Design analysis of gas engine combined heat and power plants (CHP) for building and industry heat demand under varying price structures
Design analysis of gas engine combined heat and power plants (CHP) for building and industry heat demand under varying price structures
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DOI：
10.1016/j.energy.2017.02.113
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发表时间：
2017-04
期刊：
影响因子：
9
通讯作者：
Philipp Vögelin;Gil Georges;K. Boulouchos
中科院分区：
文献类型：
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作者：
Philipp Vögelin;Gil Georges;K. Boulouchos
基于燃气发动机的热电联产（CHP）电厂的总体效率为90%，响应时间不到2分钟，每天可多次启动，并可作为分散式发电机部署。在设备和散热器之间的解耦储热装置可以提高操作灵活性，但增加了投资成本。针对时间依赖性电价的工厂和存储的成本最佳规模是一个不平凡的优化问题。在这项研究中，我们研究如何优化设计取决于各种边界条件。我们扫描住宅和工业用热需求曲线（5 kW-100 MW峰值），电价水平和方差以及燃料价格。我们配对一个线性电厂模型与散热器和价格组合，并使用一个快速的启发式算法，以找到功率，存储大小和运行模式，最大限度地提高年利润超过8760小时。在今天的现货市场价格（燃料0.08€/kWh）上，实现了0.03-0.14€/kWh的盈余。发电厂≥ 1 MW功率的设计结果相似。未来的最佳设计比现在的大30%，利润也会增加。由于平坦最优，该设计通常对预期价格变化具有鲁棒性。研究结果为当前和未来的经济型电厂设计提供了有价值的依据。
Combined heat and power (CHP) plants based on gas engines feature overall efficiencies of 90%, response times of less than 2 min, tolerate multiple starts per day and can be deployed as decentralised generators. A decoupling heat storage device between the plant and the heat sink can improve operation flexibility, but increases investment costs. The cost-optimal sizing of plant and storage against time dependent electricity prices is a non-trivial optimisation problem. In this study, we investigate how the optimal design depends on various boundary conditions. We sweep residential and industrial heat demand profiles (5 kW–100 MW peak), electricity price levels and variance and fuel prices. We pair a linear plant model with heat sink and price combinations and use a fast heuristic algorithm to find power, storage size and operating pattern for maximised annual profit over 8760 h. Brake-even is reached with a surplus of 0.03–0.14€/kWh on today's spot market price (fuel 0.08€/kWh). Design results for plants≥ 1 MW power are similar. Future optimal designs are up to 30% larger than today's and profits increase. The design is generally robust on expected price changes due to the flat optimum. The results provide a valuable basis for designing profitable plants today and in future.