• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
CHEN Weirong, FU Wangxuan, HAN Ying, LI Qi, HUANG Lanjia, XU Chengpeng. Optimal Configuration of Wind-Solar-Hydrogen Multi-Energy Complementary Microgrid with Demand Side[J]. Journal of Southwest Jiaotong University, 2021, 56(3): 640-649. doi: 10.3969/j.issn.0258-2724.20200163
Citation: CHEN Weirong, FU Wangxuan, HAN Ying, LI Qi, HUANG Lanjia, XU Chengpeng. Optimal Configuration of Wind-Solar-Hydrogen Multi-Energy Complementary Microgrid with Demand Side[J]. Journal of Southwest Jiaotong University, 2021, 56(3): 640-649. doi: 10.3969/j.issn.0258-2724.20200163

Optimal Configuration of Wind-Solar-Hydrogen Multi-Energy Complementary Microgrid with Demand Side

doi: 10.3969/j.issn.0258-2724.20200163
  • Received Date: 04 Apr 2020
  • Rev Recd Date: 17 Jun 2020
  • Available Online: 25 Aug 2020
  • Publish Date: 15 Jun 2021
  • To optimize the economic cost of multi-energy complementary microgrid, an optimal configuration method is proposed for the wind-solar-hydrogen multi-energy complementary microgrid with demand-side response. First, the operation control strategy is formulated under the relevant power constraints and control principles. Then, in order to maximize the direct consumption of wind and solar power, an incentive demand-side response is introduced, and the mixed integer programming is used to optimize the load curve. Further the optimal configuration model with the demand-side response is established: with the minimum annual cost as the optimization goal and the requisite constraints of the system, the particle swarm optimization is used to iteratively find the optimal configuration. In order to verify the model, the historical data of a certain area is utilized to solve the optimal configuration scheme, and the technical and economic analysis is carried out under different operating modes of microgrid, the self-balance rate constraint and influencing factors of construction cost. The analysis results show that by introducing the hydrogen energy power generation system and considering the demand-side response, when the self-balancing rate is 81.64%, the minimum cost to reach the equivalent annual value is 3.143 million yuan; the self-balancing rate is controlled at a reasonable level, and the cost reduction promoted by the technology advancement will help to improve the economic benefits of the microgrid.

     

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    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 13.1 %其他: 13.1 %其他: 0.6 %其他: 0.6 %San Jose: 0.1 %San Jose: 0.1 %Seattle: 0.4 %Seattle: 0.4 %[]: 0.2 %[]: 0.2 %上海: 1.2 %上海: 1.2 %东莞: 2.1 %东莞: 2.1 %临汾: 0.2 %临汾: 0.2 %丽江: 0.2 %丽江: 0.2 %伊塔茹巴: 0.3 %伊塔茹巴: 0.3 %保定: 0.1 %保定: 0.1 %北京: 3.6 %北京: 3.6 %十堰: 0.1 %十堰: 0.1 %南京: 1.2 %南京: 1.2 %南宁: 0.2 %南宁: 0.2 %南通: 0.1 %南通: 0.1 %印多尔: 0.2 %印多尔: 0.2 %合肥: 0.6 %合肥: 0.6 %呼和浩特: 0.7 %呼和浩特: 0.7 %哈尔滨: 0.3 %哈尔滨: 0.3 %哥伦布: 0.3 %哥伦布: 0.3 %唐山: 0.2 %唐山: 0.2 %喀什: 0.2 %喀什: 0.2 %嘉兴: 0.1 %嘉兴: 0.1 %埃拉泽: 0.3 %埃拉泽: 0.3 %天津: 1.7 %天津: 1.7 %孟买: 0.2 %孟买: 0.2 %宁波: 0.2 %宁波: 0.2 %安康: 0.1 %安康: 0.1 %宜宾: 0.2 %宜宾: 0.2 %宝鸡: 0.1 %宝鸡: 0.1 %宣城: 0.3 %宣城: 0.3 %密蘇里城: 0.7 %密蘇里城: 0.7 %常州: 0.1 %常州: 0.1 %延安: 0.1 %延安: 0.1 %弗吉: 0.2 %弗吉: 0.2 %张家口: 1.6 %张家口: 1.6 %成都: 2.0 %成都: 2.0 %扬州: 0.2 %扬州: 0.2 %新乡: 0.1 %新乡: 0.1 %昆明: 0.2 %昆明: 0.2 %杭州: 1.1 %杭州: 1.1 %武汉: 0.2 %武汉: 0.2 %江门: 0.1 %江门: 0.1 %池州: 0.1 %池州: 0.1 %沈阳: 0.7 %沈阳: 0.7 %洛阳: 0.2 %洛阳: 0.2 %济南: 0.2 %济南: 0.2 %深圳: 0.7 %深圳: 0.7 %温州: 0.4 %温州: 0.4 %湖州: 0.2 %湖州: 0.2 %漯河: 0.4 %漯河: 0.4 %漳州: 0.1 %漳州: 0.1 %濮阳: 0.1 %濮阳: 0.1 %石家庄: 3.1 %石家庄: 3.1 %福州: 0.9 %福州: 0.9 %秦皇岛: 0.2 %秦皇岛: 0.2 %舟山: 0.1 %舟山: 0.1 %芒廷维尤: 15.2 %芒廷维尤: 15.2 %芝加哥: 0.6 %芝加哥: 0.6 %苏州: 0.2 %苏州: 0.2 %荆州: 0.1 %荆州: 0.1 %莫斯科: 0.1 %莫斯科: 0.1 %衡水: 0.1 %衡水: 0.1 %襄阳: 0.2 %襄阳: 0.2 %西宁: 30.6 %西宁: 30.6 %西安: 1.7 %西安: 1.7 %贵阳: 0.1 %贵阳: 0.1 %资阳: 0.1 %资阳: 0.1 %运城: 0.6 %运城: 0.6 %连云港: 0.3 %连云港: 0.3 %邯郸: 0.1 %邯郸: 0.1 %郑州: 0.1 %郑州: 0.1 %重庆: 0.4 %重庆: 0.4 %金奈: 0.2 %金奈: 0.2 %银川: 0.2 %银川: 0.2 %长春: 0.2 %长春: 0.2 %长沙: 3.6 %长沙: 3.6 %青岛: 1.2 %青岛: 1.2 %其他其他San JoseSeattle[]上海东莞临汾丽江伊塔茹巴保定北京十堰南京南宁南通印多尔合肥呼和浩特哈尔滨哥伦布唐山喀什嘉兴埃拉泽天津孟买宁波安康宜宾宝鸡宣城密蘇里城常州延安弗吉张家口成都扬州新乡昆明杭州武汉江门池州沈阳洛阳济南深圳温州湖州漯河漳州濮阳石家庄福州秦皇岛舟山芒廷维尤芝加哥苏州荆州莫斯科衡水襄阳西宁西安贵阳资阳运城连云港邯郸郑州重庆金奈银川长春长沙青岛

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