(661c) GHG Emissions Reduction By Optimizing Design and Operation of Cross-Sector Integrated Energy Systems: Civic and Industrial Sectors
- Conference: AIChE Annual Meeting
- Year: 2022
- Proceeding: 2022 Annual Meeting
- Group: Environmental Division
- Time: Thursday, November 17, 2022 - 4:12pm-4:33pm
Typically, a CCHP system operates either following the electricity load (FEL) or following the thermal load (FTL). The power generation unit (PGU) of the CCHP system generates electricity and heat by combusting natural gas, where the heat is recovered for meeting heating and cooling demands. However, the heat and electricity generated usually cannot be entirely consumed at the same time, which leads to excess or shortage in either the heat or electricity. The mismatch between the energy generation and supply can lead to the system operating supplementary energy system equipment (such as the backup boiler) or using supplementary energy resources (such as the grid electricity), which leads to higher GHG emissions and total costs.
The unbalanced heat and electricity demand and supply can also be solved by integrating multiple CCHP systems by transferring electricity and heat among entities. Each entity in the network performs both as a supplier and a consumer to dispatch excess energy to entities that face energy shortages or to receive energy from other entities when energy demands cannot be fully satisfied. To extensively balance the energy demands and supplies of the overall integrated system, entities with different energy demand patterns should be combined. For example, an integrated system can combine residential buildings and commercial buildings that have higher electricity demand than heating demand with food processing plants that require more heating than electricity, such as confectionery plants, breweries, and bakery plants. Thus, the residential and commercial buildings can transfer excess heat to the plants, while receiving surplus electricity from the plants.
Several studies have been performed on the integration of energy systems, for example, studies performed by Mehleri et al. , Li et al. , and Jing et al. . However, these studies: 1. do not consider the temperature of heating demands when modeling the heat transfer; 2. do not consider opportunities for industrial plants to switch their production volumes, thus, adjusting their heat and electricity usages based on the energy demands of other entities; 3. have not explored the relationship between the entity sizes and maximum GHG emissions reduction of the integrated operation.
To address the research gaps mentioned above, this work investigates the design and operation of the integrated systems for residential, commercial, and industrial sectors through optimization approaches. Besides capacity and the amount of heating, cooling, or electricity generated by each piece of the energy system equipment, the approach also finds the optimal industrial production volumes. The industrial processes that require heating have been differentiated as the ones that can use the transferred heat from other entities (processes at low temperatures) and the ones that cannot use the transferred heat (processes at high temperatures). Heat balances for each of the industrial processes have been developed, reflecting whether the processes can use the transferred heat to ensure feasible heat transfer among entities.
The optimal solution identifies the operation and capacity of the energy system equipment, as well as production volumes of the plants that minimize GHG emissions and annual total costs (capital costs and operation costs) of the entire integrated system. Since there is a trade-off between GHG emissions and annual total costs (ATC) of the CCHP system, Pareto fronts of the integrated system are employed to depict trade-offs between non-dominated solutions.
In this work, an integrated system with a residential building (including electric vehicles), a supermarket, a brewery, a confectionery plant, and a bakery plant has been used for case studies. Except for the supermarket, each of the entities has been assumed to have energy system equipment, as shown in Figure 1. Thus, besides natural gas, the system also utilizes solar energy to generate heating, cooling, and electricity. Since the supermarket has extremely high electricity demand for providing cooling at low temperatures, using an absorption chiller and PGU in the supermarket is not efficient. Thus, the supermarket has been assumed does not implement the PGU, absorption chiller, and heat recovery unit. The integrated system has been compared to a non-integrated system. The non-integrated system is identical to the integrated system; however, there is no energy transfer among entities.
