scholarly journals A Robust Formulation Model for Multi-Period Failure Restoration Problems in Integrated Energy Systems

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3673
Author(s):  
Chen ◽  
Lou ◽  
Guo
Keyword(s):  
Natural Disasters ◽  
High Efficiency ◽  
Storage System ◽  
Energy Systems ◽  
Mixed Integer ◽  
Level Energy ◽  
Piecewise Linearization ◽  
Integrated Energy Systems ◽  
Failure Restoration ◽  
Robust Formulation

The risks faced by modern energy systems are increasing, primarily caused by natural disasters. As a new form of multi-level energy complimentary utilization, integrated energy systems are attracting more and more attention for their high-efficiency and low-cost. However, due to the deep coupling relationship between systems, they are more susceptible to natural disasters, resulting in a cascading failure. To enhance the resilience of the integrated electricity-gas system, this paper proposes a failure restoration strategy after a natural disaster occurs. First, the temporal constraints of the dispatching model are considered, and the failure restoration problem is molded into a multi-period mixed-integer linear programme, aiming to recover the interrupted loads as much as possible. Second, since the uncertain output of distributed generation sources (DGs) such as wind turbines and photovoltaic systems will threat the reliability of restoration results, the robust formulation model is incorporated to cope with this problem. Third, we propose a new modeling method for radial topology constraints towards failure restoration. Moreover, the Column and Constraints Generation (C&CG) decomposition method is utilized to solve the robust model. Then, the piecewise linearization technique and the linear DistFlow equations are utilized to eliminate the nonlinear terms, providing a model that could be easily solved by an off-shelf commercial solver. The obtained results include the sequence of line/pipeline switchgear actions, the time-series dispatching results of electricity storage system, gas storage system, and the coupling devices including the gas-fired turbine, power to gas equipment. Finally, the effectiveness of the proposed restoration strategy is verified by numerical simulation on a 13-6 node integrated energy system.

scholarly journals Optimal Design on Fossil-to-Renewable Energy Transition of Regional Integrated Energy Systems under CO2 Emission Abatement Control: A Case Study in Dalian, China

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2879
Author(s):  
Xinxin Liu ◽  
Nan Li ◽  
Feng Liu ◽  
Hailin Mu ◽  
Longxi Li ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Optimal Design ◽  
Co2 Emission ◽  
Energy Demand ◽  
Energy Systems ◽  
Energy System ◽  
Mixed Integer ◽  
Total Annual Cost ◽  
Emission Abatement ◽  
Integrated Energy Systems

Optimal design of regional integrated energy systems (RIES) offers great potential for better managing energy sources, lower costs and reducing environmental impact. To capture the transition process from fossil fuel to renewable energy, a flexible RIES, including the traditional energy system (TES) based on the coal and biomass based distributed energy system (BDES), was designed to meet a regional multiple energy demand. In this paper, we analyze multiple scenarios based on a new rural community in Dalian (China) to capture the relationship among the energy supply cost, increased share of biomass, system configuration transformation, and renewable subsidy according to regional CO2 emission abatement control targets. A mixed integer linear programming (MILP) model was developed to find the optimal solutions. The results indicated that a 40.58% increase in the share of biomass in the RIES was the most cost-effective way as compared to the separate TES and BDES. Based on the RIES with minimal cost, by setting a CO2 emission reduction control within 40%, the RIES could ensure a competitive total annual cost as compared to the TES. In addition, when the reduction control exceeds 40%, a subsidy of 53.83 to 261.26 RMB/t of biomass would be needed to cover the extra cost to further increase the share of biomass resource and decrease the CO2 emission.

Coordinated Regional-District Operation of Integrated Energy Systems for Resilience Enhancement in Natural Disasters

2019 ◽  
Vol 10 (5) ◽  
pp. 4881-4892 ◽  
Author(s):  
Mingyu Yan ◽  
Yubin He ◽  
Mohammad Shahidehpour ◽  
Xiaomeng Ai ◽  
Zhiyi Li ◽  
...  
Keyword(s):  
Natural Disasters ◽  
Energy Systems ◽  
Integrated Energy Systems

Co-Design Optimization of a Combined Heat and Power Hybrid Energy System

2021 ◽  
Author(s):  
Dongze Li ◽  
Jiaxin Wu ◽  
Jie Zhang ◽  
Pingfeng Wang
Keyword(s):  
Design Optimization ◽  
Storage System ◽  
Energy Systems ◽  
Combined Heat And Power ◽  
Mixed Integer ◽  
Production Operation ◽  
Efficient Technology ◽  
Hybrid Energy ◽  
Hybrid Energy Systems ◽  
Component Design

