scholarly journals IGDT-Based Wind–Storage–EVs Hybrid System Robust Optimization Scheduling Model

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3848
Author(s):  
Bo Sun ◽  
Simin Li ◽  
Jingdong Xie ◽  
Xin Sun
Keyword(s):  
Robust Optimization ◽  
Wind Power ◽  
Hybrid System ◽  
Electricity Market ◽  
Optimization Model ◽  
Probabilistic Approach ◽  
System Optimization ◽  
Stable Operation ◽  
Scheduling Model ◽  
Optimization Scheduling

Wind power has features of uncertainty. When wind power producers (WPPs) bid in the day-ahead electricity market, how to deal with the deviation between forecasting output and actual output is one of the important topics in the design of electricity market with WPPs. This paper makes use of a non-probabilistic approach—Information gap decision theory (IGDT)—to model the uncertainty of wind power, and builds a robust optimization scheduling model for wind–storage–electric vehicles(EVs) hybrid system with EV participations, which can make the scheduling plan meet the requirements within the range of wind power fluctuations. The proposed IGDT robust optimization model first transforms the deterministic hybrid system optimization scheduling model into a robust optimization model that can achieve the minimum recovery requirement within the range of wind power output fluctuation, and comprehensively considers each constraint. The results show that the wind–storage–EVs hybrid system has greater operational profits and less impact on the safe and stable operation of power grids when considering the uncertainty of wind power. In addition, the proposed method can provide corresponding robust wind power fluctuation under different expected profits of the decision-maker to the wind–storage–EVs hybrid system.

scholarly journals Method for Determining the Maximum Allowable Capacity of Wind Farm Based on Box Set Robust Optimization

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Lihui Guo ◽  
Hao Bai
Keyword(s):  
Wind Speed ◽  
Robust Optimization ◽  
Wind Power ◽  
Optimization Model ◽  
Wind Farm ◽  
Optimization Theory ◽  
Wind Farms ◽  
Bilevel Optimization ◽  
Grid Connection ◽  
Node Voltage

With the increasing penetration of wind power, the randomness and volatility of wind power output would have a greater impact on safety and steady operation of power system. In allusion to the uncertainty of wind speed and load demand, this paper applied box set robust optimization theory in determining the maximum allowable installed capacity of wind farm, while constraints of node voltage and line capacity are considered. Optimized duality theory is used to simplify the model and convert uncertainty quantities in constraints into certainty quantities. Under the condition of multi wind farms, a bilevel optimization model to calculate penetration capacity is proposed. The result of IEEE 30-bus system shows that the robust optimization model proposed in the paper is correct and effective and indicates that the fluctuation range of wind speed and load and the importance degree of grid connection point of wind farm and load point have impact on the allowable capacity of wind farm.

Robust Optimization of Steam Power System

2013 ◽  
Vol 860-863 ◽  
pp. 2606-2609
Author(s):  
Ran Ding ◽  
Guo Xiang Li
Keyword(s):  
Power System ◽  
Robust Optimization ◽  
Optimization Model ◽  
System Optimization ◽  
Uncertain Parameters ◽  
Steam Power ◽  
Power System Optimization ◽  
Steam Power System ◽  
System Optimal ◽  
Simulation Results

In steam power system optimal problems, uncertain parameters should be considered unless the solution will be infeasible. The uncertain parameters and constraints in steam power system optimization model are analyzed. Then the related constraints with uncertain parameters which used to be expressed by joint chance constraints are approximated, and a robust optimization model of steam power system is proposed. The simulation results illustrate the validity of the model.

Multi-Object Optimization Research about Wind/Solar Hybrid Generation System

2014 ◽  
Vol 672-674 ◽  
pp. 337-341
Author(s):  
Zhi Huang Liu ◽  
Hai Yuan Liu ◽  
Xue Jun Gao
Keyword(s):  
Test Data ◽  
Hybrid System ◽  
Optimization Model ◽  
Cost Control ◽  
System Optimization ◽  
Optimization Method ◽  
Generation System ◽  
Hybrid Generation ◽  
Pareto Solutions

Wind/solar hybrid system optimization is a key point for cost control. Here a multi-object optimization model is raised. Then a multi-object optimization method based on GA is used to find the Pareto solutions of wind/solar hybrid system. The test data shows that this method can get a good result.

