Integration of storage and renewable energy into district heating systems: A review of modelling and optimization. (15th October 2016)

• Record Type: Journal Article
• Authors: Olsthoorn, Dave; Haghighat, Fariborz; Mirzaei, Parham A.
• Is Part Of: Solar energy. Volume 136(2016)
• Page Start: 49
• Page End: 64
• Publication Date: 2016-10-15
• Subjects: CPEA clustering pareto evolutionary algorithm -- DHS district heating system -- DH district heat -- DHW domestic hot water -- CHP combined heat and power -- GHG green-house gas -- COP coefficient of performance -- GDHS geothermal district heating systems -- HOB heat-only boilers -- MSW municipal solid waste -- LSDHS large-scale district heating systems -- LTDHS low temperature district heating systems -- SH space heating -- DDM degree-day method -- ANN artificial neural network -- SVR support vector regression -- SPECO specific exergy and cost method -- MILP mixed integer linear programming -- MINLP mixed integer non-linear programming -- NSGA non-dominated sorting genetic algorithm -- GIS geographic information system -- O&M operation and management -- RE renewable energy -- BIGCC CHP biomass integrated gasification combined cycle combined heat and power plant -- GA-ANFIS hybrid genetic algorithm adaptive network-based fuzzy inference system -- MRA-ANN multi resolution analysis artificial neural network -- CFB circulation fluidised bed combustion -- CCGT CHP combined-cycle gasification turbine combined heat and power plant -- NGCC CHP natural gas combined-cycle combined heat and power plant -- APF advanced pulverised fuel -- WtE waste to energy and -- TSP thermal solar plant -- 3GDHS third generation district heating system -- 4GDHS fourth generation district heating system; District heating -- Optimization -- Energy -- Renewable -- Sustainability -- Modelling; Solar energy -- Periodicals; Solar engines -- Periodicals; 621.47
• DOI: 10.1016/j.solener.2016.06.054
• Languages: English
• ISSNs: 0038-092X

Abstract

Highlights: District heating systems (DHS) is a promising technology to address sustainability in buildings. Modelling methods were discussed in terms of computation, precision and degree of output certainty. DHS are classified in terms of optimization objectives. Research limitations were summarized and future research directions were proposed. Abstract: The building and infrastructure sector is accountable for 46% of the total worldwide energy consumption. Most traditional energy sources such as coal or petroleum are among the non-renewable types and most likely to be depleted in the forthcoming decades. To address the current energy crisis, use of renewable energy such as solar sources and a considerable increase in energy efficiency are proposed as the potential solutions. District heating systems (DHS), in particular, has recently received more attention due to several advantages in energy production, distribution and consumption for the space heating. This paper reviews the recent advancements in the energy production, modelling and optimization of the DHSs. A classification of energy sources is presented in terms of their sustainability and ease of integration to a DHS. Current modelling methods are further compared with respect to computational limitations, level of precision as well as the degree of certainty in the output level. Moreover, the recent studies of DHS are classified in accordance with the optimization objectives, including energy/exergy efficiency, cost, exergo-economic/thermo-economic and green-house gas (GHG) and pollutant production.