Day-Ahead Scheduling Model of the Distributed Small Hydro-Wind-Energy Storage Power System Based on Two-Stage Stochastic Robust Optimization

With renewable energy sources (RESs) highly penetrating into the power system, new problems emerge for the independent system operator (ISO) to maintain and keep the power system safe and reliable in the day-ahead dispatching process under the fluctuation caused by renewable energy. In this paper, considering the small hydropower with no reservoir, different from the other hydro optimization research and wind power uncertain circumstances, a day-ahead scheduling model is proposed for a distributed power grid system which contains several distributed generators, such as small hydropower and wind power, and energy storage systems. To solve this model, a two-stage stochastic robust optimization approach is presented to smooth out hydro power and wind power output fluctuation with the aim of minimizing the total expected system operation cost under multiple cluster water inflow scenarios, and the worst case of wind power output uncertainty. More specifically, before dispatching and clearing, it is necessary to cluster the historical inflow scenarios of small hydropower into several typical scenarios via the Fuzzy C-means (FCM) clustering method, and then the clustering comprehensive quality (CCQ) method is also presented to evaluate whether these scenarios are representative, which has previously been ignored by cluster research. It can be found through numerical examples that FCM-CCQ can explain the classification more reasonably than the common clustering method. Then we optimize the two stage scheduling, which contain the pre-clearing stage and the rescheduling stage under each typical inflow scenario after clustering, and then calculate the final operating cost under the worst wind power output scenario. To conduct the proposed model, the day-ahead scheduling procedure on the Institute of Electrical and Electronics Engineers (IEEE) 30-bus test system is simulated with real hydropower and wind power data. Compared with traditional deterministic optimization, the results of two-stage stochastic robust optimization structured in this paper, increases the total cost of the system, but enhances the conservative scheduling strategy, improves the stability and reliability of the power system, and reduces the risk of decision-making simultaneously.

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Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage

Complexity ◽

10.1155/2018/2517987 ◽

2018 ◽

Vol 2018 ◽

pp. 1-13 ◽

Cited By ~ 5

Author(s):

Tingli Cheng ◽

Minyou Chen ◽

Yingxiang Wang ◽

Bo Li ◽

Muhammad Arshad Shehzad Hassan ◽

...

Keyword(s):

Renewable Energy ◽

Energy Storage ◽

Multiobjective Optimization ◽

Power System ◽

Wind Power ◽

Optimization Method ◽

Optimal Dispatch ◽

Comparison Results ◽

Multiobjective Particle Swarm Optimization ◽

Teaching Learning

In association with the development of intermittent renewable energy generation (REG), dynamic multiobjective dispatch faces more challenges for power system operation due to significant REG uncertainty. To tackle the problems, a day-ahead, optimal dispatch problem incorporating energy storage (ES) is formulated and solved based on a robust multiobjective optimization method. In the proposed model, dynamic multistage ES and generator dispatch patterns are optimized to reduce the cost and emissions. Specifically, strong constraints of the charging/discharging behaviors of the ES in the space-time domain are considered to prolong its lifetime. Additionally, an adaptive robust model based on minimax multiobjective optimization is formulated to find optimal dispatch solutions adapted to uncertain REG changes. Moreover, an effective optimization algorithm, namely, the hybrid multiobjective Particle Swarm Optimization and Teaching Learning Based Optimization (PSO-TLBO), is employed to seek an optimal Pareto front of the proposed dispatch model. This approach has been tested on power system integrated with wind power and ES. Numerical results reveal that the robust multiobjective dispatch model successfully meets the demands of obtaining solutions when wind power uncertainty is considered. Meanwhile, the comparison results demonstrate the competitive performance of the PSO-TLBO method in solving the proposed dispatch problems.

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A Study on Wind - Energy Storage Hybrid System

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.187.97 ◽

2011 ◽

Vol 187 ◽

pp. 97-102 ◽

Cited By ~ 1

Author(s):

Liang Liang ◽

Jian Lin Li ◽

Dong Hui

Keyword(s):

Renewable Energy ◽

Energy Storage ◽

Power System ◽

Wind Energy ◽

Wind Power ◽

Large Scale ◽

Renewable Energy Sources ◽

Storage System ◽

Energy Storage System ◽

Wind Power System

Recently, more and more people realize the importance of environment protection. Electric power generation systems using renewable energy sources have an advantage of no greenhouse effect gas emission. Among all the choices, wind power can offer an economic and environmentally friendly alternative to conventional methods of power supply. As a result, wind energy generation, utilization and its grid penetration in electrical grid is increasing world wide. The wind generated power is always fluctuating due to its time varying nature and causing stability problem. Inserting energy storage system into large scale wind farm to eliminate the fluctuation becomes a solution for developing large scale renewable energy system connected with grid. The topology diagram and control strategy are presented in this paper. According to the simulation result, it could be indicated that embedding energy storage system into wind power system could improve the access friendly and extend system functions. This paper shows that integrating energy storage system into wind power system will build a more reliable and flexible system for power grid.