Results of the case studies show that, under the same ATC values, the integrated system releases over 18.8% less GHG emissions. The lower GHG emissions are because, with energy transfer, operations of the PGUs in the plants are no longer limited by electricity demands (lower compared to heating demands) of the plants. The confectionery plant, the brewery, and the bakery plant operate PGUs more frequently to generate more heating used in the entities and transfer the associated excess electricity to the residential building, which has higher electricity demand. As a result, the integrated system uses 93% less natural gas for operating backup boilers and purchases over 66% less electricity from the grid compared to the non-integrated system, which further leads to lower GHG emissions.
By optimizing production volumes, GHG emissions reduction of the integrated system (compared to the non-integrated system) can be further increased by 2% compared to the integrated system with fixed industrial production volumes at average daily rates. Additionally, it has been found that when temperatures of heating processes are not differentiated, around 34% of the heat transfer is infeasible, where heat at lower temperatures is transferred to processes that require high-temperature heating.
The relationship between the sizes of entities and GHG emissions reduction achieved by the integrated system has been explored by adapting the objective function of the optimization problem and setting the sizes of entities as decision variables. The investigation intends to find whether there exists an optimal relative entity size that maximizes GHG emissions reduction of the integrated system compared to the non-integrated system. Therefore, the objective function has been changed to maximize the GHG emissions reduction percentage between the integrated system and the non-integrated system, as shown in Eq. (1). The objective function is based on the minimum GHG emissions of the integrated system and the non-integrated system, where the minimum GHG emissions for the non-integrated system can be expressed as a linear equation of entity sizes.
Case studies have been performed on the same system mentioned above, except that the entities no longer implement batteries for storing electricity. The results show that the integrated operation can reduce GHG emissions by a maximum of 17%, compared to the non-integrated system. It requires the system to combine the residential building and the supermarket with 870 electric vehicles, a bakery plant with a production volume of 5.0x103 kg/day, and a brewery that generates 2.7x103 kg product each hour. The ratio between sizes of the residential building, supermarket, electric vehicles, bakery plant, and brewery represents the optimal relative entity size, following which GHG emissions reduction benefits of the integrated operation can be maximized.
When there are requirements on sizes of specific entities that result in the optimal relative entity sizes cannot being followed, GHG emissions reduction benefits provided by the integrated operation can be lower. However, as shown in Figure 2, by optimizing the sizes of other entities, the reduction can still be maintained at a value close to 17%.
The studies show that by integrating individually operating CCHP systems, GHG emissions of the overall system can be further reduced (by 17% for the system in case studies) compared to the corresponding non-integrated system. The maximum GHG emissions reduction benefits require the integrated system to be built following the optimal relative entity sizes, optimize production volumes of industrial plants, and optimize the operation and capacity of energy system equipment. When there are requirements on the sizes of specific entities in the integrated system, by optimizing the sizes of other entities, a GHG emissions reduction close to the maximum value can still be achieved. Additionally, it is necessary to differentiate the temperature of heating demands to ensure feasible heat transfer among entities. The optimization approaches introduced make a further step in reducing GHG emissions of distributed energy systems through integrated operation.
 Mancarella P, Chicco G, Capuder T. Arbitrage opportunities for distributed multi-energy systems in providing power system ancillary services. Energy 2018;161:381â95. https://doi.org/10.1016/j.energy.2018.07.111.
 Mehleri ED, Sarimveis H, Markatos NC, Papageorgiou LG. A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level. Energy 2012;44:96â104. https://doi.org/10.1016/j.energy.2012.02.009.
 Li L, Mu H, Gao W, Li M. Optimization and analysis of CCHP system based on energy loads coupling of residential and office buildings. Appl Energy 2014;136:206â16. https://doi.org/10.1016/j.apenergy.2014.09.020.
 Jing R, Wang M, Liang H, Wang X, Li N, Shah N, et al. Multi-objective optimization of a neighborhood-level urban energy network: Considering Game-theory inspired multi-benefit allocation constraints. Appl Energy 2018;231:534â48. https://doi.org/10.1016/j.apenergy.2018.09.151.