Placing and sizing distributed photovoltaic generators for optimal reactive power compensation

The modern active distribution systems necessitate integrating storage systems, thereby facilitating the large-scale proliferation of photovoltaic (PV) energy resources. This further calls for the optimal planning of energy storage systems, satisfying all the operational and economic constraints. This article describes an exhaustive storage integration method, deeming the life cycle of the battery energy storage, the uncertainty of load and PV output, and the islanded mode of operation of the system. A two-stage mixed-integer linear programming problem is formulated that determines the capacity and the number of discharge cycles of the batteries in the first stage. The lifetime of the battery based on the partial depth of discharge is analyzed in the second stage. Furthermore, the uncertainty and variability of PV and demand are taken into account through probabilistic analysis and time-period clustering. The method is validated on a standard 33-bus radial distribution network for the allocation of distributed lithium-ion batteries. Also, the method’s scalability is validated on a practical Indian distribution network and a 141-bus distribution network of metropolitan area of Caracas with distributed PV installations on various nodes.

Utilization of active power filters (APFs) is the most efficient method to reduce harmonic pollution in distribution networks. Previous approaches utilized APFs in integrated control schemes based on broad data-gathering systems. Since a broad data-gathering system is not available in most practical distribution networks, previously proposed approaches may not readily be implemented. This paper presents the utilization of stand-alone controlled APFs (SACAPFs) in radial distribution networks. Utilizing APFs with a stand-alone control system decreases implementation costs and complexity by making them autonomous and independent of integrated control systems, which are complicated and expensive in practical applications. In this paper, a single SACAPF is modeled as a dependent current source where its injection current is equal in amplitude but opposite in phase compared to the harmonic content of the current passing through the point of common coupling (reference current). Due to the presence of both linear and nonlinear loads in the distribution network, the reference current changes after injection by SACAPF, so it is necessary to modify the injection current until reaching a constant value in the reference current. This is considered via an iterative procedure in the modeling scheme. Operation of multiple SACAPFs is handled using a backward procedure based on a priority list. Simulation results on an IEEE 18-bus test system show the proper operation of the stand-alone control systems for both single and multiple SACAPF implementation. Furthermore, optimal allocation of the proposed SACAPFs is performed in an IEEE 33-bus test network and a 9-bus test network, and the results are discussed and compared with the allocation of integrated control system APFs.

A Solid-State Transformer as Enabling Technology for Microgrids for Integration into the Power Distribution System: An Overview

Integration of Distributed Generation (DG) in the Distribution network will reduce the network expansion costs and increase the network reliability in terms of reduction in voltage magnitude deviations.This paper presents Symbiotic Organisms Search (SOS) based technique for finding out the best size and position of DG in Radial Distribution networks to improve the voltage profile and voltage security state of the Distribution network. The primary objectives of the paper are minimization of bus voltage variation and maximization of voltage stability index of the network as a multi objective optimization problem in presence of uncertainty of sources and loads. In this paper the uncertainty of solar power, wind power and load are modelled using 2m Point Estimate Method along with SOS algorithm.To show the effect of DG placement on voltage security state of Distribution system, the system is classified into three states based on the values of voltage stability index (VSI). Simulation results as obtained from two standard (IEEE) radial distribution networks prove the efficiency and accuracy of the proposed SOS method. The results of SOS based method are compared with some other techniques as found in recent literature, which shows that SOS algorithm outperforms other standard optimization techniques.

