Abstract

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.

Highlights

  • integrated energy system (IES) refers to the use of advanced physical information technology and innovative management modes in a certain region and to the integration of regional coal, oil, natural gas, electrical energy, thermal energy and other kinds of energy to achieve a variety of heterogeneous energy subsystems: coordination planning, optimization operation, collaborative management, and interactive and complementary response

  • At the same time, considering the existence of gas turbines, the production of heat and electricity in the comprehensive energy system has some degree of interconnection [5], which is often restricted by heat load

  • With regard to system operation risk, this paper introduces a stochastic optimization model based on conditional value at risk (CVaR), which takes the sum of expected operation costs and carbon emission penalty costs of the system as the minimum objective function and achieves control of the system operation risk while optimizing scheduling

Read more

Summary

Background and Motivation

With the high-speed development of the economy, fossil energy is increasingly exhausted. The renewable and clean energy dominated by solar energy and wind energy has been widely concerned. It is an irresistible trend for clean energy to replace fossil energy [3]. At the same time, considering the existence of gas turbines, the production of heat and electricity in the comprehensive energy system has some degree of interconnection [5], which is often restricted by heat load. This mode of operation is often referred to as “following the thermal load (FTL)”. This fixed operational mode has a fatal weakness which greatly reduces the flexibility of IES, so the improvement of the flexibility of IES has further research value and significance [6]

Literature Review
Contributions and Organization
Description of Operation Mechanism of FIES
Stochastic Optimization Reformulation Considering CVaR
Energy Efficiency Analysis
Solving Methodology
DI 1 PI
Case Study
Parameter Setting
Scenario Setting
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call