Abstract As an energy efficient technology that generates electricity and captures the heat that would otherwise be wasted to provide useful thermal energy, combined heat and power (CHP) hybrid energy systems have been widely used in the U.S. In the presented study, a two-stage co-design optimization model for CHP-based hybrid energy systems is developed. By applying a mixed integer programming (MIP) method, the optimization is performed from the operational and design perspectives. Six components: CHP, boiler, heat recover unit (HRU), thermal storage system (TS), power storage system (ES), and photovoltaic (PV) are considered in the CHP-based microgrids. During the optimization process, the cost-based optimal component design solutions are firstly obtained by minimizing the total installation costs of the components. The optimal operational strategy is further attained based on the component design by minimizing the costs from production, operation and maintenance, startup, and unsatisfied load. In the end, non-disruptive and disruptive scenarios are considered in the case study to testify to the model’s effectiveness in co-design and reliability improvement.

scholarly journals Configuration Optimization Model for Data-Center-Park-Integrated Energy Systems under Economic, Reliability, and Environmental Considerations

Energies ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 448 ◽  
Author(s):  
Zhiyuan Liu ◽  
Hang Yu ◽  
Rui Liu ◽  
Meng Wang ◽  
Chaoen Li
Keyword(s):  
Carbon Emissions ◽  
Data Center ◽  
High Reliability ◽  
Estimation Method ◽  
Energy Systems ◽  
Reliability Estimation ◽  
Mixed Integer ◽  
Configuration Model ◽  
Low Carbon ◽  
Integrated Energy Systems

The analysis of energy configuration in the planning of data-center-park-integrated energy systems (DCP-IESs) has become an enormous challenge, owing to multi-energy complementarity, energy cascade use, and energy security. In this study, a configuration model of DCP-IESs was established to obtain the economic and low-carbon energy uses of the data centers, based on mixed integer linear programming. In the model, carbon emissions were converted to economic indicators through carbon pricing. Then, the configuration model was modified according to the security of the proposed device switching logic, and the Markov-based reliability estimation method was used to ensure the redundant design of the configuration. Using the new energy configuration method, the DCP-IES configuration scheme could be obtained under economical, low-carbon, and high reliability conditions. A data center park in Shanghai was selected as a case study, and the results are as follows: it will only take 2.88 years for the economics of DCP-IES to reach those of traditional data center energy systems. Additionally, the use of configuration model in DCP-IES would result in a reduction in annual carbon emissions of 39,323 tons, with a power usage effectiveness of 1.388, whereas an increase in reliability results in an increasingly faster increase in the initial investment cost.

scholarly journals Classification and Analysis of Optimization Techniques for Integrated Energy Systems Utilizing Renewable Energy Sources: A Review for CHP and CCHP Systems

Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 339 ◽  
Author(s):  
Mohammad Ali Bagherian ◽  
Kamyar Mehranzamir ◽  
Amin Beiranvand Pour ◽  
Shahabaldin Rezania ◽  
Elham Taghavi ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Renewable Energy Sources ◽  
Energy Systems ◽  
Evolutionary Computing ◽  
Energy Generation ◽  
Optimization Methods ◽  
Optimization Techniques ◽  
Mixed Integer ◽  
Energy Sources ◽  
Integrated Energy Systems

Energy generation and its utilization is bound to increase in the following years resulting in accelerating depletion of fossil fuels, and consequently, undeniable damages to our environment. Over the past decade, despite significant efforts in renewable energy realization and developments for electricity generation, carbon dioxide emissions have been increasing rapidly. This is due to the fact that there is a need to go beyond the power sector and target energy generation in an integrated manner. In this regard, energy systems integration is a concept that looks into how different energy systems, or forms, can connect together in order to provide value for consumers and producers. Cogeneration and trigeneration are the two most well established technologies that are capable of producing two or three different forms of energy simultaneously within a single system. Integrated energy systems make for a very strong proposition since it results in energy saving, fuel diversification, and supply of cleaner energy. Optimization of such systems can be carried out using several techniques with regards to different objective functions. In this study, a variety of optimization methods that provides the possibility of performance improvements, with or without presence of constraints, are demonstrated, pinpointing the characteristics of each method along with detailed statistical reports. In this context, optimization techniques are classified into two primary groups including unconstrained optimization and constrained optimization techniques. Further, the potential applications of evolutionary computing in optimization of Integrated Energy Systems (IESs), particularly Combined Heat and Power (CHP) and Combined Cooling, Heating, and Power (CCHP), utilizing renewable energy sources are grasped and reviewed thoroughly. It was illustrated that the employment of classical optimization methods is fading out, replacing with evolutionary computing techniques. Amongst modern heuristic algorithms, each method has contributed more to a certain application; while the Genetic Algorithm (GA) was favored for thermoeconomic optimization, Particle Swarm Optimization (PSO) was mostly applied for economic improvements. Given the mathematical nature and constraint satisfaction property of Mixed-Integer Linear Programming (MILP), this method is gaining prominence for scheduling applications in energy systems.

Sign in / Sign up

Export Citation Format

Share Document