ABSTRACTThe optimal design and installation of hybrid photovoltaic (PV), wind turbine (WT) distributed generation (DG), and battery energy storage system (BESS) in radial distribution network (RDN) using dynamic arithmetic optimization algorithm (DAOA) is the main purpose of this work. The DAOA algorithm is the improved version of arithmetic optimization algorithm (AOA) which is widely used in the field of Electrical Engineering to solve the different optimization tasks. The simultaneous minimization of active power loss and voltage deviation is taken as the objectives to improve the efficiency of the distribution network using hybrid PV/WT/BESS system. To establish the efficacy of the suggested DAOA method, it is examined on two very well‐known test systems (33‐bus and 69‐bus). The uncertainty of power generation from PV‐ and WT‐based DG due to solar irradiance and wind speed variation also is taken into consideration. The cost analysis of the hybrid PV/WT/BESS system as well as active power loss cost are also assessed in this study. The result comparison shows that the DAOA algorithm gives supreme result in case of active power losses, voltage deviation, and benefits in active power lost cost. This algorithm has good speed of response and solution quality when hybrid PV/WT/BESS system allocation problem of the distribution network with simultaneous power loss reduction and voltage deviation minimization is executed in RDN. The placement of hybrid PV/WT/BESS system in 33‐bus reduces the active power loss by 44.27%, 41.47%, 46.23% using DAOA and 44.26%, 39.87%, 45.18% using AOA for normal loading, 15% increased loading, and 10% decreased loading, respectively. Similar results are also observed for 69‐bus test system. Moreover, if the performance of the DAOA, AOA, immune clone selection algorithm (ICSA), clone selection algorithm (CSA), manta ray foraging optimization (MRFO), and particle swarm optimization (PSO) for PV, WT, BESS‐ based 33‐bus system are observed, it can be noticed that DAOA gives annual savings of 10$, 496$, 505$, 669$, and 554$ as compared to AOA, ICSA, CSA, MRFO, and PSO, respectively. Similarly for PV, WT, BESS‐based 69‐bus system, it is observed that DAOA gives annual savings of 29$, 3147$, 3154$, 3342$, and 3158$ as compared to AOA, ICSA, CSA, MRFO, and PSO, respectively. In case of solution quality, the DAOA method grants its superiority over several optimization methods found in the literature.

The development of distributed photovoltaic (PV) power generation has been significantly promoted in recent years. With the increasing penetration of PVs, severe voltage violations may occur in distribution networks due to the intermittency and fluctuation of PV power output. Reactive power compensation by PV and active power charging/discharging by battery energy storage systems (BESS) are effective solutions. This paper proposes an accelerated dual ascent (ADA)‐based distributed voltage control framework for PV and BESS coordination of distribution networks to alleviate the voltage violation. To maximise PV utilisation, the strategy prioritises PV reactive power control, while BESS active power rapidly responds to voltage deviations if the voltage exceeds predefined limits. The proposed voltage control strategy can effectively ensure distribution network security. Furthermore, to enhance the convergence speed of the traditional dual ascent (DA) algorithm, this paper incorporates an additional momentum term into the DA algorithm to obtain the ADA algorithm. To address the limitation of traditional voltage control, which requires iterative convergence before voltage control can be performed, an online voltage control strategy has been designed. The online implementation of ADA‐based distributed voltage control leverages instantaneous voltage measurement to effectively handle rapid fluctuations of distribution networks. Moreover, the proposed method only requires information exchange between adjacent PVs and BESSs, thereby reducing the complexity of communication. Simulation based on an IEEE 123‐bus distribution network and a typical rural distribution network demonstrated the proposed control strategy has a faster convergence speed and better voltage regulation effect.

With large-scale distributed energy resources (DERs) being integrated into distribution networks (DNs), the coordinated optimal power flow (OPF) of high voltage (HV) and medium voltage (MV) DNs becomes challenging due to enhanced uncertainties and nonlinearity. This paper presents a hierarchical distributed chance-constrained OPF model for HV and MV DNs based on a nonlinear adaptive data-driven method. The HV master problem aims to minimize the overall operational costs, and is transformed into mixed-integer convex problem via second order cone programming. A model-free chance-constrained optimization sub-problem is established to tackle inaccurate model parameters issues and DER uncertainties in MV DNs and realize rapid response to control schemes from HV DN. The nonlinearity of power flow is approximately depicted by a data-driven incomplete dimension lifting power flow (IDL-PF) constraint, which is integrated into the MV DNs optimization model. A novel multi-parameter programming (MPP)-based distributed algorithm is proposed to solve the coordinated OPF model, which can significantly accelerate the iterative speed between the master and sub-problems. Finally, the convergence, efficiency and optimality of the proposed method are validated by numerous simulations in a practical DNs in China.

This paper studies optimal day-ahead scheduling of grid-connected batteries that simultaneously provide three services: 1) load shifting, 2) real-time balancing, and 3) primary frequency control (PFC). The uncertainties of load and frequency are incorporated in the cost-minimizing scheduling problem via chance constraints. The resulting chance-constrained problem is then reformulated into a mixed-integer second-order cone program (MISOCP) that can be solved by commercial solvers. However, it is computationally formidable to obtain the globally optimal solution to the MISOCP due to the big problem size. To obtain a suboptimal solution quickly, a heuristic based on penalty alternating direction method (PADM) is developed to solve the MISOCP. Fixing the integer solution returned by the heuristic, we adopt the duality of the second-order cone program (SOCP) to price the three services in the local market. Theoretical analysis of the market equilibrium, individual rationality, and balanced budget is given. Real-world data of load, frequency, and price in the French grid is used in simulation. The results show that the proposed heuristic is computationally efficient, and the pricing results can guarantee a positive utility for each of the batteries, incentivizing them to provide services.

