A Comparison of Different District Integration for a Distributed Generation System for Heating and Cooling in an Urban Area

Abstract

The paper proposes a comparison of different district integration options for a distributed generation system for heating and cooling in an urban area. The system considered includes several production units located close to the users, a central unit and the district heating and cooling network which can connect all the users to each other and to a central unit, where a cogeneration system and a solar plant can be placed. Thus, each user can be regarded as isolated from the others, satisfying its energy needs by means of an autonomous production unit. Alternatively, it can be connected to the others through the district heating and cooling network. When a district heating and cooling network is included in the design option the synthesis-design and operation problems cannot be solved separately, because the energy to be produced by each production site is not known in advance, as the flows through the district heating and cooling network are not defined. This paper uses a mixed integer linear programming (MILP) methodology for the multi-objective optimization of the distributed generation energy system, considering the total annual cost for owning, operating and maintaining the whole system as the economic objective function, while the total annual CO2 emissions as the environmental objective function. The energy system is optimized for different district integration option, in order to understand how they affect the optimal solutions compared with both the environmental and economic objects.

A Review of Small–Medium Combined Heat and Power (CHP) Technologies and Their Role within the 100% Renewable Energy Systems Scenario

“…Therefore, the study highlights the potential heat sources and the match with the small and medium size, low temperature CCHP technologies that will be still of interest, even in a future scenario dominated by RE resources and massive electrification, showing that reductions in the LCOE and LCOH can be achieved through a wider integration of the thermal products. Full exploitation of the potential benefit of CHP could be reached only by means of an optimization procedure of CHP units, jointly with the DH local grids [145,146], in the considered economic and energy-demand scenarios.…”

A Dynamic Optimization Tool to Size and Operate Solar Thermal District Heating Networks Production Plants

“…The case they studied in Northern Italy demonstrated how the storage operation could allow solar energy to cover total demand. Solar thermal energy integration has also been studied in an industrial sector [28,29] using MILP approaches. This showed that, in a combined heat and power (CHP) system, the optimized solar field produced around 55% of user annual demand.…”

“…The storage is therefore broken down into 91.25 small equal volumes called V part , and we assume that storage use on one of the typical days is the same as for the other 91.25 times. The terms V hot and V cold from Equations ( 26)- (29) become V hot,part and V cold,part with V hot,part + V cold,part = V part and V total = 91.25 × V part . According to Equations ( 26)- (29), when moving from one typical day to another (i.e., from one season to another) the state of the storage at the end of a season is retained at the start of the next.…”

“…The terms V hot and V cold from Equations ( 26)- (29) become V hot,part and V cold,part with V hot,part + V cold,part = V part and V total = 91.25 × V part . According to Equations ( 26)- (29), when moving from one typical day to another (i.e., from one season to another) the state of the storage at the end of a season is retained at the start of the next.…”

“…polynomial CapEx stor = a stor V 2 stor + b stor V stor + c stor V stor (29) logarithmic CapEx stor = (a stor log(V stor ) + b stor ) V stor (30) exponential CapEx stor = a stor exp − V stor b stor + c stor V stor (31) power CapEx stor = a stor V stor b stor V stor (32) Different tests were carried out before ultimately choosing the exponential approach (31) (a stor = EUR 1918.45/m 3 , b stor = 309.77 m 3 and c stor = EUR 117.62/m 3 ) to calculate the installation costs (CapEx) while keeping a reasonable degree of precision, as can be seen in Figure 7. The exponential approach has the advantage of being able to take into account storage larger than 10,000 m 3 because the costs converge to the value of c stor .…”