Integrated Intelligent Energy

Optimal scheduling of integrated energy systems based on NSGA-Ⅱ-WPA

LI Yun, ZHOU Shijie, HU Zheqian, LIANG Junyuan, XIAO Leiming

2024, 46(4): 1-9. doi:10.3969/j.issn.2097-0706.2024.04.001

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Since the optimal scheduling on integrated energy systems （IES） with complex multi-energy flows can hardly balance the economy and low-carbon operation， an NSGA-Ⅱ-WPA algorithm based on non-dominant genetic algorithm （NSGA-Ⅱ） and wolf pack algorithm （WPA） is proposed. The proposed algorithm can realize the multi-objective optimization. Firstly， an IES scheduling model of strong coupling relationship is established considering the characteristics of the IES with multi-energy flows which integrates a power supply subsystem， a heat supply subsystem and a cooling supply subsystem. Secondly， the basic IES operation strategies are designed which includes the battery storage operation strategy under real-time pricing mechanism， layered energy supply strategy and carbon emission trading strategy. The strategies aim to realize the collaborative control optimization on the IES influenced by the multiple factors. Finally， the multi-objective optimization for the IES with multi-energy flows is completed based on the NNSGA-Ⅱ-WPA algorithm. The operational cost and carbon emissions of the IES are evaluated by simulation experiments， and the experimental results prove that the improvement on comprehensive energy efficiency of the IES provided by the proposed algorithm is better than that by NSGA-Ⅱ algorithm.

Joint economic dispatch of an AC/DC power system and a heating system

SHI Mingming, ZHU Rui, LIU Ruihuang

2024, 46(4): 10-16. doi:10.3969/j.issn.2097-0706.2024.04.002

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With the wide application of combined heat and power technology， the coupling between power systems and heating systems is becoming increasingly tight， and the combined heat and power dispatch （CHPD） has received extensive attention. However， existing CHPD models often ignore the diversity of heat sources. To fill this gap， a joint economic dispatch method for AC/DC power systems and heating systems is proposed. Firstly， a linear approximation method is taken to deal with the strong nonlinearity caused by the voltage source converter in a hybrid AC/DC power system model. Then， aiming at minimizing the operating cost， a CHPD model considering the thermal inertia of the heating network is established. In the joint dispatch model， the heating system is coupled with the AC power system through CHP units and AC-driven electric boilers， and coupled with the DC power system through DC-driven electric boilers. Finally， the effectiveness of the proposed method is verified by case studies， and the necessity of taking AC and DC power sources into consideration during the joint economic dispatch of electricity and heat is demonstrated.

Optimal scheduling strategy of distributed PV‒energy storage systems based on PV output characteristics

DONG Qiang, XU Jun, FANG Dongping, FANG Lijuan, CHEN Yanqiong

2024, 46(4): 17-23. doi:10.3969/j.issn.2097-0706.2024.04.003

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With the transformation and upgrading of China's energy mix， solar power generation technology has received increasing attention. However， large-scale grid-connection of distributed PV power stations will cause power fluctuations in the power grid. Since energy storage systems can facilitate load and frequency regulations， a joint optimal scheduling method for PV‒energy storage systems is proposed. Firstly， the optimal scheduling model of a PV‒energy storage system is constructed considering its economy and technical indicators， and the charging and discharging power of the energy storage modules are optimized with the aim of minimizing the variance of active power fluctuations. Secondly， a real-time scheduling strategy based on predicted PV outputs is proposed to improve the orderly grid-connection of distributed PV‒energy storage systems， which can smooth the load fluctuation of the grid and reduce load‒valley difference. Finally， a simulation study is designed and carried out to verify the feasibility of the method.

