Thermal Unit Commitment Problem with Wind Power and Energy Storage System

2013 ◽  
Vol 347-350 ◽  
pp. 1455-1461 ◽  
Author(s):  
Rui Wang ◽  
Yu Guang Xie ◽  
Kai Xie ◽  
Ya Qiao Luo
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Branch And Bound ◽  
Unit Commitment ◽  
Storage System ◽  
Operating Cost ◽  
Peak Load ◽  
Energy Storage System ◽  
Mixed Integer ◽  
Unit Commitment Problem

This paper presents a methodology for solving unit commitment (UC) problem for thermal units integrated with wind power and generalized energy storage system (ESS).The ESS is introduced to achieve peak load shaving and reduce the operating cost. The volatility of wind power is simulated by multiple scenarios, which are generated by Latin hypercube sampling. Meanwhile, the scenario reduction technique based on probability metric is introduced to reduce the number of scenarios so that the computational burden can be alleviated. The thermal UC problem with volatile wind power and ESS is transformed to a deterministic optimization which is formulated as the mixed-integer convex program optimized by branch and bound-interior point method. During the branch and bound process, the best first search and depth first search are combined to expedite the computation. The effectiveness of the proposed algorithm is demonstrated by a ten unit UC problem.

scholarly journals Stochastic Unit Commitment Problem, Incorporating Wind Power and an Energy Storage System

2020 ◽  
Vol 12 (23) ◽  
pp. 10100
Author(s):  
Khalid Alqunun ◽  
Tawfik Guesmi ◽  
Abdullah F. Albaker ◽  
Mansoor T. Alturki
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Unit Commitment ◽  
Mixed Integer ◽  
Master Problem ◽  
Thermal Unit ◽  
Unit Commitment Problem ◽  
Battery Energy Storage ◽  
Commitment Problem ◽  
Battery Energy

This paper presents a modified formulation for the wind-battery-thermal unit commitment problem that combines battery energy storage systems with thermal units to compensate for the power dispatch gap caused by the intermittency of wind power generation. The uncertainty of wind power is described by a chance constraint to escape the probabilistic infeasibility generated by classical approximations of wind power. Furthermore, a mixed-integer linear programming algorithm was applied to solve the unit commitment problem. The uncertainty of wind power was classified as a sub-problem and separately computed from the master problem of the mixed-integer linear programming. The master problem tracked and minimized the overall operation cost of the entire model. To ensure a feasible and efficient solution, the formulation of the wind-battery-thermal unit commitment problem was designed to gather all system operating constraints. The solution to the optimization problem was procured on a personal computer using a general algebraic modeling system. To assess the performance of the proposed model, a simulation study based on the ten-unit power system test was applied. The effects of battery energy storage and wind power were deeply explored and investigated throughout various case studies.

Unit Commitment Considering Wind Power and Electrochemical Energy Storage System

2013 ◽  
Vol 805-806 ◽  
pp. 387-392
Author(s):  
Zhi Cai ◽  
De Yue Men ◽  
Wei Dong ◽  
Sai Dai ◽  
Hui Cui ◽  
...  
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Unit Commitment ◽  
Storage System ◽  
Energy Storage System ◽  
Electrochemical Energy Storage ◽  
Large Capacity ◽  
Variable Nature ◽  
The Impact ◽  
Electrochemical Energy

With the rapid development of wind power, electric grid faces significant challenges from the variable nature and anti-peak-regulation characteristic of wind power. In order to mitigate the impact of wind power, large capacity electrochemical energy storage is proposed to solve this problem. This study establishes a unit commitment (UC) model with large capacity electrochemical energy storage given the specific characteristics. Meanwhile, wind forecast deviation and curtailment are considered. Case studies with modified IEEE 39-bus system are employed to validate the proposed method. The impact of electrochemical energy storage system on economics, peak load shifting and accommodating wind power is analyzed.

Determination of an Optimal Operating Schedule for Thermal Units with an Energy Storage System

2008 ◽  
Vol 9 (3) ◽  
Author(s):  
Tomonobu Senjyu ◽  
Shantanu Chakraborty ◽  
Ahmed Yousuf Saber ◽  
Atsushi Yona ◽  
Toshihisa Funabashi
Keyword(s):  
Energy Storage ◽  
Unit Commitment ◽  
Storage System ◽  
Operating Cost ◽  
Energy Storage System ◽  
Optimal Operation ◽  
Total Production ◽  
Priority List ◽  
Hourly Output

This paper presents a determination methodology for finding optimal operation schedules of thermal units (namely unit commitment) integrated with an energy storage system (ESS) to minimize total operating costs. A generic ESS formulation along with a method for solving unit commitment (UC) of thermal units with ESS is proposed to serve this purpose. The problem of unit commitment with an ESS is solved using the Priority List method. Intelligent Genetic algorithm (GA) is included in the algorithm for generating new and potential solutions. The proposed method consists of two steps. The first step is to determine the schedule of ESS and the schedule of thermal units. The second step is to dispatch the hourly output of thermal units and the ESS which comply a minimized total production cost. The proposed method is applied to a power system with ten thermal units and a large ESS. The presented simulation results show that the schedule of thermal units with an ESS of a particular life cycle, achieved by the proposed method, minimizes the operating cost. The discussion regarding the determination of schedule thermal units (TU) along with the integrated ESS may interest many types of ESS due to their generalized formulations.

