Optimal Battery Sizing in Microgrids Using Probabilistic Unit Commitment

Abstract

The Stochastic nature of wind power can cause insufficiency of supply in electrical systems. Applying an energy storage system can alleviate the impact of wind power forecast error on power systems performance and increase system tolerance against deficiency of supply. This paper attempts to investigate a new unit commitment (UC) problem based on the cost-benefit analysis and here-and-now (HN) approach for optimal sizing of battery banks (BBs) imicrogrids (MGs) with wind power systems. To solve this problem, particle swarm optimization is used to minimize the total cost and maximize the total benefit. In this paper, 12 scenarios have been considered in the presence of BBs and without them in 2 operating modes: 1) stand-alone mode and 2) grid-connected mode. Using the HN approach, the uncertainty of wind power is applied as a constraint in these operating modes. The mathematical formulations related to the HN approach in MGs and its combination in a UC problem are presented in detail for optimal sizing of BBs. Simulation results show that the best sizes of BBs and the scheduling of distributed generations would be entirely different when the accessibility of wind power is taken into consideration by applying HN approach to the proposed probabilistic UC problem

State-Of-The-Art in Microgrid-Integrated Distributed Energy Storage Sizing

“…The work in [15] studies DES sizing considering the stochastic nature of wind generation. A Here-and-Now approach is implemented to model the variability of wind generation by including new constraints to the microgrid unit commitment formulation.…”

“…Note that if a charging/discharging cycle is not completed (i.e., ξ eb = 0), the value of φ ebt must be 1 which forces the depth of discharge value in Equation (13) to be 0. The binary variable z ebmt is used to indicate the actual depth of discharge segment (m) which will be used in Equation (15) to estimate the DES lifetime degradation. The DES degradation parameter α is calculated for each depth of discharge segment m using Equation (2).…”

Optimal Real-Time Operation Strategy for Microgrid: An ADP-Based Stochastic Nonlinear Optimization Approach

“…1) Algorithm Validity Simulation: DP and PSO are commonly used methods to solve NP hard problem. To illustrate the validity of the ADP-EMA algorithm, the optimization result of ADP-EMA is compared with PSO algorithm [43], myopic policy, and DP method. The parameter setting of the PSO is as follow.…”

Scheduling Model for Renewable Energy Sources Integration in an Insular Power System

“…In [27], a cost-based UC was proposed, and an optimization approach to the design of ESS based on batteries of a microgrid with wind power potential, with the uncertainty of this type of energy being considered as a constraint. In order to minimize the total cost and maximize the benefit, the PSO algorithm was used, considering scenarios with and without ESS, and with or without connections to the main network.…”