Capacity planning method with high reliability for integrated energy systems with low-carbon emissions based on scenario expansion

CHEN Yong, XIAO Leiming, WANG Jingnan, WU Jian

2024, 46(4): 24-33. doi:10.3969/j.issn.2097-0706.2024.04.004

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In the context of addressing frequent extreme weather around the world and urgent needs for low-carbon energy supply， an integrated energy system （IES） that can couple multiple local energy sources is considered to be an effective paradigm for improving energy efficiency and reducing carbon emissions. Due to the limit of carbon emissions，the uncertain outputs of various renewable energy sources in an IES ，and unstable demands on cold， heat and electricity， an optimal capacity planning method aiming at optimizing the economic cost， local energy supply reliability and carbon emission cost of the IES is proposed. The planning method can expand the IES operation scenarios with the help of data-driven denoising diffusion model. It improves the reliability of the optimization model under uncertain conditions. Based on the simulation experiment on actual case data， the results show that compared with the traditional planning method， the proposed planning method reduces the operating cost by 34.5%， and reduces the carbon emission by 39.4%.

Performance optimization of photovoltaic/thermal systems coupled with air source heat pumps

TANG Zihan, WANG Shuaijie, JU Zhenhe, LEI Zhiqi

2024, 46(4): 34-41. doi:10.3969/j.issn.2097-0706.2024.04.005

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To explore the performance of photovoltaic/thermal（PV/T） systems coupled with air source heat pumps in certain regions， the daily electricity generation， daily power consumption， heating effect and total investment of a coupling system during heating season were analysed by experiments and numerical model analyses. Firstly， the simulation model was established by Trnsys， and the simulation results were compared with the experimental results. Secondly， the angle of PV/T modules， the area of PV/T modules， the heating capacity of the air source heat pump，hot water tank temperature， and the capacity of batteries were optimized by non-dominated sorting genetic algorithm（NSGA-II）.Taking the highest electricity generation of the PV system， the lowest power consumption of the heating system and the minimal initial investment of the coupling system as objectives， the performance of the coupling system was improved by the multi-objective optimization carried out in JEplus software. Finally， the configuration scheme after the optimization shows a 117.40% increase in the electricity generation of the PV system and a 38.76% decrease in the power consumption of the coupling system， with only additional 9 700 yuan in its initial investment.

Collaborative optimization method for power-heat-gas integrated energy systems considering multiple uncertainties

WANG Jinglong, WANG Hui, YANG Ye, ZHENG Yingying

2024, 46(4): 42-51. doi:10.3969/j.issn.2097-0706.2024.04.006

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The uncertainties of wind outputs， solar outputs and loads of integrated energy systems（IES） challenge IES operational safety and planning. To address this issue， an IES integrating photovoltaics（PV） units and a biomass gasification combined heating and power（BCHP） unit is studied. A scheduling method based on integrated stochastic programming and information gap decision theory（IGDT） is proposed to eliminate the uncertainties on the source side and user side of the IES during its collaborative optimization. Stochastic programming can deal with the short-term uncertainty of PV outputs， and its optimization results are taken as the benchmark of load uncertainty optimization by IGDT.While resisting the operational risks triggered by the uncertainties in IGDT optimization， the IES managers tend to choose two strategies， risk-aversion strategy and risk-taking strategy. The test results on the case demonstrate that the daily power output of the BCHP unit under risk-aversion strategy is 50% higher under that under risk-taking strategy. Different dispatching results under different strategies give system managers flexible choices.

Economic dispatch of multi-energy complementary systems considering multi-period scales and regional stratification

ZHONG Yongjie, WANG Zidong, ZUO Jianxun, WANG Changqing, LI Jingxia, JI Ling

2024, 46(4): 52-59. doi:10.3969/j.issn.2097-0706.2024.04.007

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To complete the coupling and interconnection of electric and heating sources，an economic dispatch strategy for electric-heating coupled multi-energy complementary systems considering multi-period scales and regional stratification is provided. Analyzing from the perspectives of single period and multi-period，this strategy comprehensively considers the energy balance relationship at local level and regional level to achieve the economic dispatch of a multi-energy complementary system. Firstly，bus electric balance model and bus heating balance model are established based on the collected data and information of local-level energy resources. Secondly，a common bus energy balance model at regional level is proposed，in which the equivalent idea is adopted to aggregate the units of the same type. Then， a typical electric-heating coupled energy system model at local level is established. Finally，the economic scheduling results are obtained from the electric-heating coupled system dispatch strategy implementation. The effectiveness and rationality of the economic dispatch of the electric-heating coupled multi-energy complementary system have been verified through simulation examples，providing reference and theoretical guidance for multi-energy complementary utilization，resource coordination，economic and efficient operation of the multi-energy complementary systems at regional level.

