The coupling impact of subsystem interconnection and demand response on the distributed energy systems: A case study of the composite community in China

Energy ◽  
2021 ◽  
pp. 120588
Author(s):  
Rui Qiu ◽  
Qi Liao ◽  
Jie Yan ◽  
Yamin Yan ◽  
Zhichao Guo ◽  
...  
2017 ◽  
Vol 142 ◽  
pp. 1991-1996 ◽  
Author(s):  
Jing Kang ◽  
Shengwei Wang ◽  
Wenjie Gang

2020 ◽  
Vol 197 ◽  
pp. 01006
Author(s):  
Pietro Lubello ◽  
Guglielmo Vaccaro ◽  
Carlo Carcasci

Renewable energy systems (RES) are currently being deployed on a large scale to meet the ambitious sustainable development goals for the next decades. A higher penetration of sustainable means of power production passes through the diffusion of RES-based distributed energy systems. The hybridization of such systems and their integration with Energy Storage Systems (ESS) can help improve reliability and level the mismatch between power production and consumption. In this paper, a novel modular tool for the simulation of distributed energy systems is presented by means of its application to a case study. The considered system is composed by PV modules, ESS and heat pumps. The optimal sizing of the components for self-consumption has been obtained through an electricity production cost minimization. A comparison between two different configurations has been conducted: in the first case, the thermal load is completely satisfied by a natural gas-fired boiler, while in the latter case, part of the thermal load is satisfied by a heat pump. The results have highlighted the impact of ESS on the economics of distributed energy systems and how the investment in such systems, in conditions similar to the case study, can be more easily sustained if a share of the total energy consumption of the unit is shifted from the thermal to the electrical part.


2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Yeşim Ok ◽  
Mehmet Atak

An optimal allocation of centralized district-scale distributed energy resource (DER) systems with district heating and cooling network (DHCN) is studied. A generic mixed integer linear programming (MILP) model is constructed to increase the system efficiency and decrease costs by reducing energy distribution losses and transportation costs in energy distribution network. Initial investment costs based on size and type (co/trigeneration) of the facility and demand-weighted transportation costs are minimized by the capacitated fixed charge facility location (FCFL) model. However, unlike the standard FCFL model, by adding the maximum coverage distance in the set covering problem, a new method has been proposed. Thus, its aim is to avoid assigning a demand point to a candidate facility from a point farther than the predetermined distance. That means that the weakness of disregarding the distance between supply and demand points in the FCFL problem is eliminated. Additionally, this model, in which the annual inputs are used, has a generic framework suitable to form infrastructure needs in consideration of distributed energy systems in the general planning level for sustainable urban planning. For this purpose, the applications of the model, both case study and tests, have been made over wide areas, with annual demand and capacity values. Consequently, a case study with different coverage distances has been conducted to see the effect of coverage distance on the model, and also test problems with different sizes have been carried out to demonstrate the capability of the proposed model.


2017 ◽  
Vol 192 ◽  
pp. 329-336 ◽  
Author(s):  
Liuchen Liu ◽  
Tong Zhu ◽  
Yu Pan ◽  
Hai Wang

Author(s):  
Jian Zhang ◽  
Heejin Cho ◽  
Hongguang Zhang ◽  
Fubin Yang

As a promising approach for sustainable development, the distributed energy system receives increasing attention worldwide and has become a key topic explored by researchers in the areas of building energy systems and smart grid. In line with this research trend, this paper presents a case study of designing an integrated distributed energy system including photovoltaics (PV), combined cooling heating and power (CCHP) and electric and thermal energy storage for commercial buildings (i.e., a hospital and a large hotel). The subsystems are modeled individually and integrated based on a proposed control strategy to meet the electric and thermal energy demand of a building. A multi-objective particle swarm optimization (PSO) is performed to determine the optimal size of each subsystem with objectives to minimize carbon dioxide emissions and payback period. The results demonstrate that the proposed method can be effectively utilized to obtain an optimized design of distributed energy systems that can minimize environmental and economic impacts for different buildings.


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