蓄热式热电联产电厂的产能优化

Elnaz Abdollahi, Haichao Wang, S. Rinne, R. Lahdelma
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引用次数: 30

摘要

热电联产(CHP)是一种非常有效的技术,在一个综合过程中产生电力和热量。在热电联产电厂中,热电联产具有共同的特点,这意味着这两种产品的生产计划必须协调进行。每小时生产的电力可以以市场价格出售给电网,但必须生产热量来满足当地的区域供热需求或特定工业过程的热量。通常,热电联产系统的最有利可图的操作可以通过使用优化模型来规划。利用储能装置可以进一步提高热电联产电厂的高效率和盈利能力。蓄热装置使每小时产生的热量完全符合当地需求的限制得以放松。这允许通过在低需求时储存热量和在需求高时排放热量来更便宜地满足可变的热量需求。通过放松供热和发电之间的联系,蓄热也可以在现货价格高的时候向电力市场提供更多的电力,在现货价格低的时候减少发电量。本研究的目的是开发一个模型,以优化热电联产电厂与蓄热装置的运行。该模型是一个线性规划(LP)模型,由小时模型与动态存储约束连接而成。目标是最小化生产(燃料)成本减去向市场出售电力的收入。该模型使用修改后的芬兰城市真实数据进行了演示。研究结果对电厂的高效运行规划具有指导意义。该模型还可以用于确定存储的最佳大小。
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Optimization of energy production of a CHP plant with heat storage
Combined heat and power (CHP) production is a very efficient technique to produce power and heat in an integrated process. In CHP plants, generation of heat and power follows a joint characteristic, which means that production planning of both commodities must be done in coordination. The hourly produced power can be sold to the grid at market price, but heat must be produced to meet the local demand of district heating or heat for specific industrial processes. Typically, the most profitable operation of a CHP system can be planned by using an optimization model. The high efficiency and profitability of CHP plants can be further improved by utilization of energy storage units. Heat storages make it possible to relax the constraint to produce heat each hour to exactly match the local demand. This allows satisfying the variable heat demand more cheaply by storing heat during low demand and discharging heat when demand is high. By relaxing the connection between heat and power production, heat storages also allow producing more electricity to the power market when the spot price is high and reducing the power generation when spot price is low. The aim of this study is to develop a model for optimizing the operation of a CHP plant together with a heat storage. The model is a linear programming (LP) model consisting of hourly models connected together with dynamic storage constraints. The objective is to minimize the production (fuel) costs subtracted by revenue from selling power to the market. The model is demonstrated using modified reallife data of a Finnish city. The results are useful for planning efficient operation of the plant. The model can also be adapted for determining the optimal size of the storage.
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