With more and more distributed roof photovoltaic generators connected to the grid and their complementarity with gas turbines, which providing many possibilities for the coordinated operation of electricity-gas integrated energy system (IES). In this paper, aiming at minimize the total generation costs, a robust optimal power flow (ROPF) model was proposed for the electricity-gas IES connecting roof photovoltaic (PV) generators in the distribution network. Then, the proposed ROPF model is transformed into the mixed-integer second-order conic programming (MISOCP) model, which can be solved by Gurobi. The numerical simulations are carried on IG-30 system and IG-118 system to verify the applicability, safety and economy of the proposed ROPF model.

This paper deals with the use of grid-connected photovoltaic (PV) power plants for supplying the ancillary service of reactive power compensation to the distribution grid. A control strategy has been developed for controlling both real and reactive power exchanged with the distribution network. The paper suggests how the real and reactive power references should be selected in order to maximize the electrical energy generated by PV arrays and to exploit the apparent power of the inverter close to its rated value. The choice suggested for reference signals allows reactive power compensation service also when the solar irradiation is negligible. The control strategy is then applied to a sample grid-connected PV unit, which has been simulated in Simulink environment. Numerical simulations show that, using an adaptive Perturb & Observe algorithm, the maximum power point tracking is achieved in about 2 seconds, both at starting and when the irradiation changes. The inverter is also capable of giving without interruptions the reactive power support to the grid, reducing grid currents and voltage drops along the line respect to the classical configuration where no reactive compensation is present.

As the gradual increase of distributed photovoltaic (PV) connected to the distribution network, to promote the consumption of distributed clean energy generation on the basis of maintaining the safe and stable operation of the distribution network, this paper proposes a calculation method for the maximum consumption capacity of distributed PV in the distribution network. Firstly, the fuzzy C-means clustering method is used to construct typical scenarios of PV output to ensure the applicability of the calculation method of photovoltaic accommodation capacity. Secondly, multiple active management (AM) measures existing in the distribution network are modeled, such as on-load voltage regulation, reactive power compensation, control of the battery energy storage system, etc., to promote distributed PV consumption in the distribution network. Then, with the objective function of maximizing the distributed PV accommodation capacity, the calculation model of the distributed PV accommodation capacity in distribution network is established by comprehensively considering various electrical constraints, such as harmonic current and voltage fluctuation constraints. Finally, the effectiveness of the method is verified by an improved IEEE 33-bus system, and the promoting effect of various AM measures on PV consumption is verified.

The power grid has gradually changed its operation during the recent decades. These developments have encouraged a shift from centralized to decentralized power flow control. A research has been carried out to investigate the possibilities to control power flows using the Smart Power Router (SPR) in distribution networks, where a large share of distributed generation (DG) is present. In this paper, the possible applications of the SPR have been explored in a laboratory test network. In particular, the SPR's control capabilities for both active and reactive power flows were enhanced to improve the system performance. An overview of the control of the SPR is presented. The effect of the power flow management with reconfigurations in the distribution network is considered. Furthermore, the possibilities for decoupled control of the active and the reactive power flow are elaborated.

Grid-connected photovoltaic system in Malaysia: A review on voltage issues

Dynamic active and reactive power compensation in distribution networks with batteries: A day-ahead economic dispatch approach

In this paper a new and efficient method for solving the load flow problem of a distribution system is discussed. It is based on network topology, basic circuit laws and power summation technique. The main contribution of this paper is: (i) It proposes a new, efficient load flow method for radial and weakly meshed distribution systems, (ii) It evaluates the impact of load models, different values of X/R ratios, load growth for future expansion and tolerance levels, (iii) It analyses the impact of number of loops on weakly meshed distribution systems, (iv) and also gives comparison of radial and weakly meshed distribution system. The results are obtained for voltage values, total real and reactive power losses, time of computation, and number of iterations required. Computer program coded to implement this power flow solution scheme in MATLAB and successfully applied to several practical distribution networks with radial and weakly meshed structure. Effectiveness of the proposed load flow method has been presented on IEEE 33bus radial and meshed distribution networks.