A distributed voltage control scheme is proposed in an active distribution network in the presence of a large scale photovoltaic (PV) farm/plant to mitigate high ramp-rate issues. Multiple voltage regulating devices, such as on-load tap changers, step voltage regulators (SVRs), and switched capacitors banks are controlled in various ways based on either a centralized or a distributed coordination management scheme. This paper presents the relationship of the active and reactive power outputs of a PV plant in the presence of the conventional voltage regulating devices, and proposes a distributed control strategy to coordinate the SVRs with the PV smart inverter's capability to improve power quality. The distributed voltage control schemes are tested on an unbalanced medium voltage feeder located in a California utility service territory with the PV integrated at the far end of the feeder.

This work proposes a novel zone-based multistage “time-graded” operation of cascaded on-load tap changing (OLTC) transformers, capacitor banks (Cap Banks) and step voltage regulators (SVRs) in the presence of large-scale photovoltaic (PV) sources. A multi-stage Volt-VAr optimization (VVO) algorithm is proposed to regulate the voltage in a medium voltage (MV) unbalanced distribution system while trying to relax the tap/switch operations of regulators that are cascaded in series, and minimize the curtailment of PV inverter output. A linearized power system model is formulated and a Mixed-Integer Quadratic Programming (MIQP) solver is utilized to solve the sub-objective optimization at each stage in near to real-time. The multi-stage coordinated operations are performed successively based on the regulator zones starting from the zone nearest to the substation, to achieve the overall voltage regulation of the system. Simulation studies were performed for various scenarios of PV and load profile variations. A comparison study between the novel multi-stage VVO and a multi-objective Volt-VAr optimization (VVO) to observe the convergence performance. Results show the efficient usage of the conventional voltage regulating devices along with minimal power curtailment from PVs when required.

Electricity generation from biomass energy resources is compared with wind and solar power considering an uncertain electric load and a variable generation in the present study. The comparison results can give a good perspective to readers for judgment about energy utilization method in places which all of these renewable energy sources are available and the electricity consumption as well as wind and solar energy are not certain and constant. The hybrid operation of biomass, wind, and solar is unavoidable due to limited availability to energy sources in each region under load uncertainty and generation variability. For examples, some areas have a great potential for wind power generation, while they are cloudy most of the times as solar irradiation efficiency is low in such places. Whereas in some sunny areas, often wind is absent and in some other places like seashores both wind blow and sunshine is good. Important question is that if these three energy generation sources are available enough in the same place, which of them is better and more efficient to satisfy electricity demand of consumers with uncertain load patterns? To address this concern, a village in Morocco with great potentials of wind, solar, and biomass energy generation is economically studied to find out better renewable electricity generation method in uncertain environments.

The operational cost of distribution systems is significantly affected by the energy losses of the system. Distribution network losses are known to be higher than transmission system losses, constituting over 70% of all the losses that occur in the power system. For the achievement of loss minimization, operation cost mitigation, and generation expense reduction, the efficient allocation of distributed generation (DG) in distribution networks is considered an effective solution. The penetration of renewable DG units in distribution systems has seen an increasing trend in recent times due to the numerous benefits that come with the use of renewable sources for power generation, especially for the environment. Power demand variations and the variability of load levels play a vital role in the determination of the amount of losses that occur on the network and subsequently the optimal generation of DGs. Meanwhile, taking into consideration the variability of load level in the DG allocation problem worsens the computational stress and time significantly. Therefore, this paper has formulated an effective DG allocation model for energy loss minimization considering power demand variation. The developed model was simulated for different distribution systems using A Mathematical Programming Language (AMPL) to validate the performance of the proposed formulation by comparing the proposed model results with two different models (exact and peak load model). Parameters tested in the study are network losses, cost, and computational time. The evaluation of numerical results indicates the proposed model is very effective for DG allocation in terms of losses, cost, and computational time.

Network reconfiguration is an effective technique to reduce lost power in distribution systems, where losses are significantly greater than the ones in transmission. The distribution power loss produces a costly operation and a degraded voltage profile over the electric power systems. In traditional reconfiguration, the topology of the distribution network is efficiently modified to achieve minimum power losses based on the electric energy requested by end-users. Various types of energy consumers are connected to load points of actual distribution networks that cause different power losses compared to mono-type loads. However, the majority of models propose distribution reconfiguration problems disregarding consumer diversity. The few studies that have included load type in their proposed reconfiguration strategies present non-linear formulations for the problem and do not consider the impact of ambient temperature on network topology. However, non-linear models can be solved by metaheuristic algorithms without guaranteed optimal solutions or can be computed by non-linear solvers in classic optimization tools but require intensive and time-consuming computations that restrict their real-world applications. Moreover, environmental temperature affects electricity consumption, and therefore, the selection of appropriate switching combinations. Therefore, the current paper introduces an efficient model for the reconfiguration of distribution systems considering various load types with their dependencies on environment temperature rise that can be easily implemented by linear solvers in commercial optimization software. The results indicate that the proposed model is precise enough to find accurate solutions for desired reconfiguration problems and is adequately fast for online reconfigurations, showing significant effect of environment temperature on the configuration of distribution systems through load and power losses changes.

Distribution network losses constitute over 70% of all the losses that occur in power systems, resulting in the increment of operational cost, voltage profile distortion, and power supply instability. Therefore, addressing power losses has become a major concern for power system owners and operators, leading to the development of several mechanisms for network losses minimization. Among the proposed methods for loss minimization in power systems, the placement of distributed generation (DG) in reconfigurable power networks is considered as one of the most efficient mechanisms to reduce network losses, operation costs, and generation expenses. However, load variability consideration in the DG allocation and reconfiguration problem raises the burden and computational time considerably. Consequently, the current paper proposes an effective reconfiguration and DG allocation approach for loss reduction in the presence of variable loads. In the proposed method, an equivalent load factor was appropriately calculated from an actual load profile and embedded into the constraints of DG and reconfiguration problem. The proposed model is compared with exact and conventional models in several IEEE busbar systems in a mix-integer liner programming model using A Mathematical Programming Language (AMPL) in CPLEX. Numerical results evaluation of the proposed model and the exact model shows that the proposed model is able to reduce the computational time of the exact load profile model by 9 to 1000 times with power loss error margin of between 7 and 18%. While comparing the proposed model with conventional one indicates the proposed formulation is able to reduce the systems power loss of the conventional model by up to 50%. From the results, it was concluded that the proposed model is very efficient in terms of computational time reduction as well as reducing the active losses of a distribution network.