires careful design. Sizing methodologies often lack the consideration for reliability and this aspect is limited to power adequacy. There exists an inherent trade-off between renewable integration, cost, and reliability. To bridge this gap, a sizing methodology has been developed to perform multi-objective optimization, considering the three design objectives mentioned above. This method is based on the non-dominated sorting genetic algorithm (NSGA-II) that returns the set of optimal solutions under all objectives. This method aims to identify the trade-offs between renewable integration, reliability, and cost allowing to choose the adequate architecture and sizing accordingly. As a case study, we consider an autonomous microgrid, currently being installed in a rural area in Mali. The results show that increasing system reliability can be done at the least cost if carried out in the initial design stage.

Multi-Objective Hydro-Thermal Scheduling Problem Using Two Novel Optimization Techniques

2021 ◽  
Vol 12 (3) ◽  
pp. 1-36
Author(s):  
Provas Kumar Roy ◽  
Moumita Pradhan ◽  
Tandra Pal
Keyword(s):  
Power Systems ◽  
Test System ◽  
Optimization Techniques ◽  
Computational Time ◽  
Environmental Aspects ◽  
Grey Wolf Optimization ◽  
Multi Objective ◽  
Efficiency And Effectiveness ◽  
Loading Effects ◽  
Solution Accuracy

This article describes an efficient and reliable strategy for the scheduling of nonlinear multi-objective hydrothermal power systems using the grey wolf optimization (GWO) technique. Moreover, the theory of oppositional-based learning (OBL) is integrated with original GWO for further enhancing its convergence rate and solution accuracy. The constraints related to hydro and thermal plants and environmental aspects are also considered in this paper. To show its efficiency and effectiveness, the proposed GWO and OGWO algorithms are authenticated for the test system consisting of a multi-chain cascade of 4 hydro and 3 thermal units whose valve-point loading effects are also taken into account. Furthermore, statistical outcomes of the conventional heuristic approaches available in the literature are compared with the proposed GWO and OGWO approaches, and these methods give moderately better operational fuel cost and emission in less computational time.

Multi-objective ant lion optimization algorithm to solve large-scale multi-objective optimal reactive power dispatch problem

2019 ◽  
Vol 38 (1) ◽  
pp. 304-324 ◽  
Author(s):  
Souhil Mouassa ◽  
Tarek Bouktir
Keyword(s):  
Power Systems ◽  
Large Scale ◽  
Reactive Power ◽  
Stability Index ◽  
Active Power ◽  
Power Losses ◽  
Content Type ◽  
Multi Objective ◽  
Ant Lion Optimization ◽  
Active Power Losses

Purpose In the vast majority of published papers, the optimal reactive power dispatch (ORPD) problem is dealt as a single-objective optimization; however, optimization with a single objective is insufficient to achieve better operation performance of power systems. Multi-objective ORPD (MOORPD) aims to minimize simultaneously either the active power losses and voltage stability index, or the active power losses and the voltage deviation. The purpose of this paper is to propose multi-objective ant lion optimization (MOALO) algorithm to solve multi-objective ORPD problem considering large-scale power system in an effort to achieve a good performance with stable and secure operation of electric power systems. Design/methodology/approach A MOALO algorithm is presented and applied to solve the MOORPD problem. Fuzzy set theory was implemented to identify the best compromise solution from the set of the non-dominated solutions. A comparison with enhanced version of multi-objective particle swarm optimization (MOEPSO) algorithm and original (MOPSO) algorithm confirms the solutions. An in-depth analysis on the findings was conducted and the feasibility of solutions were fully verified and discussed. Findings Three test systems – the IEEE 30-bus, IEEE 57-bus and large-scale IEEE 300-bus – were used to examine the efficiency of the proposed algorithm. The findings obtained amply confirmed the superiority of the proposed approach over the multi-objective enhanced PSO and basic version of MOPSO. In addition to that, the algorithm is benefitted from good distributions of the non-dominated solutions and also guarantees the feasibility of solutions. Originality/value The proposed algorithm is applied to solve three versions of ORPD problem, active power losses, voltage deviation and voltage stability index, considering large -scale power system IEEE 300 bus.

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