An Optimization Model for Large–Scale Wind Power Grid Connection Considering Demand Response and Energy Storage Systems

Abstract

Abstract:To reduce the influence of wind power output uncertainty on power system stability, demand response (DRPs) and energy storage systems (ESSs) are introduced while solving scheduling optimization problems. To simulate wind power scenarios, this paper uses Latin Hypercube Sampling (LHS) to generate the initial scenario set and constructs a scenario reduction strategy based on Kantorovich distance. Since DRPs and ESSs can influence the distribution of demand load, this paper constructs a joint scheduling optimization model for wind power, ESSs and DRPs under the objective of minimizing total coal cost, and constraints of power demand and supply balance, users' demand elasticity, thermal units' startup-shutdown, thermal units' output power climbing and wind power backup service. To analyze the influences of ESSs and DRPs on system wind power consumption capacity, example simulation is made in a 10 thermal units system with a 1000 MW wind farm and 400 MW energy storage systems under four simulation scenarios. The simulation results show that the introduction of DRPs and ESSs could promote system wind power consumption capacity with significantly economic and environment benefits, OPEN ACCESSEnergies 2014, 7 7283 which include less coal consumption and less pollutant emission; and the optimization effect reaches the optimum when DRPs and ESSs are both introduced.

Multi-Objective Scheduling Optimization Based on a Modified Non-Dominated Sorting Genetic Algorithm-II in Voltage Source Converter−Multi-Terminal High Voltage DC Grid-Connected Offshore Wind Farms with Battery Energy Storage Systems

“…Compared to other technologies, the battery energy storage system (BESS) is the most cost-effective option coupled with power-electronic devices for an optimal operation of power systems. In recent times, various studies have been conducted on integrated systems for optimal operation [16][17][18]. A control strategy including a hierarchical scheme has been developed for a multi-terminal HVDC network [16].…”

“…A control strategy including a hierarchical scheme has been developed for a multi-terminal HVDC network [16]. In [17], the demand response and ESS have been introduced to reduce the influence of wind power output uncertainty on the power system stability using the real-time outputs of thermal units and wind turbines and real-time charging/discharging behavior of energy storage. In [18], the authors presented a new coordination control scheme between an offshore WF and a hydrogen management system for reducing the adverse impacts of wind variability.…”

Optimal Scheduling of Energy Storage System for Self-Sustainable Base Station Operation Considering Battery Wear-Out Cost

“…DR can be used with ESS to minimize the losses payments in distribution networks under the condition that electricity price has uncertainty [9]. The authors in [10] implemented a scheduling optimization with DR to reduce the influence of wind power uncertainty in power systems. In [11], the authors addressed an optimization algorithm for a combined wind power generation and ESS enabling to peak shift based on forward dynamic programming (DP).…”

Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation

“…In fact, as DR, DG, and storage units, for example, can influence the demand, adequate scheduling of these resources is needed. The work in [6] proposes a joint scheduling optimization model for storage, DR, and DG (focusing on wind generation) minimizing total costs.…”