沼氣發(fā)電機組：跨周期智能優(yōu)化，發(fā)電量提升 14.66%，破解北方低溫產(chǎn)沼瓶頸

　　Biogas generator set: cross cycle intelligent optimization, power generation increased by 14.66%, breaking the bottleneck of low-temperature biogas production in the north

　　讓沼氣發(fā)電更"智能"：跨發(fā)酵周期優(yōu)化技術(shù)增產(chǎn)沼氣，實現(xiàn)鄉(xiāng)村生物質(zhì)能低碳高效發(fā)電

　　Making biogas power generation more "intelligent": cross fermentation cycle optimization technology to increase biogas production and achieve low-carbon and efficient rural biomass energy generation

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　　研究背景本項目基于團隊承擔的江蘇省碳達峰碳中和科技創(chuàng)新專項資金(重大科技示范)項目開展相關研究，經(jīng)項目現(xiàn)場實地考察發(fā)現(xiàn)，在我國北方地區(qū)，冬季低溫常常導致沼氣工程"休眠"，夏季高溫又造成能源浪費。傳統(tǒng)方法難以應對全年溫差挑戰(zhàn)，現(xiàn)有增溫模式能耗高且缺乏精準量化。如何實現(xiàn)增溫能耗與發(fā)電產(chǎn)出最優(yōu)平衡，讓沼氣發(fā)電系統(tǒng)"知冷知熱"，成為提升生物質(zhì)能利用效率的關鍵難題。

　　Research Background: This project is based on the Jiangsu Province Carbon Peak and Carbon Neutrality Science and Technology Innovation Special Fund (Major Science and Technology Demonstration) project undertaken by the team to conduct relevant research. Through on-site inspections of the project, it was found that in northern China, low temperatures in winter often lead to the "dormancy" of biogas projects, while high temperatures in summer cause energy waste. Traditional methods are difficult to cope with the challenge of annual temperature differences, and existing warming modes have high energy consumption and lack precise quantification. How to achieve the optimal balance between heating energy consumption and power generation output, and make the biogas power generation system "know the cold and know the heat", has become a key challenge to improve the efficiency of biomass energy utilization.

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　　論文解決問題及意義本研究針對鄉(xiāng)村綜合能源系統(tǒng)面臨的低溫環(huán)境下沼氣產(chǎn)量嚴重受限，解決以下難題：1）增溫措施能耗與增產(chǎn)效益的動態(tài)關系難以量化。2）長期運行中環(huán)境溫度波動對沼氣發(fā)酵存在顯著影響。為此，本研究本文提出變溫影響下鄉(xiāng)村生物質(zhì)能發(fā)電系統(tǒng)跨周期滾動優(yōu)化運行方法。首先，精確建模生物質(zhì)物料預處理、厭氧消化產(chǎn)沼、沼氣凈化與貯存、沼氣發(fā)電及余熱回收、增溫助產(chǎn)等環(huán)節(jié)，提出精準量化助產(chǎn)能耗與發(fā)電增量的鄉(xiāng)村生物質(zhì)能產(chǎn)沼及發(fā)電優(yōu)化模型；其次，考慮環(huán)境不確定性因素對厭氧消化產(chǎn)沼效率的影響，針對跨多個水力停留周期下的助增方式及運行變量難以決策的問題，提出一種跨周期的滾動優(yōu)化運行方法，以最近一個水力停留周期為控制域，滾動時窗后移更新環(huán)境溫度、太陽輻射等變量數(shù)據(jù)，以年運行總發(fā)電量最大為目標，生成跨周期鄉(xiāng)村生物質(zhì)能發(fā)電系統(tǒng)滾動優(yōu)化運行方案。

　　This study aims to address the severe limitation of biogas production in low-temperature environments faced by rural integrated energy systems, and to solve the following challenges: 1) The dynamic relationship between energy consumption and yield benefits of warming measures is difficult to quantify. 2) The fluctuation of environmental temperature during long-term operation has a significant impact on biogas fermentation. Therefore, this study proposes a cross cycle rolling optimization operation method for rural biomass power generation systems under the influence of temperature changes. Firstly, accurately model the processes of biomass material pretreatment, anaerobic digestion biogas production, biogas purification and storage, biogas power generation and waste heat recovery, and warming assisted delivery, and propose a rural biomass biogas production and power generation optimization model that accurately quantifies the energy consumption and power generation increment of assisted delivery; Secondly, considering the impact of environmental uncertainty factors on anaerobic digestion and biogas production efficiency, a cross cycle rolling optimization operation method is proposed to address the problem of difficulty in decision-making on boosting methods and operating variables across multiple hydraulic retention cycles. The method uses the most recent hydraulic retention cycle as the control domain, updates variables such as environmental temperature and solar radiation with a rolling time window, and generates a rolling optimization operation plan for the cross cycle rural biomass energy generation system with the goal of maximizing the total annual power generation.

