A comprehensive review of planning,modeling,optimization,and control of distributed energy systems

Distributed energy system,a decentralized low-carbon energy system arranged at the customer side,is characterized by multi-energy complementarity,multi-energy flow synergy,multi-process coupling,and multi-temporal scales(n-M characteristics).This review provides a systematic and comprehensive summary and presents the current research on distributed energy systems in three dimensions:system planning and evaluation,modeling and optimization,and operation and control.Under the regional environmental,resource,and policy constraints,planning distributed energy systems should fully integrate technical,economic,environmental,and social factors and consider device characteristics,system architecture,and source-load uncertainties.Further,this review presents four modeling perspectives for optimizing and analyzing distributed energy systems,including energy hub,thermodynamics,heat current,and data-driven.The system’s optimal operation and scheduling strategies,disturbance analysis,and related control methods are also discussed from the power system and thermal system,respectively.In all,more research is required for distributed energy systems based on an integrated energy perspective in optimal system structure,hybrid modeling approaches,data-driven system state estimation,cross-system disturbance spread,and multi-subject interaction control.

Planning of distributed renewable energy systems under uncertainty based on statistical machine learning

The development of distributed renewable energy,such as photovoltaic power and wind power generation,makes the energy system cleaner,and is of great significance in reducing carbon emissions.However,weather can affect distributed renewable energy power generation,and the uncertainty of output brings challenges to uncertainty planning for distributed renewable energy.Energy systems with high penetration of distributed renewable energy involve the high-dimensional,nonlinear dynamics of large-scale complex systems,and the optimal solution of the uncertainty model is a difficult problem.From the perspective of statistical machine learning,the theory of planning of distributed renewable energy systems under uncertainty is reviewed and some key technologies are put forward for applying advanced artificial intelligence to distributed renewable power uncertainty planning.

Data Center as a Key Player of a District Electric Power and Heat Network System： A Comparison in Urban and Suburb Regions

A DC （data center） demands air-conditioning power as large as the 1/3-1/2 of total electricity consumption. Thus, energy saving of cooling power of DC yields considerable effect on both economic and environmental views. PV （Photovoltaic） and absorption refrigerator with CGS （cogeneration systems） or gas boiler are possible power saving options. The waste warm air from DC would be utilized for greenhouse heating when DC and greenhouse locate near in the suburbs. In this study, the authors develop an energy network model to assess the potential contribution of DC as a major electric power and chilled air consumer as well as the warm air supplier in a district to the energy efficiency improvement. The evaporation heat of LNG （liquefied natural gas） utilization is also considered as well as PV, CGS. This model is applied to the cases of the urban area in Tokyo which involves athletic center, shops and hospital and the suburbs including greenhouse and then compared.

Fluid dynamic modeling of a free piston engine with labyrinth seals

Preliminary design and simulation of a free piston engine suitable for small-scale energy production in distributed energy systems is presented in this paper.The properties,particularly the properties of gas seals of the engine are simulated using a simulation program developed for this case,and the results are utilized in preliminary main design parameter selection.The engine simulation program was developed by combining and modifying the source codes of the simulation and calculation programs obtained from Helsinki University of Technology,Tampere University of Technology,and Lappeenranta University of Technology.Because of the contact-free labyrinth seal used in the piston,the efficiency of the motor is lower than the efficiency of a conventional motor with oil lubricated piston rings.On the other hand,the lack of bearing losses,and the lack of losses associated with a crankshaft system and a gearbox,as well as the lack of lubrication oil expenses,compensates this effect.As a net result,this new motor would perform slightly better than the conventional one.Being completely oil-free,it is very environmentally friendly,and its exhaust gases are completely free of oil residuals which are causing problems in normal gas motors.