This review provides the state of the art of energy management systems (EMS) and organizational structures of prosumers. Integration of renewable energy sources (RES) into the household brings new challenges in optimal operation, power quality, participation in the electricity market and power system stability. A common solution to these challenges is to develop an EMS with different prosumer organizational structures. EMS development is a multidisciplinary process that needs to involve several aspects of observation. This paper provides an overview of the prosumer organizational and control structures, types and elements, prediction methods of input parameters, optimization frameworks, optimization methods, objective functions, constraints and the market environment. Special attention is given to the optimization framework and prediction of input parameters, which represents room for improvement, that mitigate the impact of uncertainties associated with RES-based generation, consumption and market prices on optimal operation.

This paper presents a method for finding an optimal photovoltaic (PV) system according to Croatian legislation. The PV sizing model, in which a decision on investment is made according to economic indicators, is made using MATLAB Software. Based on the input data, the monthly PV system production is calculated, and electricity price formed. According to the PV system production and electricity price, economic indicators are calculated and obtained as output data. The model input data are solar irradiation, load diagram, PV system costs and market price of electricity while the model output data are PV system production, savings, profit, incomes, Net Present Value (NPV) and Levelized Cost of Electricity (LCOE). The obtained economic indicators are presented graphically and used for decision making on an optimal PV system size. The presented model is applied and presented in a case study.

The paper presents an optimized off-grid photovoltaic (PV)-wind battery model that considers the value of loss of load probability (LOLP). The optimum combination of all model components: wind turbines, PV panels, batteries and electrical load for the City of Osijek using MATLAB software is defined. The examined data are based on measured load values for the residential home. For values of LOLP in the range from 0.00 to 0.10 in steps of 0.01, optimal size of the presented system has been determined. In order to determine the optimal model, investment costs were taken into account in comparison with various LOLP values.

One of the important goals of the EU is to ensure a secure, sustainable, and competitive energy system that is less dependent on external energy supply. Greater independence is planned to be achieved by diversifying energy sources, as well as investing in renewables and energy efficiency. One of the mechanisms is the demand response (DR) that provides a high level of energy independence for the consumer. In this paper, we explore perspectives of the development of DR with a mediating effect of the independent aggregators from an EU member state standpoint. We use a hybrid research methodology that combines instruments of strategic analysis, i.e., PESTLE framework and SWOT analysis, along with the integrated risk management framework in order to identify, evaluate and rank prominent risks to which this initiative is exposed. Interdependencies between the identified risk factors are also included and efficient mitigation measures are proposed. The findings of this exploratory research are aimed at developing the policies and strategies for the aggregators’ development in the medium term. The most emphasized risks detected in analysis are the investment risk, the legal risk, the risk of substitute technologies, the consumer behavior risk, the risk of opportunistic behavior and the risk of entry barriers.