scholarly journals Two-Stage Optimization Model for Two-Side Daily Reserve Capacity of a Power System Considering Demand Response and Wind Power Consumption

2019 ◽  
Vol 11 (24) ◽  
pp. 7171 ◽  
Author(s):  
Jun Dong ◽  
Anyuan Fu ◽  
Yao Liu ◽  
Shilin Nie ◽  
Peiwen Yang ◽  
...  
Keyword(s):  
Power Consumption ◽  
Wind Power ◽  
Demand Response ◽  
Optimization Model ◽  
Reserve Capacity ◽  
Supply Side ◽  
Compensation Mechanism ◽  
Demand Side ◽  
Clustering Method ◽  
Wind Curtailment

Today, wind power is becoming an important energy source for the future development of electric energy due to its clean and environmentally friendly characteristics. However, due to the uncertainty of incoming wind, the utilization efficiency of wind energy is extremely low, which means the problem of wind curtailment becomes more and more serious. To solve the issue of wind power large-scale consumption, a two-stage stochastic optimization model is established in this paper. Different from other research frameworks, a novel two-side reserve capacity mechanism, which simultaneously takes into account supply side and demand side, is designed to ensure the stable consumption of wind power in the real-time market stage. Specifically, the reserve capacity of thermal power units is considered on the supply side, and the demand response is introduced as the reserve capacity on the demand side. At the same time, the compensation mechanism of reserve capacity is introduced to encourage generation companies (GENCOs) to actively participate in the power balance process of the real-time market. In terms of solution method, compared with the traditional k-means clustering method, this paper uses the K-means classification based on numerical weather prediction (K-means-NWP) scenario clustering method to better describe the fluctuation of wind power output. Finally, an example simulation is conducted to analyze the influence of reserve capacity compensation mechanism and system parameters on wind power consumption results. The results demonstrate that with the introduction of reserve capacity compensation mechanism, the wind curtailment quantity of the power system has a significant reduction. Besides, the income of GENCOs is gradually increasing, which motivates their enthusiasm to provide reserve capacity. Furthermore, the reserve capacity mechanism designed in this paper promotes the consumption of wind power and the sustainable development of renewable energy.

scholarly journals Peaking Compensation Mechanism for Thermal Units and Virtual Peaking Plants Union Promoting Curtailed Wind Power Integration

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3299
Author(s):  
Tianliang Wang ◽  
Xin Jiang ◽  
Yang Jin ◽  
Dawei Song ◽  
Meng Yang ◽  
...  
Keyword(s):  
Wind Power ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Supply Side ◽  
Compensation Mechanism ◽  
Demand Side ◽  
Wind Power Integration ◽  
Compensation Mechanisms ◽  
Relationship Of ◽  
Installed Capacity

As the installed capacity of wind power increases rapidly, how to promote wind power curtailment (WPC) integration has become a concern. The surface and underlying causes of wind power curtailment are insufficient peaking capability of the power system and imperfect peaking compensation mechanisms, respectively. Therefore, this paper proposes a peaking compensation mechanism uniting supply side and demand side to enhance system peaking capability. Firstly, through incentive and fairness analysis, the interest relationship of peaking subjects is researched based on game theory, and the peaking contribution on supply/demand side is quantified by Pearson correlation coefficients. Secondly, based on clustering analysis, the potential of system peaking providers are explored adequately, supply-side thermal units are divided into deep peaking clusters, and demand-side demand response (DR) resources are integrated into virtual peaking plants (VPP). Accordingly, a two-stage wind-thermal-VPP coordination optimization model is built to dispatch peaking providers. Furtherly, a two-layer peaking compensation allocation method considering peaking contribution and peaking enthusiasm is proposed to encourage peaking providers and mitigate “combination explosion”. Simulation results indicate that the proposed mechanism effectively promotes the enthusiasm of union peaking and the integration of WPC.

scholarly journals The Bi-Level Optimization Model Research for Energy-Intensive Load and Energy Storage System Considering Congested Wind Power Consumption

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 51
Author(s):  
Shuyan Zhang ◽  
Kaoshe Zhang ◽  
Gang Zhang ◽  
Tuo Xie ◽  
Jiaxing Wen ◽  
...  
Keyword(s):  
Energy Storage ◽  
Power Consumption ◽  
Wind Power ◽  
Power Output ◽  
Optimization Model ◽  
Storage System ◽  
Energy Storage System ◽  
Model Research ◽  
Important Means ◽  
Upper Level