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Impact of compressed air energy storage system into diesel power plant with wind power penetration

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v9i3.pp1553-1560 ◽

2019 ◽

Vol 9 (3) ◽

pp. 1553

Author(s):

Abdulla Ahmed ◽

Tong Jiang

Keyword(s):

Renewable Energy ◽

Energy Storage ◽

Power Plant ◽

Power System ◽

Wind Power ◽

Power Supply ◽

Renewable Energy Sources ◽

Compressed Air ◽

Energy Sources ◽

Compressed Air Energy Storage

<p>The wind energy plays an important role in power system because of its renewable, clean and free energy. However, the penetration of wind power (WP) into the power grid system (PGS) requires an efficient energy storage systems (ESS). compressed air energy storage (CAES) system is one of the most ESS technologies which can alleviate the intermittent nature of the renewable energy sources (RES). Nyala city power plant in Sudan has been chosen as a case study because the power supply by the existing power plant is expensive due to high costs for fuel transport and the reliability of power supply is low due to uncertain fuel provision. This paper presents a formulation of security-constrained unit commitment (SCUC) of diesel power plant (DPP) with the integration of CAES and PW. The optimization problem is modeled and coded in MATLAB which solved with solver GORUBI 8.0. The results show that the proposed model is suitable for integration of renewable energy sources (RES) into PGS with ESS and helpful in power system operation management.</p>

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Evaluation of Wind Energy Accommodation Based on Two-Stage Robust Optimization

Elektronika ir Elektrotechnika ◽

10.5755/j01.eie.26.3.25756 ◽

2020 ◽

Vol 26 (3) ◽

pp. 61-68

Author(s):

Kunpeng Tian ◽

Weiqing Sun ◽

Dong Han ◽

Ce Yang

Keyword(s):

Renewable Energy ◽

Power System ◽

Wind Energy ◽

Robust Optimization ◽

Optimization Problem ◽

Mixed Integer ◽

Master Problem ◽

Two Stage ◽

Energy Accommodation ◽

Robust Optimization Problem

Large-scale renewable energy integration brings unprecedented challenges to electric power system planning and operation. The paper aims at economic dispatch and the safe operation of high penetration renewable energy power systems. According to the principle of power system dispatchability, the assessment of wind energy accommodation is formulated into a two-stage robust optimization problem with a min-max-min structure. Based on the benders algorithm, the intractable robust optimization problem is transformed into the form of sub-problem and master problem. Strong duality theory and big-M method are used to recast the sub problem into a mixed integer linear programming. The envelope of wind energy accommodation can be obtained by using commercial software to solve the master problem and sub problem alternately. For the realization of arbitrary wind power within the envelope, the amount of wind energy leakage and load shedding in power system operation are acceptable. An example of modified IEEE 39-bus test systems is used to verify the effectiveness and practicability of the evaluation method.

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A Multi-Objective Risk Scheduling Model of an Electrical Power System-Containing Wind Power Station with Wind and Energy Storage Integration

Energies ◽

10.3390/en12112153 ◽

2019 ◽

Vol 12 (11) ◽

pp. 2153

Author(s):

Hai He ◽

Feixiang Peng ◽

Zhengnan Gao ◽

Xin Liu ◽

Shubo HU ◽

...

Keyword(s):

Energy Storage ◽

Power System ◽

Wind Power ◽

Power Station ◽

Multi Objective ◽

Power Stations ◽

Wind Power Station ◽

Scheduling Model ◽

Wind Power System ◽

Power System Scheduling

The integrated operation of wind storage is a developmental trend for future wind power stations. Compared with energy storage and wind power system scheduling, the utilization ratio of wind power is improved. This paper analyzes the power system scheduling risks that are brought about by wind power stations with wind and energy storage integration and puts forward the corresponding risks indexes, which are based on the physical structure and the long-operation features of the battery energy storage system. This paper also proposes the multi-objective optimization scheduling model, considering the economy of optimization, risk of load-shedding, and wind power curtailment that is caused by the full failure and partial failure of energy storage and wind turbines, and the uncertainty of the wind power output. Example results have shown that the optimization scheduling model can apply to various control strategies and different risk levels of the system, and reduce the risk of an electric power system containing a wind power station with wind and energy storage integration. In the meantime, it can also improve the economical efficiency and utilization rate of the wind power system.

