scholarly journals Distributed Economic Optimal Scheduling Scheme for Ship-Integrated Energy System Based on Load Prediction Algorithm

2021 ◽  
Vol 9 ◽  
Author(s):  
Yuxin Zhang ◽  
Qihe Shan ◽  
Fei Teng ◽  
Tieshan Li
Keyword(s):  
Power System ◽  
Environmental Protection ◽  
Energy Management ◽  
Load Forecasting ◽  
Energy System ◽  
Optimal Scheduling ◽  
Short Term ◽  
Scheduling Scheme ◽  
Load Demand ◽  
Integrated Energy System

In order to enhance navigation safety and promote environmental protection, this paper takes the problem of energy management in a ship-integrated energy system into consideration. According to the characteristics of navigation, an intelligent ship energy management model, simultaneously considering the social and economic benefits, has been proposed. Meanwhile, this paper analyzes a distributed optimal scheduling problem which considers renewable generation devices and an energy storage system. Combined with an electricity-power system and thermal-power system, we propose an optimal scheduling scheme to accurately meet the actual load demand based on the pre-results analyzed by the ensemble learning short-term load forecasting algorithm. In addition, the related stability analysis is given. Further, a series of simulation results have been presented, which denote that the proposed load forecasting algorithm can accurately analyze the short-term load demand trend, and the proposed optimization algorithm can effectively coordinate economic and environmental protection.

scholarly journals Day-Ahead and Intra-Day Optimal Scheduling of Integrated Energy System Considering Uncertainty of Source & Load Power Forecasting

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2539
Author(s):  
Zhengjie Li ◽  
Zhisheng Zhang
Keyword(s):  
Wind Power ◽  
Demand Response ◽  
Solar Power ◽  
Load Forecasting ◽  
Energy System ◽  
Optimal Scheduling ◽  
Scheduling Scheme ◽  
Load Power ◽  
Integrated Energy System ◽  
Operation Cost

At present, due to the errors of wind power, solar power and various types of load forecasting, the optimal scheduling results of the integrated energy system (IES) will be inaccurate, which will affect the economic and reliable operation of the integrated energy system. In order to solve this problem, a day-ahead and intra-day optimal scheduling model of integrated energy system considering forecasting uncertainty is proposed in this paper, which takes the minimum operation cost of the system as the target, and different processing strategies are adopted for the model. In the day-ahead time scale, according to day-ahead load forecasting, an integrated demand response (IDR) strategy is formulated to adjust the load curve, and an optimal scheduling scheme is obtained. In the intra-day time scale, the predicted value of wind power, solar power and load power are represented by fuzzy parameters to participate in the optimal scheduling of the system, and the output of units is adjusted based on the day-ahead scheduling scheme according to the day-ahead forecasting results. The simulation of specific examples shows that the integrated demand response can effectively adjust the load demand and improve the economy and reliability of the system operation. At the same time, the operation cost of the system is related to the reliability of the accurate prediction of wind power, solar power and load power. Through this model, the optimal scheduling scheme can be determined under an acceptable prediction accuracy and confidence level.

scholarly journals A short term load forecasting of integrated energy system based on CNN-LSTM

2020 ◽  
Vol 185 ◽  
pp. 01032
Author(s):  
Xianjun Qi ◽  
Xiwei Zheng ◽  
Qinghui Chen
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Pearson Correlation ◽  
Load Forecasting ◽  
Energy System ◽  
Composite Model ◽  
Short Term ◽  
Characteristic Quantity ◽  
Integrated Energy System ◽  
Coupling Characteristics

The accurate forecast of integrated energy loads, which has important practical significance, is the premise of the design, operation, scheduling and management of integrated energy systems. In order to make full use of the coupling characteristics of electricity, cooling and heating loads which is difficult to deal with by traditional methods, this paper proposes a new forecast model of integrated energy system loads based on the combination of convolutional neural network (CNN) and long short term memory (LSTM). Firstly, the Pearson correlation coefficients among the electricity, cooling and heating load series of the integrated energy system are calculated, and the results show that there is a strong coupling relationship between the loads of an integrated energy system. Then, the CNN-LSTM composite model is constructed, and CNN is used to extract the characteristic quantity which reflects the load coupling characteristics of the integrated energy system. Then, the characteristic quantity is converted into the time series input to LSTM, and the excellent time series processing ability of LSTM is used for load forecasting. The results show that the CNN-LSTM composite model proposed in this paper has higher prediction accuracy than the wavelet neural network model, CNN model and LSTM model.

scholarly journals A comprehensive energy system optimization method considering variable operating condition characteristics of equipment

2021 ◽  
Vol 256 ◽  
pp. 02029
Author(s):  
Yongli Wang ◽  
Suhang Yao ◽  
Siyi Tao ◽  
Yuze Ma ◽  
Yanchao Lu
Keyword(s):  
System Optimization ◽  
Energy System ◽  
Optimization Method ◽  
Operating Conditions ◽  
Optimal Scheduling ◽  
Scheduling Scheme ◽  
Load Rate ◽  
Integrated Energy System ◽  
Scheduling Method ◽  
Variable Operating Conditions

The economy of the Regional Integrated Energy System (RIES) scheduling scheme is affected by the parameter accuracy of different energy conversion equipment models. The traditional static energy hub (EH) model regards the equipment efficiency as a constant and ignores the variable condition characteristics of the equipment efficiency changing with the load rate. This paper presents an optimal scheduling method of RIES considering the characteristics of equipment under variable operating conditions. Firstly, the architecture of the integrated energy system is analyzed. Secondly, based on the DEH model, an optimal scheduling method of RIES was proposed considering the characteristics of equipment under variable operating conditions. Finally, an optimal scheduling analysis is performed for a typical RIs. The results show that the proposed method can improve the accuracy of the equipment model and reduce the cost prediction error by considering the variable operating conditions of the equipment, thus providing a more economical scheduling scheme for Ries.

scholarly journals Optimized Operation of Integrated Energy Microgrid with Energy Storage Based on Short-Term Load Forecasting

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 22
Author(s):  
Hanlin Dong ◽  
Zhijian Fang ◽  
Al-wesabi Ibrahim ◽  
Jie Cai
Keyword(s):  
Energy Storage ◽  
Optimization Technique ◽  
Load Forecasting ◽  
Energy System ◽  
Mixed Integer ◽  
Programming Approach ◽  
Short Term ◽  
Short Term Load Forecasting ◽  
Integrated Energy System ◽  
Optimal Coordination

This research proposes an optimization technique for an integrated energy system that includes an accurate prediction model and various energy storage forms to increase load forecast accuracy and coordinated control of various energies in the current integrated energy system. An artificial neural network is utilized to create an accurate short-term load forecasting model to effectively predict user demand. The 0–1 mixed integer linear programming approach is used to analyze the optimal control strategy for multiple energy systems with storage, cold energy, heat energy, and electricity to solve the problem of optimal coordination. Simultaneously, a precise load forecasting method and an optimal scheduling strategy for multienergy systems are proposed. The equipment scheduling plan of the integrated energy system of gas, heat, cold, and electricity is proposed after researching the operation characteristics and energy use process of the equipment in the combined power supply system. A system economic operation model is created with profit maximization in mind, while also taking into account energy coordination between energy and the power grid. The rationality of the algorithm and model is verified by analyzing the real data of a distributed energy station in Wuhan for two years.

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