This disclosure is related to heat energy management within metal casting facilities.
The statements in this section merely provide background information related to the present disclosure. Accordingly, such statements are not intended to constitute an admission of prior art.
Metal casting plants use heat to melt metal ingots, chips, and other solid forms, to provide molten metal that is transferred to casting locations. The molten metal is transported to casting locations for molding into a final part. The melting process generates waste heat. Casting plants (i.e., foundries) can be complex industrial facilities that include equipment and processes that demand heating and cooling. This demand for heat energy can be satisfied in part by utilizing the waste heat from the melting process, thus increasing overall energy efficiency of the casting plant.
A metal casting plant including a plurality of modular melting furnaces is described. A method for managing heat energy in the metal casting plant includes executing a local control optimization model to control mass of solid metal charges to each modular melting furnace. The local control optimization model is configured to achieve a commanded total mass of molten material and coincidentally minimize waste heat for each of the modular melting furnaces. The method for managing heat energy in the metal casting plant further includes executing a system control optimization model to manage operation of a heat energy recovery system. The system control optimization model is configured to manage the operation of the heat energy recovery system including transferring the waste heat from the modular melting furnaces to a plurality of heat demand centers while minimizing total loss of the waste heat in the metal casting plant.
One or more embodiments will now be described, by way of example, with reference to the accompanying drawings, in which:
Referring now to the drawings, wherein the showings are for the purpose of illustrating certain exemplary embodiments only and not for the purpose of limiting the same,
The modular metal melting furnace 10 is subject to an optimization process that manages the metal charges 21, 22, 23, and 24 to achieve the preferred molten metal charge 25 that meets a molten metal demand from casting production in the metal melting furnace 10. The optimization process is subject to a limitation of minimizing the generated waste heat 15. The optimization process has the following objective function in EQ. 1:
wherein
The objective function set forth in EQ. 1 is subject to the constraint that the sum of the solid metal from the metal charges 21, 22, 23, and 24 at time t must be at least equal to the preferred total molten metal charge 25 at time t, represented as follows in EQ. 2:
The preferred decision variable is Xit. Thus the solution set indicates the mass of solid metal for each of the metal charges 21, 22, 23, and 24 at time t.
In one embodiment, linear programming is employed to minimize the objective function set forth in EQ. 1 subject to the constraint set forth in EQ. 2 to determine the mass of metal for each of the metal charges 21, 22, 23, and 24 at time t, thus minimizing the generated waste heat 15 while meeting the production schedule using the preferred molten metal charge 25 that meets the total demand for molten metal at time t to achieve casting production for the specific modular metal melting furnace 10.
The generated waste heats 115, 125, and 135 from the modular metal melting furnaces 110, 120, 130 are distributed to a plurality of usage distribution centers, including space heating indicated by node 210, space cooling indicated by node 220, process heating indicated by node 230, and process cooling indicated by node 240. The usage distribution centers have integrated energy conversion processes or devices to convert waste heat energy in the form of hot gases into another form of energy as dictated by process demand requirements. Heat exchangers and absorption chillers are examples of such devices. Other usage distribution centers may be employed depending upon the configuration of the heat energy recovery system 200. The distribution of the generated waste heat 115, 125, and 135 to the plurality of usage distribution centers indicated by nodes 210, 220, 230, and 240 has accompanying heat losses that are indicated by arcs 141, 142, 143, 151, 152, 153, 154, 161, 162, and 163. The usage distribution center employing the aforementioned arcs is illustrative. Other configurations of arcs may be employed.
Heat transfers from the nodes 210, 220, 230, and 240 to a plurality of heat demand centers indicated by nodes 250, 260, 270, and 280. The heat demand centers have integrated energy conversion processes or devices to convert waste heat energy in the form of hot gases into another form of energy as dictated by process demand requirements. Heat exchangers and absorption chillers are examples of such devices. Each distribution from the usage distribution centers indicated by nodes 210, 220, 230, and 240 to the heat demand centers indicated by nodes 250, 260, 270, and 280 has accompanying heat losses that are indicated by arcs 211, 221, 231, 232, 233, 241, 242, and 243. Each of the heat demand centers indicated by nodes 250, 260, 270, and 280 represents a piece of equipment or a process that has one or more demands for heat, including heat demand 251 associated with node 250, heat demand 261 associated with node 260, heat demands 273, 275, and 277 associated with demand centers 272, 274, and 276, respectively, of node 270, and heat demands 283, 285, and 287 associated with demand centers 282, 284, and 286, respectively, of node 280. In one embodiment, the heat demand center indicated by node 250 is associated with space heating, the heat demand center indicated by node 260 is associated with space cooling, the heat demand center indicated by node 270 is associated with process heating, and the heat demand center indicated by node 280 is associated with process cooling. Alternative configurations of usage distribution centers and heat demand centers may be employed with similar effect.
