scholarly journals Multi-time scale optimization scheduling of integrated energy system considering demand side response

2020 ◽  
Vol 213 ◽  
pp. 02038
Author(s):  
Peng Fang ◽  
Cui Mao ◽  
Yuping Chen ◽  
Shan Zhou ◽  
Rui You ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Operating Cost ◽  
Energy System ◽  
Demand Side ◽  
Response Characteristics ◽  
Side Load ◽  
Scheduling Model ◽  
Integrated Energy System ◽  
Demand Side Response ◽  
Optimization Scheduling

As the physical carrier of the energy Internet, the integrated energy system has become the focus of current research. Considering the renewable energy and demand side load fluctuations, using the price type and the alternative demand side response characteristics, a day-ahead and intraday optimization scheduling model that takes into account the demand side response is established, in which the intraday, according to the difference of electricity, cold/heat and natural gas scheduling time, a three-layer rolling optimization scheduling model is proposed. The example analysis shows that this model can suppress the fluctuation of renewable energy and load in the day, improve the stability of the system, and further reduce the operating cost of the system.

scholarly journals Integrated Energy Multi-Objective Operation Optimization

2020 ◽  
Vol 185 ◽  
pp. 01067
Author(s):  
Zhao Liu ◽  
Mengjin Hu ◽  
Xianlong Zhao ◽  
Yongli Wang ◽  
Suhang Yao ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Energy Flow ◽  
Energy System ◽  
Demand Side ◽  
Renewable Energy Consumption ◽  
Operation Optimization ◽  
Integrated Energy System ◽  
System Energy ◽  
Demand Side Response

The Integrated Energy System (IES) offers a new approach to the energy dilemma. It introduces demand-side response into the Regional Integrated Energy System (RIES) and proposes an operational optimization model considering Integrated Demand Side Response (IDSR) in the framework of RIES. First of all, the typical cold\thermal\electric RIES is used as a framework to establish the multi-energy flow model of RIES based on the energy flow relationships among energy production, conversion and consumption. Then, from the perspective of energy transfer, the potential to enhance renewable energy consumption by carrying out RIES to transfer the system energy flow is analyzed. Finally, the RIES operation optimization model considering IDSR is established with the goal of the economy of system operation, considering the system energy balance and the operating constraints of each energy device, and the solution algorithm is designed. Taking the RIES in a certain region as an example, the proposed method and model were verified computationally, and the results showed that IDR can effectively improve system economics and increase the level of renewable energy consumption.

scholarly journals Optimal operation of regional integrated energy system based on demand-side load response

2020 ◽  
Vol 213 ◽  
pp. 02005
Author(s):  
Peng Fang ◽  
Cui Mao ◽  
Yuping Chen ◽  
Shan Zhou ◽  
Rui You ◽  
...  
Keyword(s):  
Operating Cost ◽  
Electric Heating ◽  
Energy System ◽  
Optimal Operation ◽  
Energy Utilization ◽  
Utilization Rate ◽  
Demand Side ◽  
Side Load ◽  
Load Response ◽  
Integrated Energy System

The integrated energy system (IES) has the advantage of improving energy utilization and promoting energy flexibility. From the perspective of demand-side load response, this paper establishes demand-side power, thermal load response, and natural gas demand response models, and then constructs the objective function of the lowest operating cost of the regional IES for combined electric heating and gas supply, using Cplex to perform optimization. Finally, a typical northern park is taken as an example to analyze and verify the feasibility of the model and algorithm. The analysis of the case shows that considering the electric heating gas demand side response will be better than not considering or considering only the single and both responses, not only can reduce operating costs, achieve peak reduction and valley filling, but also reduce abandonment of wind and energy, and increase energy utilization rate.

scholarly journals An Energy Management Optimization Method for Community Integrated Energy System Based on User Dominated Demand Side Response

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4398
Author(s):  
Yiqi Li ◽  
Jing Zhang ◽  
Zhoujun Ma ◽  
Yang Peng ◽  
Shuwen Zhao
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Value At Risk ◽  
Operating Cost ◽  
Optimization Method ◽  
Conditional Value At Risk ◽  
Demand Side ◽  
Scheduling Model ◽  
Management Optimization ◽  
Demand Side Response

