Expanding the number of photovoltaic (PV) systems integrated into a grid raises many concerns regarding protection, system safety, and power quality. In order to monitor the effects of the current harmonics generated by PV systems, this paper presents long-term current harmonic distortion prediction models. The proposed models use a multilayer perceptron neural network, a type of artificial neural network (ANN), with input parameters that are easy to measure in order to predict current harmonics. The models were trained with one-year worth of measurements of power quality at the point of common coupling of the PV system with the distribution network and the meteorological parameters measured at the test site. A total of six different models were developed, tested, and validated regarding a number of hidden layers and input parameters. The results show that the model with three input parameters and two hidden layers generates the best prediction performance.
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.
The self-sufficiency of a power system is no longer a relevant issue at the electricity market, since day-to-day optimization and security of supply are realized at the regional or the internal electricity market. Research connected to security of supply, i.e., having reliable power capacities to meet demand, has been conducted by transmission system operators. Some of the common parameters of security of supply are loss of load probability (LOLP) and/or loss of load expectation (LOLE), which are calculated by a special algorithm. These parameters are specific for each power system. This work presents the way of calculating LOLP as well as the optimization algorithm of LOLP, which takes into consideration the particularities of the power system. It also presents a difference in the treatment of LOLP regarding the observed power system and the necessary installed power capacity if applied to the calculated LOLP in relation to the optimized LOLP. As a conclusion, the study analyzed the parameters impact the regional electricity market—where the participants are countries with different development levels and various particularities of power systems—i.e., what it means when the same LOLP criterion is applied to them and the optimized LOLP.
Infrared thermography, in the analysis of photovoltaic (PV) power plants, is a mature technical discipline. In the event of a hailstorm that leaves the PV system without the support of the power grid (and a significant portion of the generation potential), thermography is the easiest way to determine the condition of the modules and revive the existing system with the available resources. This paper presents research conducted on a 30 kW part of a 420 kW PV power plant, and demonstrates the procedure for inspecting visually correct modules that have suffered from a major natural disaster. The severity of the disaster is shown by the fact that only 14% of the PV modules at the test site remained intact. Following the recommendations of the standard IEC TS 62446-3, a thermographic analysis was performed. The thermographic analysis was preceded by an analysis of the I-V curve, which was presented in detail using two characteristic modules as examples. I-V curve measurements are necessary to relate the measured values of the radiation and the measured contact temperature of the module to the thermal patterns. The analysis concluded that soiled modules must be cleaned, regardless of the degree of soiling. The test results clearly indicated defective module elements that would result in a safety violation if reused. The research shows that the validity criterion defined on the basis of the analysis of the reference module can be supplemented, but can also be replaced by a statistical analysis of several modules. The comparison between the thermographic analysis and the visual inspection clearly confirmed thermography as a complementary method for testing PV-s.
Driven by the need for sustainable and efficient energy systems, the optimal management of distributed generation, including photovoltaic systems and battery energy storage systems within prosumer households, is of crucial importance. This requires a comprehensive cost–benefit analysis to assess their viability. In this study, an optimization model formulated as a mixed-integer linear programming problem is proposed to evaluate the integration of battery storage systems for 10 prosumers on the radial feeder in Croatia and to quantify the benefits both from the prosumers’ perspective and that of the reduction in grid losses. The results show significant annual cost reductions for prosumers, totaling EUR 1798.78 for the observed feeder, with some achieving a net profit. Grid losses are significantly reduced by 1172.52 kWh, resulting in an annual saving of EUR 216.25 for the distribution system operator. However, under the current Croatian market conditions, the integration of battery storage systems is not profitable over the entire lifetime due to the high initial investment costs of EUR 720/kWh. The break-even analysis reveals that investment cost needs to decrease by 52.78%, or an inflation rate of 4.87% is required, to reach prosumer profitability. This highlights the current financial barriers to the widespread adoption of battery storage systems and emphasizes the need for significant cost reductions or targeted incentives.