Scheduling coordination of back pressure CHP coupled electricity-heat energy system with adaptive constraint strategy to accommodate uncertain wind power

Energy ◽  
2021 ◽  
pp. 122791
Author(s):  
Zhejing Bao ◽  
Yangli Ye ◽  
Ruijie Liu ◽  
Weidong Cheng ◽  
Qiang Zhao ◽  
...  
Keyword(s):  
Wind Power ◽  
Energy System ◽  
Back Pressure ◽  
Heat Energy

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.

Implementing a Fuzzy Logic Based Algorithm to Predict Solar and Wind Energies in a Hybrid Renewable Energy System

2015 ◽  
Vol 4 (3) ◽  
pp. 10-24 ◽  
Author(s):  
Sanaa Faquir ◽  
Ali Yahyaouy ◽  
Hamid Tairi ◽  
Jalal Sabor
Keyword(s):  
Fuzzy Logic ◽  
Renewable Energy ◽  
Wind Power ◽  
Input Parameter ◽  
Energy System ◽  
System Stability ◽  
Industrial Sectors ◽  
Hybrid Renewable Energy System ◽  
Renewable Energy System ◽  
Hybrid Renewable Energy

The use of multi sources systems of energy progressed significantly in different industrial sectors. Between all the existing sources of energy, batteries and renewable sources, such as photovoltaic and wind, contain the highest specified energy. However, solar and wind energies are not available all the time, their performance is affected by unpredictable weather changes and therefore, it is difficult to control as it is not always feasible to obtain an accurate mathematical model of the controlled system. Also, uncertainty of the wind power can affect system stability. This paper presents a computer algorithm based on fuzzy logic control (FLC) to estimate the wind and solar energies in a hybrid renewable energy system from natural factors. The wind power was estimated using the wind speed as an input parameter and the solar power was estimated using the temperature and the lighting as input parameters.

scholarly journals Impacts of Electric Road Systems on the German and Swedish Electricity Systems—An Energy System Model Comparison

2021 ◽  
Vol 9 ◽  
Author(s):  
Johanna Olovsson ◽  
Maria Taljegard ◽  
Michael Von Bonin ◽  
Norman Gerhardt ◽  
Filip Johnsson
Keyword(s):  
Wind Power ◽  
Peak Power ◽  
Large Scale ◽  
Solar Power ◽  
Energy System ◽  
Transport Sector ◽  
Electricity System ◽  
Road Systems ◽  
The Impact ◽  
Electricity Systems

This study analyses the impacts of electrification of the transport sector, involving both static charging and electric road systems (ERS), on the Swedish and German electricity systems. The impact on the electricity system of large-scale ERS is investigated by comparing the results from two model packages: 1) a modeling package that consists of an electricity system investment model (ELIN) and electricity system dispatch model (EPOD); and 2) an energy system investment and dispatch model (SCOPE). The same set of scenarios are run for both model packages and the results for ERS are compared. The modeling results show that the additional electricity load arising from large-scale implementation of ERS is mainly, depending on model and scenario, met by investments in wind power in Sweden (40–100%) and in both wind (20–75%) and solar power (40–100%) in Germany. This study also concludes that ERS increase the peak power demand (i.e., the net load) in the electricity system. Therefore, when using ERS, there is a need for additional investments in peak power units and storage technologies to meet this new load. A smart integration of other electricity loads than ERS, such as optimization of static charging at the home location of passenger cars, can facilitate efficient use of renewable electricity also with an electricity system including ERS. A comparison between the results from the different models shows that assumptions and methodological choices dictate which types of investments are made (e.g., wind, solar and thermal power plants) to cover the additional demand for electricity arising from the use of ERS. Nonetheless, both modeling packages yield increases in investments in solar power (Germany) and in wind power (Sweden) in all the scenarios, to cover the new electricity demand for ERS.

scholarly journals Low-Carbon Economic Bi-Level Optimal Dispatching of an Integrated Power and Natural Gas Energy System Considering Carbon Trading

2021 ◽  
Vol 11 (15) ◽  
pp. 6968
Author(s):  
Hong Li ◽  
Yazhong Ye ◽  
Lanxin Lin
Keyword(s):  
Natural Gas ◽  
Power System ◽  
Wind Power ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Energy System ◽  
Mixed Integer ◽  
Carbon Trading ◽  
Carbon Emission Reduction ◽  
Gas System

The integrated power and natural gas energy system (IPGES) is of great significance to promote the coordination and complementarity of multi-energy flow, and it is an important carrier to increase the proportion of wind power accommodation and achieve the goal of carbon emission reduction. In this paper, firstly, the reward and punishment ladder-type carbon trading model is constructed, and the impact of the carbon trading mechanisms on the carbon emission sources in the power system is comparatively analyzed. Secondly, in order to achieve a reasonable allocation of carbon resources in IPGES, a bi-level optimization model is established while taking into account the economics of dispatching and the requirements of carbon emission reduction. Among them, the outer layer is the optimal carbon price solution model considering carbon trading; in the inner layer, considering the power system constraints, natural gas system constraints, and coupling element operation constraints, a stochastic optimal dispatching model of IPGES based on scenario analysis is established. Scenario generation and reduction methods are used to deal with the uncertainty of wind power, and the inner model is processed as a mixed integer linear programming problem. In the MATLAB environment, program the dichotomy and call the Gurobi optimization solver to complete the interactive solution of the inner and outer models. Finally, case studies that use an integrated IEEE 39-bus power system and Belgian 20-node gas system demonstrate the effectiveness and scalability of the proposed model and optimization method.

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