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　　論文重點內(nèi)容1）綜合考慮消化罐所受太陽輻射、余熱回收、罐體結(jié)構(gòu)間熱傳導等多重熱傳遞，進行沼氣制備過程與發(fā)電環(huán)節(jié)耦合的精準建模，采用沼氣發(fā)電余熱回收設備與蓄熱式電鍋爐協(xié)同控制，形成靈活控溫的沼氣產(chǎn)出與發(fā)電綜合生產(chǎn)模式，實現(xiàn)增發(fā)電量與消耗能量的差值最大，有效提高輸出發(fā)電量。圖1  產(chǎn)沼率與溫度關系分段線性化2）針對鄉(xiāng)村生物質(zhì)發(fā)電系統(tǒng)跨多個水力停留周期長時間運行所面臨的環(huán)境變化與不確定性因素，以厭氧消化水力停留周期為滾動步長，利用預測域內(nèi)數(shù)據(jù)的更新對剩余時刻進行優(yōu)化調(diào)度，實現(xiàn)變溫影響下的鄉(xiāng)村生物質(zhì)能發(fā)電系統(tǒng)跨周期滾動優(yōu)化運行。

　　Key content of the paper: 1) Taking into account multiple heat transfers such as solar radiation, waste heat recovery, and thermal conduction between tank structures, a precise modeling of the coupling between biogas preparation process and power generation is carried out. The biogas power generation waste heat recovery equipment is used in conjunction with a thermal storage electric boiler to form a flexible temperature control integrated production mode for biogas output and power generation, achieving the maximum difference between increased electricity generation and energy consumption, effectively improving the output power generation. Figure 1 shows the segmented linearization of the relationship between biogas production rate and temperature. 2) In response to the environmental changes and uncertainties faced by rural biomass power generation systems operating for long periods of time across multiple hydraulic retention cycles, the anaerobic digestion hydraulic retention cycle is used as the rolling step, and the remaining time is optimized and scheduled using data updates in the prediction domain to achieve cross cycle rolling optimization operation of rural biomass power generation systems under the influence of temperature changes.

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　　結(jié)論本文剖析鄉(xiāng)村生物質(zhì)能發(fā)電系統(tǒng)工藝流程，建立鄉(xiāng)村生物質(zhì)能產(chǎn)沼及發(fā)電優(yōu)化綜合模型，探究不同運行方案對沼氣發(fā)電總量的影響，充分考慮環(huán)境變化及不確定性因素，探索高效節(jié)能的運行方式，以最大總輸出電量為目標，提出鄉(xiāng)村生物質(zhì)能發(fā)電系統(tǒng)運行滾動優(yōu)化方法。該方法應用于我國北方地區(qū)及其他寒冷地區(qū)的大型奶牛養(yǎng)殖農(nóng)場能產(chǎn)生明顯效果，對于以其他生物質(zhì)為物料的沼氣工程亦有一定參考作用。本文的核心貢獻如下：1）建立鄉(xiāng)村生物質(zhì)能產(chǎn)沼及發(fā)電綜合優(yōu)化模型，精準量化鄉(xiāng)村生物質(zhì)的物料轉(zhuǎn)換及沼氣發(fā)電中的能量轉(zhuǎn)換與物質(zhì)流動。2）能夠根據(jù)不斷更新的環(huán)境變化情況對設備出力進行滾動優(yōu)化，使系統(tǒng)能更好地適應鄉(xiāng)村復雜場景下環(huán)境溫度、太陽輻射變化與不確定性。3）通過合理決策設備出力，使總電量產(chǎn)出與能耗的差值最大，生成全水力停留周期下鄉(xiāng)村生物質(zhì)能發(fā)電系統(tǒng)運行方案，應用于年產(chǎn)沼量兩百萬立方米以上的大型奶牛牧場生物質(zhì)發(fā)電系統(tǒng)能使全周期發(fā)電總量相較原始方法增大607.25MWh，提高14.66%以上。

　　Conclusion: This article analyzes the process flow of rural biomass energy power generation system, establishes a comprehensive model for rural biomass energy biogas production and power generation optimization, explores the impact of different operation schemes on the total amount of biogas power generation, fully considers environmental changes and uncertainty factors, explores efficient and energy-saving operation modes, and proposes a rolling optimization method for rural biomass energy power generation system operation with the goal of maximum total output electricity. This method can produce significant results when applied to large-scale dairy farms in northern and other cold regions of China, and also has certain reference value for biogas engineering using other biomass materials. The core contributions of this article are as follows: 1) Establishing a comprehensive optimization model for rural biomass energy production and power generation, accurately quantifying the material conversion of rural biomass and the energy conversion and material flow in biogas power generation. 2) Being able to roll optimize equipment output based on constantly updated environmental changes, enabling the system to better adapt to changes and uncertainties in environmental temperature and solar radiation in complex rural scenarios. 3) By making reasonable decisions on equipment output, the difference between total electricity output and energy consumption can be maximized, and a rural biomass power generation system operation plan under full hydraulic retention period can be generated. This plan can be applied to a large-scale dairy farm biomass power generation system with an annual biogas production of more than two million cubic meters, which can increase the total power generation of the entire period by 607.25 MWh compared to the original method, an increase of more than 14.66%.

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