scholarly journals Research on Energy Storage Optimization Operation Schedule in an Island System

2021 ◽  
Vol 11 (8) ◽  
pp. 3690
Author(s):  
Yu-Tung Chen ◽  
Cheng-Chien Kuo ◽  
Jia-Zhang Jhan
Keyword(s):  
Unit Commitment ◽  
Storage System ◽  
Operating Cost ◽  
Peak Load ◽  
Mixed Integer ◽  
Reserve Capacity ◽  
Load Case ◽  
Peak Shaving ◽  
Battery System ◽  
Island System

This paper proposes a 24-h ahead unit commitment for a diesel-photovoltaic (PV)-battery system using mixed-integer linear programming (MILP) to minimize the operating cost which includes the power storage system (PSS) in the reserve capacity. Considering the Kinmen island’s winter peak load case of 20MW, and summer peak load case of 60MW, a 24-h schedule for the diesel-PV-battery system island system for these two scenarios was optimized that allows the PSS to perform both as an additional reserve capacity and peak-shaving auxiliary device. The results show that the addition of PSS in the dispatch decision can allow the flexibility of the systems, especially in the reserve allocation, to up to twice the value of the PSS capacity. In this way, the PSS reduces the early startup and late shutdown of high-cost units while maintaining the system reserve, thereby, reducing the operating cost of the system.

Research on Wind Power Integration Capacity of Hydro-Thermal Wind Power System with Energy Storage System

2013 ◽  
Vol 448-453 ◽  
pp. 2309-2315 ◽  
Author(s):  
Feng Li ◽  
Li Zi Zhang ◽  
Yun Yun Wang ◽  
Jun Shu Feng
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Storage System ◽  
Peak Load ◽  
Clean Energy ◽  
Energy Storage System ◽  
Wind Power Integration ◽  
Fast Development ◽  
Load Regulation ◽  
Wind Power System

With the fast development of clean energy in China, the conflict between limited peak load regulation capability and the increasing installed wind power capacity became more and more obvious. Two different wind power integration dispatching modes were proposed in this paper, meanwhile, the wind power integration capacity and system economy under different scenarios, which have different wind power penetration and energy storage system (ESS) capacity, were also analyzed. As indicated in the example analysis, the ESS can significantly enhance the wind power integration capacity; and the economical wind power integration dispatching mode is the most suitable choice for the power grid in wind-rich area.

scholarly journals Implementation of Optimal Two-Stage Scheduling of Energy Storage System Based on Big-Data-Driven Forecasting—An Actual Case Study in a Campus Microgrid

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1124 ◽  
Author(s):  
Byeong-Cheol Jeong ◽  
Dong-Hwan Shin ◽  
Jae-Beom Im ◽  
Jae-Young Park ◽  
Young-Jin Kim
Keyword(s):  
Energy Storage ◽  
Scheduling Algorithm ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Operating Cost ◽  
Optimal Schedule ◽  
Energy Storage System ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Actual Case

Optimal operation scheduling of energy storage systems (ESSs) has been considered as an effective way to cope with uncertainties arising in modern grid operation such as the inherent intermittency of the renewable energy sources (RESs) and load variations. This paper proposes a scheduling algorithm where ESS power inputs are optimally determined to minimize the microgrid (MG) operation cost. The proposed algorithm consists of two stages. In the first stage, hourly schedules during a day are optimized one day in advance with the objective of minimizing the operating cost. In the second stage, the optimal schedule obtained from the first stage is repeatedly updated every 5 min during the day of operation to compensate for the uncertainties in load demand and RES output power. The ESS model is developed considering operating efficiencies and then incorporated in mixed integer linear programming (MILP). Penalty functions are also considered to acquire feasible optimal solutions even under large forecasting errors in RES generation and load variation. The proposed algorithm is verified in a campus MG, implemented using ESSs and photovoltaic (PV) arrays. The field test results are obtained using open-source software and then compared with those acquired using commercial software.

scholarly journals Capacity Optimization Based on Energy Storage to Restrain Severe Fluctuation of Wind Power

2019 ◽  
Vol 11 (1) ◽  
pp. 9-15
Author(s):  
Xiaolin Fu ◽  
Hong Wang ◽  
Zhijie Wang ◽  
Yongxin Li ◽  
Jindu Lv ◽  
...  
Keyword(s):  
Energy Storage ◽  
Wind Power ◽  
Wind Farm ◽  
Storage System ◽  
Operating Cost ◽  
Energy Storage System ◽  
Particle Swarm Algorithm ◽  
Capacity Optimization ◽  
Coordination Problem ◽  
Whole Life Cycle

In order to solve the coordination problem between the economy and the stabilization effect of energy storage system, a capacity optimization model based on energy storage to suppress the violent fluctuation of wind power is proposed, and a multi-objective function with the maximum wind power dissipation capacity and the minimum operating cost of energy storage system is established. Considering the average annual cost and penalty cost of the whole life cycle, an evaluation index with correlation coefficient as the fitting degree is proposed, and the reference power of wind farm grid connection is optimized by particle swarm algorithm. Using the operation data of Qidong Wind Farm in Jiangsu Province, the theoretical validity is verified, the coordination is improved to the greatest extent, and the capacity demand for energy storage system is reduced.

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