With the development of integrated energy systems (IES), the traditional demand response technologies for single energy that do not take customer satisfaction into account have been unable to meet actual needs. Therefore, it is urgent to study the integrated demand response (IDR) technology for integrated energy, which considers consumers’ willingness to participate in IDR. This paper proposes an energy management optimization method for community IES based on user dominated demand side response (UDDSR). Firstly, the responsive power loads and thermal loads are modeled, and aggregated using UDDSR bidding optimization. Next, the community IES is modeled and an aggregated building thermal model is introduced to measure the temperature requirements of the entire community of users for heating. Then, a day-ahead scheduling model is proposed to realize the energy management optimization. Finally, a penalty mechanism is introduced to punish the participants causing imbalance response against the day-ahead IDR bids, and the conditional value-at-risk (CVaR) theory is introduced to enhance the robustness of the scheduling model under different prediction accuracies. The case study demonstrates that the proposed method can reduce the operating cost of the community under the premise of fully considering users’ willingness, and can complete the IDR request initiated by the power grid operator or the dispatching department.

scholarly journals A calculation method of user response potential on demand side response in integrated energy system

2020 ◽  
Vol 467 ◽  
pp. 012028
Author(s):  
Hanxian Han ◽  
Jinman Luo ◽  
Ruijing Ye ◽  
Haobo Liang ◽  
Zhilu Zhang ◽  
...  
Keyword(s):  
Calculation Method ◽  
Energy System ◽  
Demand Side ◽  
On Demand ◽  
Integrated Energy System ◽  
Demand Side Response

scholarly journals Low Carbon Scheduling Optimization of Flexible Integrated Energy System Considering CVaR and Energy Efficiency

2019 ◽  
Vol 11 (19) ◽  
pp. 5375 ◽  
Author(s):  
Liu ◽  
Nie
Keyword(s):  
Renewable Energy ◽  
Value At Risk ◽  
Operation Mode ◽  
Operating Cost ◽  
Carbon Dioxide Emission ◽  
Energy System ◽  
Conditional Value At Risk ◽  
Low Carbon ◽  
Integrated Energy System ◽  
Use Efficiency

With the rapid transformation of energy structures, the Integrated Energy System (IES) has developed rapidly. It can meet the complementary needs of various energy sources such as cold, thermal, and electricity in industrial parks; can realize multi-energy complements and centralized energy supplies; and can further improve the use efficiency of energy. However, with the extensive access of renewable energy, the uncertainty and intermittentness of renewable energy power generation will greatly reduce the use efficiency of renewable energy and the supply flexibility of IES so as to increase the operational risk of the system operator. With the goal of minimum sum of the system-operating cost and the carbon-emission penalty cost, this paper analyzes the combined supply of cooling, heating, and power (CCHP) influence on system efficiency, compared with the traditional IES. The flexible modified IES realizes the decoupling of cooling, thermal, and electricity; enhances the flexibility of the IES in a variety of energy supply; at the same time, improves the use efficiency of multi-energy; and reasonably avoids the occurrence of energy loss and resource waste. With the aim of reducing the risk that the access of renewable energy may bring to the IES, this paper introduces the fuzzy c-mean-clustering comprehensive quality (FCM-CCQ) algorithm, which is a novel method superior to the general clustering method and performs cluster analysis on the output scenarios of wind power and photovoltaic. Meanwhile, conditional value at risk (CVaR) theory is added to control the system operation risk, which is rarely applied in the field of IES optimization. The model is simulated in a numerical example, and the results demonstrate that the availability and applicability of the presented model are verified. In addition, the carbon dioxide emission of the traditional operation mode; thermoelectric decoupling operation mode; and cooling, thermal, and electricity decoupling operation mode of the IES decrease successively. The system flexibility is greatly enhanced, and the energy-use rate of the system is improved as a whole. Finally, IES, after its flexible transformation, significantly achieve energy conservation, emission reduction, and environmental protection.

scholarly journals Optimal scheduling of building integrated energy system based on demand response

2020 ◽  
Vol 185 ◽  
pp. 01068
Author(s):  
Mengju Wei ◽  
Yang Yang ◽  
Mengjin Hu ◽  
Yongli Wang ◽  
Siyi Tao ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Demand Response ◽  
Cloud Model ◽  
Operating Cost ◽  
Energy System ◽  
Model Particle ◽  
On Demand ◽  
Integrated Energy System ◽  
Building Level ◽  
Particle Group

With the development of renewable energy technology, integrating a variety of renewable energy integrated energy systems can effectively solve the problem of optimizing the scheduling of buildings with high energy consumption and fast growth rate. Based on the modeling and analysis of various energy equipment in the system, the integrated energy system of building buildings, based on the demand response compensation price, with the lowest construction operating cost as the goal function, establishes the optimization scheduling model of building-level integrated energy system based on demand response, and uses the particle group algorithm based on cloud model improvement to optimize the solution of the model. The study is introduced for simulation to compare the two different modes of participation in demand response, and the optimal performance of cloud model particle group algorithm and elementary particle group algorithm. The results show that the cloud model particle group algorithm model based on demand response can effectively save the operating cost of the building-level integrated energy system, and reduce the power grid side load peak and valley difference.

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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