The heat energy recovery system 200 is subject to an optimization process that is employed to manage transfer of the generated waste heat therethrough.
The optimization process may be configured with an objective function as follows in EQ. 3.
wherein
The preferred decision variables include Xijt, i.e., the quantities of heat from the modular melting furnaces 115, 125, and 135 delivered to the intermediate nodes, and Yjkt, i.e., the quantities of heat delivered from the intermediate nodes j, i.e., one of the usage distribution centers indicated by nodes 210, 220, 230, and 240 to the heat demand centers k at time t.
The objective function set forth in EQ. 3 is subjected to a waste heat generation constraint, as follows in EQ. 4:
Thus at each time point including a planning horizon, the solution to EQ. 3 is subject to the limitation that a total quantity of generated waste heat 115, 125, and 135 at time t delivered from the modular metal melting furnaces 110, 120, 130 does not exceed its supply at time t dictated by the production schedule.
Operation of the system includes a constraint to ensure that the heat demands 251, 261, 273, 275, 277, 283, 285, and 287 are satisfied from the heat demand centers indicated by nodes 250, 260, 270, and 280 at each time t, indicated as follows in EQ. 5.
wherein
Thus for each time t in the planning horizon, the solution to EQ. 3 is subject to the limitation that the demand of each demand node is fulfilled for all time points in the planning horizon.
Operation of the system includes an individual node heat balance constraint, which ensures that the total heat delivered into an intermediate node is equal to the total heat delivered from that node to subsequent demand nodes indicated as follows in EQ. 6.
Thus, at each time t including a planning horizon, the solution to EQ. 3 is subject to a heat balance constraint, which ensures that the total heat delivered into an intermediate node is equal to the total heat delivered from that node to subsequent demand nodes.
In one embodiment, linear programming is employed to minimize the objective function set forth EQ. 3 subject to the constraints set forth in EQs. 4, 5, and 6 to determine the quantities of heat from the modular metal melting furnaces 110, 120, 130 delivered to the intermediate nodes j, i.e., one of the usage distribution centers indicated by nodes 210, 220, 230, and 240 at time t and the quantity of heat delivered from the intermediate nodes j, i.e., the usage distribution centers indicated by nodes 210, 220, 230, and 240 to the demand nodes k at time t.
Execution of the local control optimization model set forth in EQ. 1 and the system control optimization model set forth in EQ. 3 to control operation of the heat energy recovery system 200 minimizes operational heat energy consumption while satisfying production requirements under different operating schedules. The operating schedules may include full production, partial production, and non-production. A control system employing the local control optimization model set forth in EQ. 1 and the system control optimization model set forth in EQ. 3 is able to control the diversion of heat in the form of high temperature exhaust gases from a gas turbine to various process and facility loads, thus providing operational flexibility for multiple recovery options. This facilitates use of small, modular cogeneration applications that are physically proximal to process and facility heat loads. Furthermore, natural gas-driven turbine generators produce less CO2 than other known electric generating units, thus allowing emissions reduction. When the waste heat is fully utilized, this will serve to reduce energy usage.
The disclosure has described certain preferred embodiments and modifications thereto. Further modifications and alterations may occur to others upon reading and understanding the specification. Therefore, it is intended that the disclosure not be limited to the particular embodiment(s) disclosed as the best mode contemplated for carrying out this disclosure, but that the disclosure will include all embodiments falling within the scope of the appended claims.
Number | Name | Date | Kind |
---|---|---|---|
20030074900 | McFarland | Apr 2003 | A1 |
20070055392 | D'Amato | Mar 2007 | A1 |
20080014537 | Atreya | Jan 2008 | A1 |
20080267249 | Della Vedova et al. | Oct 2008 | A1 |
20100255437 | Gibson | Oct 2010 | A1 |
20100319348 | Jones et al. | Dec 2010 | A1 |
20120320941 | Wakahara et al. | Dec 2012 | A1 |
Entry |
---|
The U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy, A BestPractices Process Heating Technical Brief: Waste Heat Reduction and Recovery for Improving Furnace Efficiency, Productivity and Emissions Performance, 2004. |
Number | Date | Country | |
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20130268105 A1 | Oct 2013 | US |