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 Robust Optimization Model for Photovoltaic Power Producer’s Bidding Decision-Making in Electricity Market

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Lifeng Liu ◽  
Huisheng Gao ◽  
Yuwei Wang ◽  
Wei Sun
Keyword(s):  
Decision Making ◽  
Robust Optimization ◽  
Electricity Market ◽  
Optimization Model ◽  
Negative Impact ◽  
Financial Risks ◽  
Worst Case ◽  
High Penetration ◽  
Uncertainty Set ◽  
Power Outputs

With the deepening of electricity market (EM) reform and the high penetration of photovoltaic (PV) energy in power system, the uncertainties of a PV power output and fluctuation of EM prices would bring substantial financial risks for PV power producers (PPPs). This paper proposed a robust optimization model for PPP’s power bidding decision-making. Specifically, the random PV power outputs are modeled by the uncertainty set, which need no probabilistic information and can fully depict the continuous range of uncertainties. Subsequently, with respect to any scenario for day-ahead EM prices, PPP’s optimal power bidding strategy is obtained under the worst-case realization within the uncertainty set, which guarantees the robustness in resisting the negative impact of random PV power outputs on PPP’s profit. Moreover, a reformulation approach was introduced for equivalently transforming our model into a tractable framework. Simulation was implemented to validate the feasibility and effectiveness of applying our proposed model.

scholarly journals Day-Ahead Scheduling Model of the Distributed Small Hydro-Wind-Energy Storage Power System Based on Two-Stage Stochastic Robust Optimization

2019 ◽  
Vol 11 (10) ◽  
pp. 2829 ◽  
Author(s):  
Jun Dong ◽  
Peiwen Yang ◽  
Shilin Nie
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Power System ◽  
Robust Optimization ◽  
Wind Power ◽  
Power Output ◽  
Clustering Method ◽  
Small Hydropower ◽  
Two Stage ◽  
Scheduling Model

With renewable energy sources (RESs) highly penetrating into the power system, new problems emerge for the independent system operator (ISO) to maintain and keep the power system safe and reliable in the day-ahead dispatching process under the fluctuation caused by renewable energy. In this paper, considering the small hydropower with no reservoir, different from the other hydro optimization research and wind power uncertain circumstances, a day-ahead scheduling model is proposed for a distributed power grid system which contains several distributed generators, such as small hydropower and wind power, and energy storage systems. To solve this model, a two-stage stochastic robust optimization approach is presented to smooth out hydro power and wind power output fluctuation with the aim of minimizing the total expected system operation cost under multiple cluster water inflow scenarios, and the worst case of wind power output uncertainty. More specifically, before dispatching and clearing, it is necessary to cluster the historical inflow scenarios of small hydropower into several typical scenarios via the Fuzzy C-means (FCM) clustering method, and then the clustering comprehensive quality (CCQ) method is also presented to evaluate whether these scenarios are representative, which has previously been ignored by cluster research. It can be found through numerical examples that FCM-CCQ can explain the classification more reasonably than the common clustering method. Then we optimize the two stage scheduling, which contain the pre-clearing stage and the rescheduling stage under each typical inflow scenario after clustering, and then calculate the final operating cost under the worst wind power output scenario. To conduct the proposed model, the day-ahead scheduling procedure on the Institute of Electrical and Electronics Engineers (IEEE) 30-bus test system is simulated with real hydropower and wind power data. Compared with traditional deterministic optimization, the results of two-stage stochastic robust optimization structured in this paper, increases the total cost of the system, but enhances the conservative scheduling strategy, improves the stability and reliability of the power system, and reduces the risk of decision-making simultaneously.

scholarly journals A Robust Scheduling Optimization Model for an Integrated Energy System with P2G Based on Improved CVaR

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3437 ◽  
Author(s):  
Zhongfu Tan ◽  
Qingkun Tan ◽  
Shenbo Yang ◽  
Liwei Ju ◽  
Gejirifu De
Keyword(s):  
Power System ◽  
Wind Power ◽  
Power Output ◽  
Optimization Model ◽  
Operating Cost ◽  
Energy System ◽  
Conditional Value At Risk ◽  
Scheduling Optimization ◽  
Scheduling Model ◽  
Integrated Energy System

The uncertainty of wind power and photoelectric power output will cause fluctuations in system frequency and power quality. To ensure the stable operation of the power system, a comprehensive scheduling optimization model for the electricity-to-gas integrated energy system is proposed. Power-to-gas (P2G) technology enhances the flexibility of the integrated energy system and the power system in absorbing renewable energy. In this context, firstly, an electricity-to-gas optimization scheduling model is proposed, and the improved Conditional Value at Risk (CVaR) is proposed to deal with the uncertainty of wind power and photoelectric power output. Secondly, taking the integrated energy system with the P2G operating cost and the carbon emission cost as the objective function, an optimal scheduling model of the multi-energy system is solved by the A Mathematical Programming Language (AMPL) solver. Finally, the results of the example illustrate the optimal multi-energy system scheduling model and analyze the economic benefits of the P2G technology to improve the system to absorb wind power and photovoltaic power. The simulation calculation of the proposed model demonstrates the necessity of taking into account the operating cost of the electrical gas conversion in the integrated energy system, and the feasibility of considering the economic and wind power acceptance capabilities.

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