Search Results (5)

The penetration rate of distributed photovoltaic (PV) in mountainous distribution networks is increasing year by year, and the assessment of distributed PV hosting capacity (PVHC) in distribution networks in mountainous areas is also becoming more and more important. To this end, this paper proposes a robust assessment method for distributed PVHC of flexible distribution networks in mountainous areas. The method utilizes soft open point (SOP) and energy storage to realize the flexible interconnection of distribution networks in mountainous areas, connecting the low-voltage nodes at the end of distribution networks in mountainous areas and improving the overall power quality of distribution networks. Secondly, the output curves of distributed PV output and load demand are analyzed and the distributed PV uncertainty model is drawn, so as to construct a two-layer robust assessment model of distributed PVHC for mountainous flexible distribution networks. Finally, the dual-layer robust assessment model, which cannot be solved directly, is transformed into a solvable mixed-integer linear programming model using the pairwise method, and the effectiveness of this paper’s method is verified by the simulation results of the IEEE 33-node distribution network system. Full article

The access of a high proportion of photovoltaic (PV) will change the energy structure of the distribution network (DN), resulting in a series of safety operation risks. This paper proposes a two-stage PV hosting capacity (PVHC) calculation model to assess the maximum PVHC, considering the uncertainty and active management (AM). Firstly, we employ a robust optimization model to characterize the uncertainty of sources and loads in DN with PV and analyze the worst-case scenarios for PVHC. Subsequently, we construct a PVHC calculation model that takes into account AM, and convert the model into a mixed-integer second-order cone (MISOC) model using linearization techniques. Finally, we apply “heuristic optimization + CPLEX solver” to solve the model and introduce overvoltage and overcurrent indices to analyze the safety of the DN under PV limit access. Case studies are carried out on the IEEE 33-bus system and a practical case. Results show that (1) only the uncertainty that reduces the load or increases the output efficiency will affect PVHC; (2) for DN limited by overvoltage, AM can better improve PVHC; however, for DN limited by maximum transmission power, the effect of AM is low; (3) for most DN, SVC can improve PVHC, but the effect is modest. And network reconfiguration can significantly increase PVHC on the system with poor branch network, even reaching 150% of the original PVHC. Full article

With many distribution networks adopting photovoltaic (PV) generation systems in their networks, there is a significant risk of over-voltages, reverse power flow, line congestion, and increased harmonics. Therefore, there is a need to estimate the amount of PV that can be injected into the distribution network without pushing the network towards these threats. The largest amount of PV a distribution system can accommodate is the PV hosting capacity (PVHC). The paper proposes an efficient method for estimating the PVHC of distribution networks that combines particle swarm optimization (PSO) and the gradient descent algorithm (GD). PSO has a powerful exploration of the solution space but poor exploitation of the local search. On the other hand, GD has great exploitation of local search to obtain local optima but needs better global search capabilities. The proposed method aims to harness the advantages of both PSO and GD while alleviating the ills of each. The numerical case studies show that the proposed method is more efficient, stable, and superior to the other meta-heuristic approaches. Full article

In recent years, the emerging fear of an energy crisis in central Europe has caused an increased demand for distributed energy resources (DER), especially small photovoltaic rooftop installations up to 10 kWp. From a technical point of view, distributed PV in low-voltage networks is associated with the risk of power quality violation, overvoltage, voltage unbalance, harmonics, and violation of the thermal limit of phase conductors, neutral conductors, and transformers. Distribution system operators (DSO) are currently in a position to determine the amount of installed PV power for which reliable and safe network operation is ensured, also known as the photovoltaic hosting capacity (PVHC). The presented study describes a stochastic methodology for PVHC estimation and uses it to analyze a typical LV rural network in the Slovak Republic. Detailed and precise calculations are performed on the 4-wire LV model with accurate results. In this study, we, thus, profoundly analyze the problems with voltage violation, unbalanced voltage energy losses, and the thermal loading effect of increasing PV penetration. The results show that overvoltage events are the main factor limiting the PVHC in LV systems. This conclusion is in accordance with the experience of the DSO in the Slovak and Czech Republic. Subsequently, the study focuses on the possibilities of increasing PVHC using those tools typically available for DSO, such as changes in PV inverter power factors and no-load tap changer transformers. The results are compared with those derived from similar analyses, but we ultimately find that the proposed solution is problematic due to the high variability of approaches and boundary conditions. In conclusion, the paper discusses the issue of the acceptable risk of overvoltage violation in the context of PVHC and lowering losses in LV networks. Full article

PV hosting capacity (PVHC) analysis on a distribution system is an attractive technique that emerged in recent years for dealing with the planning tasks on high-penetration PV integration. PVHC uses various system performance indices as judgements to find an available amount of PV installation capacity that can be accommodated on existing distribution system infrastructure without causing any violation. Generally, approaches for PVHC assessments are implemented by iterative power flow calculations with stochastic PV deployments so as to observe the operation impacts for PV installation on distribution systems. Determination of the stochastic PV deployments in most of traditional PVHC analysis methods is automatically carried out by the program that is using random selection. However, a repetitive problem that exists in these traditional methods on the selection of the same PV deployment for a calculation was not previously investigated or discussed; further, underestimation of PVHC results may occur. To assess PVHC more effectively, this paper proposes an improved stochastic analysis method that introduces an innovative idea of using repetitiveness check mechanism to overcome the shortcomings of the traditional methods. The proposed mechanism firstly obtains all PV deployment combinations for the determination of all possible PV installation locations. A quick-sorting algorithm is then used to remove repetitive PV deployments that are randomly selected during the solution procedure. Finally, MATLAB and OpenDSS co-simulations implemented on a small distribution feeder are used to validate the performance of the proposed method; in addition, PVHC enhancement by PV inverter control is investigated and simulated in this paper as well. Results show that the proposed method is more effective than traditional methods in PVHC assessments. Full article