Due to the uncertainty of wind power output, the congestion of wind power has become prominent. Exactly how to improve the capacity of wind power consumption has become a problem that needs to be studied urgently. In this paper, an energy storage system and energy-extensive load with adjustable characteristics are used as an important means of consuming wind power. Firstly, we analyze the reasons for the congestion according to the characteristics of wind power output, and establish a model of the grid’s ability to integrate wind power based on the concept of a wind power admissible interval. Secondly, we analyze the energy-extensive load regulation characteristics and establish an energy-extensive load dispatch model. Thirdly, on the basis of considering the energy-extensive load and energy storage system adjustment constraints, a bi-level optimization model is established. The upper level determines the configured capacity of the energy storage system with the goal of minimizing the total economic investment of the energy storage system, and the lower level coordinates the dispatching with the goal of maximizing wind power consumption and minimizing system operating costs. Finally, a certain region is taken as an example to verify the validity of the proposed method.

scholarly journals A Stochastic-CVaR Optimization Model for CCHP Micro-Grid Operation with Consideration of Electricity Market, Wind Power Accommodation and Multiple Demand Response Programs

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3983 ◽  
Author(s):  
Wang ◽  
Yang ◽  
Tang ◽  
Sun ◽  
Zhao
Keyword(s):  
Wind Power ◽  
Demand Response ◽  
Electricity Market ◽  
Optimization Model ◽  
Cost Minimization ◽  
Utilization Efficiency ◽  
Operational Cost ◽  
Micro Grid ◽  
Grid Operation ◽  
Demand Response Programs

Combined cooling, heating and power (CCHP) micro-grids have the advantage of high energy efficiency, and can be integrated with renewable energies and demand response programs (DRPs). With the deepening of electricity market (EM) reforms, how to carry out operation optimization under EM circumstances will become a key problem for CCHP micro-grid development. This paper proposed a stochastic-CVaR (conditional value at risk) optimization model for CCHP micro-grid operation with consideration of EM participation, wind power accommodation and multiple DRPs. Specifically, based on the stochastic scenarios for EM clearing prices and wind power outputs uncertainties, the stochastic optimization method was applied to ensure the realization of operational cost minimization and wind power accommodation; the CVaR method was implemented to control the potential risk of operational cost increase. Moreover, by introducing multiple DRPs, the electrical, thermal and cooling loads can be transformed as flexible sources for CCHP micro-grid operation. Simulations were performed to show the following outcomes: (1) by applying the proposed stochastic-CVaR approach and considering multiple DRPs, CCHP micro-grid operation can reach better performance in terms of cost minimization, risk control and wind power accommodation etc.; (2) higher energy utilization efficiency can be achieved by coordinately optimizing EM power biddings; etc.

scholarly journals Operation Optimization of Regional Integrated Energy System Based on Electric Heating Gas Demand Response

2020 ◽  
Vol 218 ◽  
pp. 01002
Author(s):  
Nan Wang ◽  
Jialin Yang ◽  
Xichao Zhou ◽  
Zhen Li ◽  
Yaling Sun ◽  
...  
Keyword(s):  
Power Consumption ◽  
Wind Power ◽  
Demand Response ◽  
Energy Cost ◽  
Energy System ◽  
Multi Objective Optimization ◽  
Total Energy Consumption ◽  
Multi Objective ◽  
Trade Offs ◽  
Integrated Energy System

Taking into account the energy cost, pollution emission, wind power consumption, and other dispatching objectives in the regionally integrated energy system (RIES), the RIES multi-objective optimization model considering the integrated demand response is established. Firstly, the RIES modeling of equipment including electricity-to-gas, energy storage systems, cogeneration units, etc., and the introduction of a comprehensive demand response that specifically considers load reduction, load transfer, and load replacement in the region, aimed at reducing system load peaks and valleys difference. Then, the objective function to minimize the system energy cost, the abandoned wind power, and the pollutant treatment cost was established respectively, and the multi-objective optimization method was adopted—the Pareto front was solved by fuzzy weighted programming traversal weights, and then the decision was made based on evidence Method to find the optimal scheduling strategy. Finally, based on a typical case study, the results show that the proposed multi-objective optimization algorithm can effectively make trade-offs among multiple scheduling objectives, and RIES considering comprehensive demand response has advantages in terms of total energy consumption, environmental friendliness, and wind power consumption.

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