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Application of a flue gas condenser becomes a common solution for improvement of the boiler energy balance. As a result, the efficiency of the boiler becomes above 100 % in reference to the fuel lower heating value (without flue gas steam condensation). However, efficient condensation of flue gas humidity is possible at low temperature of energy recovery. The dew point of the boiler flue gas is about 50-60 ºC representing the threshold of flue gas efficient recovery and depends on the temperature of return water from the district heating network. Profound cooling of flue gas (below 40-45 ºC) is not possible by direct heat exchange between the flue gas and network return water. The presented paper considers retrofit of an existing flue gas condenser heat exchanger system by implementation of an absorption heat pump (AHP). Deep cooling of flue gas will reduce the fuel consumption and ensure mitigation of carbon emission. The lithium-bromide absorption chiller unit (ACU) with rated capacity 2.1 MW is integrated with the flue gas condenser of a natural gas-fired heat only boiler (HOB) with the purpose to increase energy recovery from flue gas. The single effect steam driven ACU was converted in AHP by the following connection: part of the return district heating flow (about 350 m 3 •h -1 ) at temperature of 40 ºC degrees was warmed up in the condenser and absorber of AHP up to 52 ºC degrees. Superheated water steam at pressure about 0.8 bar (g) with total input power of 1,5 MW was used as the energy source for the generator of AHP. Water circulated in the low temperature section of the flue gas condenser was cooled down from 28 ºC degrees to 16 ºC in the evaporator of AHP. This part of the flue gas condenser extracts from the flue gas latent energy for recovery of 2.5 MW in the condenser and absorber of AHP. The paper provides analysis of the AHP coefficient of performance (COP) for wide range of HOB power from 40 to 80 MW and for different temperatures of the network return water.

To develop an advanced control of thermal energy supply for domestic heating, a number of new challenges need to be solved, such as the emerging need to plan operation in accordance with an energy market-based environment. However, to move towards this goal, it is necessary to develop forecasting tools for short- and long-term planning, taking into account data about the operation of existing heating systems. The paper considers the real operational parameters of five different heating networks in Latvia over a period of five years. The application of regression analysis for heating load dependency on ambient temperature results in the formulation of normalized slope for the regression curves of the studied systems. The value of this parameter, the normalized slope, allows describing the performance of particular heating systems. Moreover, a heat load forecasting approach is presented by an application of multiple regression methods. This short-term (day-ahead) forecasting tool is tested on data from a relatively small district heating system with an average load of 20 MW at ambient temperature of 0 °C. The deviations of the actual heat load demand from the one forecasted with various training data set sizes and polynomial orders are evaluated for two testing periods in January of 2018. Forecast accuracy is assessed by two parameters – mean absolute percentage error and normalized mean bias error.

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