Determination of economic dispatch of wind farm-battery energy storage system using Genetic Algorithm

Abstract

SUMMARY This paper considers the incorporation of battery energy storage systems (BESS) into wind farms, for the purpose of achieving economic dispatch for the wind power generators in a manner similar to conventional power plants. A BESS operation optimization model (BOOM) is introduced, and through utilizing unit commitment results, BOOM maximizes a predetermined objective that measures economic benefits obtained from the wind power dispatchability against the BESS cost. Due to the requirements of the formulated problem, a revised genetic algorithm (GA) is developed to solve the combinational‐optimization problem, in which the 0–1 variables represent BESS charge–discharge states and continuous variables pertain to BESS power. With the incorporation of the BESS, the resulting wind power stations attain bidirectional regulation capability as the stations can not only export but also absorb energy. Simulation study demonstrates the performance of the proposed design and the efficacy of the developed algorithm. Copyright © 2012 John Wiley & Sons, Ltd.

Optimal reserve provision regulation for wind farms equipped with energy storage systems

“…Energy storage systems can help wind farms follow the regulated power and almost eliminate the influence of prediction errors . The basic principle to offset errors is to put ESS in a suitable condition with enough capacity to adjust its output.…”

Mathematical modeling and control of DFIG-based wind energy system by using optimized linear quadratic regulator weight matrices

“…From Figure D, it is observed that the number of input variables of GA is the summation of the number of elements of Q and R matrices. In GA process, all the input variables of the GA are encoded into one chromosome (bit stream) . This arrangement is composed of a set of twelve elements, where the first eight are corresponding to the Q matrix, and the remaining four are related to the R matrix.…”

“…The elementary steps of the GA that are used in this work to reach the best response to satisfy the minimum target function are as follows: The objective function of the system is represented by binary coding. Population size ( n p = 20), crossover probability ( P c = 0.8), and mutation probability ( P mu = 0.05) are chosen.…”

“…Although other techniques such as pole placement technique and utilizing asymptotic modal properties are used by many researchers in determining the weight matrices, they face similar difficulties and do not guarantee the expected performance. To overcome these difficulties, genetic algorithm (GA) approach was also used for designing the Q and R matrices in various systems, such as multimachine power system, inverted pendulum system, and low‐voltage ride‐through capability of the DFIG‐based wind turbine system.…”

A Wind Power Plant with Thermal Energy Storage for Improving the Utilization of Wind Energy

“…It is found that the energy storage technology can play a prominent role in facilitating high penetration of wind energy [9]. Integrating the intermittent energy sources like wind energy with an energy storage system can achieve the economic dispatch for the power generator in a manner similar to conventional power plants [10]. Using an energy storage system would help the grid connection during the periods that grid is facing high peak demand and shifting the grid load from peak and busy time to a less demand time.…”