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A Robust Scheduling Optimization Model for an Integrated Energy System with P2G Based on Improved CVaR

Energies ◽

10.3390/en11123437 ◽

2018 ◽

Vol 11 (12) ◽

pp. 3437 ◽

Cited By ~ 7

Author(s):

Zhongfu Tan ◽

Qingkun Tan ◽

Shenbo Yang ◽

Liwei Ju ◽

Gejirifu De

Keyword(s):

Power System ◽

Wind Power ◽

Power Output ◽

Optimization Model ◽

Operating Cost ◽

Energy System ◽

Conditional Value At Risk ◽

Scheduling Optimization ◽

Scheduling Model ◽

Integrated Energy System

The uncertainty of wind power and photoelectric power output will cause fluctuations in system frequency and power quality. To ensure the stable operation of the power system, a comprehensive scheduling optimization model for the electricity-to-gas integrated energy system is proposed. Power-to-gas (P2G) technology enhances the flexibility of the integrated energy system and the power system in absorbing renewable energy. In this context, firstly, an electricity-to-gas optimization scheduling model is proposed, and the improved Conditional Value at Risk (CVaR) is proposed to deal with the uncertainty of wind power and photoelectric power output. Secondly, taking the integrated energy system with the P2G operating cost and the carbon emission cost as the objective function, an optimal scheduling model of the multi-energy system is solved by the A Mathematical Programming Language (AMPL) solver. Finally, the results of the example illustrate the optimal multi-energy system scheduling model and analyze the economic benefits of the P2G technology to improve the system to absorb wind power and photovoltaic power. The simulation calculation of the proposed model demonstrates the necessity of taking into account the operating cost of the electrical gas conversion in the integrated energy system, and the feasibility of considering the economic and wind power acceptance capabilities.

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A Two-Stage Robust Optimization Method Based on the Expected Scenario for Islanded Microgrid Energy Management

Discrete Dynamics in Nature and Society ◽

10.1155/2021/7079296 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Qing Duan ◽

Wanxing Sheng ◽

Haoqing Wang ◽

Caihong Zhao ◽

Chunyan Ma

Keyword(s):

Renewable Energy ◽

Robust Optimization ◽

Energy Management ◽

Power Output ◽

Renewable Energy Sources ◽

Energy Sources ◽

Two Stage ◽

Worst Case ◽

Proposed Model ◽

Islanded Microgrid

One of the main challenges in microgrid system energy management is dealing with uncertainties such as the power output from renewable energy sources. The classic two-stage robust optimization (C-TSRO) method was proposed to cope with these uncertainties. However, this method is oriented to the worst-case scenario and is therefore somewhat conservative. In this study, focusing on the energy management of a typical islanded microgrid and considering uncertainties such as the power output of renewable energy sources and the power demand of loads, an expected-scenario-oriented two-stage robust optimization (E-TSRO) method is proposed to alleviate the conservative tendency of the C-TSRO method because the E-TSRO method chooses to optimize the system cost according to the expected scenario instead, while ensuring the feasibility of the first-stage variables for all possible scenarios, including the worst case. According to the structural characteristics of the proposed model based on the E-TSRO method, a column-and-constraint generation (C & CG) algorithm is utilized to solve the proposed model. Finally, the effectiveness of the E-TSRO model and the solution algorithm are analysed and validated through a series of experiments, thus obtaining some important conclusions, i.e., the economic efficiency of system operation can be improved at about 6.7% in comparison with the C-TSRO results.

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A Coordinated Control of Offshore Wind Power and BESS to Provide Power System Flexibility

Energies ◽

10.3390/en14154650 ◽

2021 ◽

Vol 14 (15) ◽

pp. 4650

Author(s):

Martha N. Acosta ◽

Francisco Gonzalez-Longatt ◽

Juan Manuel Roldan-Fernandez ◽

Manuel Burgos-Payan

Keyword(s):

Energy Storage ◽

Power System ◽

Wind Power ◽

Single Layer ◽

Coordinated Control ◽

Test System ◽

Power Converter ◽

Control Logic ◽

Battery Energy Storage ◽

Battery Energy

The massive integration of variable renewable energy (VRE) in modern power systems is imposing several challenges; one of them is the increased need for balancing services. Coping with the high variability of the future generation mix with incredible high shares of VER, the power system requires developing and enabling sources of flexibility. This paper proposes and demonstrates a single layer control system for coordinating the steady-state operation of battery energy storage system (BESS) and wind power plants via multi-terminal high voltage direct current (HVDC). The proposed coordinated controller is a single layer controller on the top of the power converter-based technologies. Specifically, the coordinated controller uses the capabilities of the distributed battery energy storage systems (BESS) to store electricity when a logic function is fulfilled. The proposed approach has been implemented considering a control logic based on the power flow in the DC undersea cables and coordinated to charging distributed-BESS assets. The implemented coordinated controller has been tested using numerical simulations in a modified version of the classical IEEE 14-bus test system, including tree-HVDC converter stations. A 24-h (1-min resolution) quasi-dynamic simulation was used to demonstrate the suitability of the proposed coordinated control. The controller demonstrated the capacity of fulfilling the defined control logic. Finally, the instantaneous flexibility power was calculated, demonstrating the suitability of the proposed coordinated controller to provide flexibility and decreased requirements for balancing power.

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