Adsorption cooling and desalination technologies have recently received more attention. Adsorption chillers, using eco-friendly refrigerants, provide promising abilities for low-grade waste heat recovery and utilization, especially renewable and waste heat of the near ambient temperature. However, due to the low coefficient of performance (COP) and cooling capacity (CC) of the chillers, they have not been widely commercialized. Although operating in combined heating and cooling (HC) systems, adsorption chillers allow more efficient conversion and management of low-grade sources of thermal energy, their operation is still not sufficiently recognized, and the improvement of their performance is still a challenging task. The paper introduces an artificial intelligence (AI) approach for the optimization study of a two-bed adsorption chiller operating in an existing combined HC system, driven by low-temperature heat from cogeneration. Artificial neural networks are employed to develop a model that allows estimating the behavior of the chiller. Two crucial energy efficiency and performance indicators of the adsorption chiller, i.e., CC and the COP, are examined during the study for different operating sceneries and a wide range of operating conditions. Thus this work provides useful guidance for the operating conditions of the adsorption chiller integrated into the HC system. For the considered range of input parameters, the highest CC and COP are equal to 12.7 and 0.65 kW, respectively. The developed model, based on the neurocomputing approach, constitutes an easy-to-use and powerful optimization tool for the adsorption chiller operating in the complex HC system.

In the article, the method and algorithm for a control strategy of the operation of a micro combined heat and power (mCHP) unit and for reducing the power consumption peaks (peak shaving) are proposed and analyzed. Two scenarios of the mCHP’s operation, namely with and without the control strategy, are discussed. For calculation purposes, a boiler fired with wood pellets coupled with a Stirling engine, manufactured by ÖkoFEN, was used. These results were used to analyze two scenarios of the control strategy. In this study, the operation of mCHP was simulated using the energyPRO software. The application of this control strategy to dispersed mCHP systems allows for a very effective “peak shaving” in the local power grid. The results of calculation using the new algorithm show that the electricity generated by the mCHP system covers the total demand for power during the morning peak and reduces the evening peak by up to 71%. The application of this method also allows for a better reduction of the load of conventional grids, substations, and other equipment.

Modern distribution grids may suffer problems of voltage distortion, especially along radial low-voltage feeders with a high penetration of intermittent, unbalanced and distorted loads and generation sources. It is a challenge to develop an effective voltage-regulation method using a straightforward implementation. This paper proposes a novel method for local voltage control and balancing using a shunt-connected energy storage system. The compensation principles are explained, and a complete controller design is proposed. The algorithm is designed to be implemented in power electronic converters that provide the interface between the storage and the grid. The original contribution is the development of a low-level control method, which includes voltage balancing and a method to minimize the compensator current and is to be implemented in power electronic converters that provide the interface between the storage and the grid. The calculation of active and reactive compensator currents is explained with relation to the estimated grid impedance. The efficacy of the designed controller is verified by laboratory experiments. It is shown that voltage regulation using the proposed method is achieved with less apparent power compared to a system where only reactive power is used. The controller presents a very good dynamic response to rapid voltage variations, such as unbalanced voltage dips. The applicability and constraints of the method are discussed with respect to the present state of the art in low-voltage-grid voltage regulation.

The paper presents theoretical assumptions and implementation of the T-history method, which was used to estimate the thermal capacity and latent heat for phase change materials (PCMs). The research equipment, measurement system and obtained results were discussed. The T-history method was used to investigate the heating and cooling process of two PCMs, sold under the trade names of RT15 and RT18. Obtained results were compared with the manufacturer’s data. The analysis of the research results has led to the conclusion that the presented measurement method made it possible to perform a preliminary verification of the enthalpy–temperature dependency of the PCMs. The method can be also used for studying different commercial materials and estimating this dependency for materials of yet unknown properties.

Global modern renewable energy based on geothermal, wind, solar, and marine resources has grown rapidly over the last decades despite low energy density, intermittent supply, and other qualities inferior to those of fossil fuels. What is the explanation for this growth? The main drivers of growth are assessed using economic theories and verified with statistical data. From the neo-classic viewpoint that focuses on price substitutions, the growth can be explained by the shift from energy-intensive agriculture and industry to labour-intensive services. However, the energy resources complemented rather than substituted for each other. In the evolutionary idea, investments supported by policies enabled cost-reducing technological change. Still, policies alone are insufficient to generate the growth of modern renewable energy as they are inconsistent across countries and in time. From the behavioural perspective that is preoccupied with innovative entrepreneurs, the value addition of electrification can explain the introduction of modern renewable energy in market niches, but not its fast growth. Instead of these mono-causalities, the growth of modern renewable energy is explained by technology diffusion during the pioneering, growth, and maturation phases. Possibilities that postpone the maturation are pinpointed.