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.

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 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 Optimal operation of a hybrid-energy microgrid with energy storage system

2019 ◽  
Vol 138 ◽  
pp. 01003 ◽  
Author(s):  
Mohamed Elgamal ◽  
Nikolay V. Korovkin ◽  
Ahmed Refaat ◽  
Akram Elmitwally
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Storage System ◽  
Bat Algorithm ◽  
Energy Storage System ◽  
Optimal Operation ◽  
Rule Base ◽  
Hybrid Energy ◽  
Management Scheme ◽  
Management Optimization

In this paper, a day-ahead profit-maximizing energy management scheme for a grid-tied microgrid operation is proposed. The microgrid contains various types of distributed energy resources (DERs) and an inverter-interfaced battery-bank storage system. The average of day-ahead hourly forecasted data for loads, wind speed, and solar radiation are inputted into the framework of energy management (EMF). To optimize the microgrid performance, EMF determines the hourly dispatch of reactive and active power for each DER. Also, it specifies the discharging and charging times of the energy storage system and the onload tap changer position setting of the transformer connected to the main grid. The main aim is to maximize the revenue of microgrid meeting all technical limitations. The main grid can sell/buy reactive and active powers to/from the microgrid with a variable daily energy price of the market. A collective rule base-BAT algorithm is implemented as a solver of the energy management optimization problem for a grid-tided microgrid. Furthermore, the ability of the suggested EMF is proved in comparison with recent approaches.

Effect of Design Parameters on the Performance of Thermal Energy Storage Systems

Solar Energy ◽  
2004 ◽  
Author(s):  
Gregor P. Henze
Keyword(s):  
Energy Storage ◽  
Thermal Energy ◽  
Thermal Energy Storage ◽  
Large Scale ◽  
Control Strategies ◽  
Storage System ◽  
Operating Cost ◽  
Energy Storage System ◽  
Design Parameters ◽  
Wide Range

This paper describes simulation-based results of a large-scale investigation of a commercial cooling plant including a thermal energy storage system. A cooling plant with an ice-on-coil system with external melt and a reciprocating compressor operating in a large office building was analyzed under four different control strategies. Optimal control as the strategy that minimizes the total operating cost (demand and energy charges) served as a benchmark to assess the performance of the three conventional controls. However, all control strategies depend on properly selected design parameters. The storage and chiller capacities as the primary design parameters were varied over a wide range and the dependence of the system’s cost saving performance on these parameters was evaluated.

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