Assessing environmental impact:Micro-energy network optimization in a Chinese industrial park

Micro-energy systems contribute significantly to environmental improvement by reducing dependence on power grids through the utilization of multiple renewable energy sources.This study quantified the environmental impact of a micro-energy network system in an industrial park through a life cycle assessment using the operation of the micro-energy network over a year as the functional unit and“cradle-to-gate”as the system boundary.Based on the baseline scenario,a natural gas generator set was added to replace central heating,and the light pipes were expanded to constitute the optimized scenario.The results showed that the key impact categories for both scenarios were global warming,fine particulate matter formation,human carcinogenic toxicity,and human non-carcinogenic toxicity.The overall environmental impact of the optimized scenario was reduced by 68%compared to the baseline scenario.A sensitivity analysis of the key factors showed that electricity from the power grid was the key impact factor in both scenarios,followed by central heating and natural gas.Therefore,to reduce the environmental impact of network systems,it is necessary to further optimize the grid power structure.The research approach can be used to optimize micro-energy networks and evaluate the environmental impact of different energy systems.

Integrated energy efficiency evaluation of a multi-source multi-load desalination micro-energy network

With increasing global shortage of fresh water resources,many countries are prioritizing desalination as a means of utilizing abundantly available seawater resources.Integrated energy efficiency evaluation is a scientific method for the quantitative analysis of energy efficiency based on multiple indicators and is very useful for investment,construction,and scientific decision-making for desalination projects.In this paper,the energy efficiency evaluation of the micro energy network (MEN) of desalination for multi-source and multi-load is studied,and the basic idea of comprehensive energy efficiency evaluation is analyzed.The process includes the use of a MEN model to establish an integrated energy efficiency evaluation index system,taking into consideration energy,equipment,economic,environmental,and social factors.A combined evaluation method considering subjective and objective comprehensive weights for multi-source multi-load desalination MENs is proposed to evaluate the energy efficiency of desalination and from multiple perspectives.

Optimal Operation of Energy Hub Based Micro-energy Network with Integration of Renewables and Energy Storages

This study proposes an optimized model of a micro-energy network(MEN)that includes electricity and natural gas with integrated solar,wind,and energy storage systems(ESSs).The proposed model is based on energy hubs(EHs)and it aims to minimize operation costs and greenhouse emissions.The research is motivated by the increasing use of renewable energies and ESSs for secure energy supply while reducing operation costs and environment effects.A general algebraic modeling system(GAMS)is used to solve the optimal operation problem in the MEN.The results demonstrate that an optimal MEN formed by multiple EHs can provide appropriate and flexible responses to fluctuations in electricity prices and adjustments between time periods and seasons.It also yields significant reductions in operation costs and emissions.The proposed model can contribute to future research by providing a more efficient network model(as compared with the traditional electricity supply system)to scale down the environmental and economic impacts of electricity storage and supply systems on MEN operation.

Optimal Operation of Micro-energy Grids Considering Shared Energy Storage Systems and Balanced Profit Allocations

Following the unprecedented generation of renewable energy,Energy Storage Systems(ESSs)have become essential for facilitating renewable consumption and maintaining reliability in energy networks.However,providing an individual ESS to a single customer is still a luxury.Thus,this paper aims to investigate whether the Shared-ESS can assist energy savings for multiple users through Peer-to-Peer(P2P)trading.Moreover,with the increasing number of market participants in the integrated energy system(IES),a benefit allocation scheme is necessary,ensuring reasonable benefits for every user in the network.Using the multiplayer cooperative game model,the nucleolus and the Shapley value methods are adopted to evaluate the benefit allocation between multiple users.Numerical analyses based on multiple micro-energy grids are performed,so as to assess the performance of the Shared-ESS and the proposed benefit allocation scheme.The results show that the micro-energy grid cluster can save as much as 38.15%of the total energy cost with Shared-ESS being equipped.The following conclusions can be drawn:the Shared-ESS can significantly reduce the operating costs of the micro-energy grid operator,promote the consumption of renewable energy,and play the role of peak-shaving and valley-filling during different energy usage periods.In addition,it is reflected that the multiplayer cooperative game model is effective in revealing the interaction between the micro-energy grids,which makes the distribution results more reasonable.

Optimization for Micro-energy Grid Dispatch Based on Non-supplementary Fired Compressed Air Energy Storage Aided Energy Hub and Hybrid Hyper-spherical Search

Micro-energy grids have shown superiorities over traditional electricity and heating management systems.This paper presents a hybrid optimization strategy for micro-energy grid dispatch with three salient features.First,to enhance the ability to support new storage equipment,an energy hub model is proposed using the non-supplementary fired compressed air energy storage(NSF-CAES).This provides flexible dispatch for cooling,heating and electricity.Second,considering the unique characteristics of the NSF-CAES,a sliding time window(STW)method is designed for simple but effective energy dispatch.Third,for the optimization of energy dispatch,we blend the differential evolution(DE)with the hyper-spherical search(HSS)to formulate a hybrid DE-HSS algorithm,which enhances the global search ability and accuracy.Comparative case studies are performed using real data of scenarios to demonstrate the superiorities of the proposed scheme.