An Optimal Dispatch Framework of Electric and Heating Networks Based on Controllable Electric and Thermostatically Controlled Loads

With the increasing capacity of wind power generators (WTGs), the volatility of wind power could significantly challenge the stability and economy of electric and heating networks. To tackle this challenge, this paper proposes an optimal dispatch framework based on controllable load (including controllable electric load and controllable thermostatically load) to reduce wind power curtailment. A forecasting model is developed for the controllable load, which comprehensively considers autocorrelation, weather factor, and consumers’ behavior characteristics. With adjusting controllable load, an optimal dispatch model of power system is then established and resolved by Sequential Least Squares Programming (SLSQP) method. Our method is verified through numerous simulations. The results show that, compared with the state-of-the-art techniques of support vector machine and recurrent neural networks, the root mean square error with the proposed long short-term memory can be reduced by 0.069 and 0.044, respectively. Compared with conventional method, the peak wind power curtailment with dispatching controllable load is reduced by nearly 10% and 5% in two cases, respectively.

Method of detection of district heating pipe network leakage using data monitoring of heat energy consumers

Currently, information systems to get data of metering devices are introduced to calculate the consumed thermal energy. The metering devices are installed at the thermal station of the consumers. However, the processing of these data is usually limited to the monthly data collection to calculate the payments and to monitor the output of the observed parameters beyond the established boundaries. The urgent issue is the possibility to use these data for the in-depth study of the processes, and, in particular, to detect district heating pipe network leakage. The authors have used both the methods and tools to model and analyze the operating modes of district heating pipe networks, methods to collect and monitor data of heat supply metering devices, methods to model district heating pipe networks in the geoinformation systems environment. The authors have proposed the method to detect the sections of the heat network where a heat medium leak has occurred. The difference of the method is the use only of the readings of the metering devices installed at consumers. The limitations of the application of the method and its implementation in geoinformation system environment are considered. An example is given to illustrate the possibility to detect the location of leakage based on the analysis of real data of the house heat metering devices collected during leakage and leakage elimination. Practical application of the developed method is discussed by the example of a real situation of leakage at the section of the heat network of the ISPU boiler house. The results obtained have confirmed the possibility to detect localization of leakage in heating networks based on the analysis of meter readings installed at consumers. The developed method can be applied in information systems to monitor the operating modes of district heating networks to search the places of accidents.

Lessons Learnt from Substation Inspection on Low Temperature District Heating Networks

District heating networks are considered to be a key element for the decarbonization of Europe. The RELaTED project seeks to contribute to the decarbonization of these infrastructures with the demonstration of low temperature district heating networks. One of the demonstration sites consists of more than 50 substations within a subsection of a larger network in the city of Tartu (Estonia), where the temperature was lowered by 10 °C. To ensure the benefits of this new generation district heating network and the fulfillment of comfort requirements, data have been monitored and analyzed at the substation level in an automatic way to facilitate the inspection of every user.

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

The aim of the ISORC/OPTIMISER project is to increase and improve the use of solar thermal energy in district heating networks. One of the main tasks of the project is to develop an optimization tool for the sizing and operation of a solar district heating network. This is the first optimization tool using an open-source interface (Julia, JuMP) and solver (Ipopt) to solve nonlinear problems. This paper presents the multi-period optimization problem which is implemented to consider the dynamic variations in a year, represented by four typical days, with an hourly resolution. The optimum is calculated for a total duration of 20 years. First, this paper presents the modeling of the different components of a solar district heating network production plant: district network demand, storage and three sources, i.e., a fossil (gas) and two renewable (solar and biomass) sources. In order to avoid prohibitive computational time, the modeling of sources and storage has to be fairly simple. The multi-period optimization problem was formulated. The chosen objective function is economic: The provided economic model is accurate and use nonlinear equations. Finally the formulated problem is a nonlinear Programming problem. Optimization of the studied case exhibits consistent operating profiles and design. A comparison is made of different types of storage connection at the production site, highlighting the relevance of placing the storage at the solar field outlet. The optimum configuration supplies 49% of demand using solar energy, achieving a renewable rate of 69% in combination with the biomass boiler.

Energy Efficiency of DH System with Wood Chips Boiler Houses and Flue Gas Condensing Unit

This study proposes a method for the evaluation of the efficiency of a heat supply system based on a correlation analysis of the data of the system's operations. The data from the system's operations have been analysed and a correlation equation has been applied to obtain the results of the analysis, which are then used for further calculations. The data can be divided into two groups: data characterising the condenser operations in the boiler house, and data characterising heating networks.