Prediction on loads and photovoltaic output coefficients based on Informer

MIAO Yuesen, XIA Hongjun, HUANG Ningjie, LI Yun, ZHOU Shijie

2024, 46(4): 60-67. doi:10.3969/j.issn.2097-0706.2024.04.008

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A long-term time series forecast on electric loads and photovoltaic output coefficients is crucial for the layout and installed capacity design of renewable energy. A photovoltaic output coefficient can reflect the power-generating efficiency of a photovoltaic system in operation. But the inaccurate prediction on meteorological information brings challenges to the prediction on the maximum daily photovoltaic output coefficient. To overcome the problem，an envelope is constructed based on the maximum and minimal daily photovoltaic output coefficients which are calculated every 7 days. The upper and lower limits of the envelope provide a range of the factor. The envelope can overcome the uncertainties of meteorological information， so as to facilitate the prediction to be more robust and reliable. The Informer model employed as the prediction framework in this study is compared with Transformer， LSTM， and RNN models. A simulation test is carried out on a data sequence of actual electric loads and the upper and lower bounds of the photovoltaic output coefficients' envelope. The results validate the feasibility and outstanding prediction accuracy of the Informer model.

Research on multi-path balancing topology based on transformers

CHEN Yang, WENG Weijie, HUANG Jiangdong, ZOU Tao, JIANG Wei

2024, 46(4): 68-77. doi:10.3969/j.issn.2097-0706.2024.04.009

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With the upgrade of the voltage level and power level of energy storage systems，the number of cells in a series-connected battery pack increases，making the imbalance between battery packs more complex. Therefore，a transformer-based direct equalization topology for multi-path series-connected battery packs is proposed. The topology，which uses a transformer as the energy transfer carrier，is able to switch between Buck-Boost mode and flyback mode. By controlling a low-conduction bi-directional switching array， the topology structure can achieve equalization between any battery cells. This topology is of multiple equalization modes，flexible equalization paths and fast equalization speed. In order to distribute energy effectively and achieve equalization efficiently，a fuzzy control strategy with State of Charge（SOC）as its equalization index is designed. Finally，a series of simulation experiments are carried out to verify the effectiveness of the proposed topology and its control strategy under different working conditions. The results show that the proposed balancing topology and control strategy have good effects in overcoming the inconsistency between single cells in a battery pack. This study is of great significance for improving the capacity difference between the battery cells， the capacity utilization rate of the energy storage system and the service life of the battery pack.

Effectiveness evaluation on energy trading systems taking blockchain technology

WANG Yongli, WANG Yanan, MA Ziben, QIN Yumeng, CHEN Xichang, TENG Yue

2024, 46(4): 78-84. doi:10.3969/j.issn.2097-0706.2024.04.010

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Clean energy-based distributed energy has become an important part of China's energy transition and new power system construction. Since traditional energy transactions mostly take single trading mode and centralized operation and management mode， the demands for decentralized energy system transactions can hardly be met. Blockchain，an emerging technical means， is suitable for distributed energy systems in solving the existing problems of new energy trading， due to the decentralization， tamper-proof and other technical characteristics of the technology. Based on this， a new energy transaction process based on blockchain technology is proposed. Business models are divided into three categories： smart energy integration， smart energy hosting and regional shared energy. Energy transaction services can be partitioned into three categories： operation and maintenance management service， system transformation service and market service. The evaluation index system for energy trading systems taking blockchain technology is constructed， and the trading system is analyzed by Analytic Hierarchy Process（AHP）-fuzzy comprehensive evaluation method. According to the results of the simulated case， the effectiveness of the evaluation index system for energy trading systems taking blockchain technology is proven.

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