Optimal power flow for distribution systems under uncertain forecasts

Decentralized saddle-point dynamics solution for optimal power flow of distribution systems with multi-microgrids

Proliferation of Distributed Energy Resources (DERs) and Phasor Measurement Units (PMUs) into electric power distribution grids presents new opportunities for utility operators to manage distribution systems more effectively. In this work we formulate an Optimal Power Flow (OPF) approach that manages DER power injections to minimize the voltage phasor difference between two nodes on a distribution network with the goal of enabling efficient network reconfiguration. To accomplish this, we develop a linear model that relates voltage phase angles to active and reactive power flows in unbalanced distribution systems. Used in conjunction with existing linearizations relating voltage magnitudes to power flows, we formulate an OPF capable of minimizing the voltage phasor difference between two points in a network. In simulations, we explore the use of the developed approach to minimize the phasor difference across switches to be closed, thereby providing an opportunity to automate and increase the speed of reconfiguration in unbalanced distribution grids.

The increasing penetration of wind generation in electric power systems has made evident the necessity of a unified energy infrastructure interdependency analysis, in order to explore the optimal use of fossil fuel-based generation and the security constraints associated with different energy infrastructures. In this context, the optimal generation dispatch of online generating units is important in the daily operation planning. This paper proposes a multi-energy day-ahead optimal power flow (OPF) approach in order to assess the wind energy penetration in an electric power system and its impact on the fossil fuel-based generation management. The applicability of the proposed approach is demonstrated by integrating a 15-node natural gas network and a 4-node coal distribution system with the IEEE 118-bus power system.

Based on the forecasted power demand, energy generated by the powerindustries, is lost on their path to users via the transmission and distribution networks. This is consistently one of the most predominant issues facing the power industries. In view of the expansion of the distribution system, most power losses occur in such networks. So, there has a great need to reduce the losses. In this paper, an Optimal Power Flow (OPF) approach is implemented by minimizing the total system losses. And also, the impacts of Wind and D-STATCOM on loss reduction and voltage profile improvement are studied by placing them individually and simultaneously at optimal location. Sensitivity based methods are used to find optimal location. In addition, the annual energy savings and energy loss costs obtained using Deterministic load is compared with Probabilistic load. The entire case study was carried out on a standard IEEE 69 bus Radial Distribution System (RDS) using General Algebraic Modeling System (GAMS) software.

Today, congestion management on higher voltage levels is almost exclusively done preventively. However, integrating curative measures which utilize flexible power and innovative control equipment such as Impedance Controllers (ICs) can leverage significant benefits for grid operation. To ensure these curative measures take effect in due time, they should be activated by an automated system. In this work, a centralized replica of a distributed Multi-Agent System (MAS) is developed as a kind of simplified digital twin. The MAS uses heuristic search algorithms based on dc sensitivity analysis to eliminate grid congestion. By centrally replicating the underlying control algorithms, control interventions of the distributed system can be predicted. Also, testing and troubleshooting of new Heuristic Control Algorithms (HCAs) is facilitated by the centralized version. This way, in addition to the existing HCA, alternative heuristics are developed, implemented and tested in this centralized version. The proposed heuristics focus on the differences in the calculation of IC sensitivities and their accuracies for overload control. Besides, they make a broader range of choices of Flexible Power Units (FPUs) available to solve overloads in the grid, making the algorithm more efficient. Furthermore, the control heuristics are validated with Optimal Power Flow (OPF) approaches. For the validation of the system, the IEEE 39 New England Test-Bus system is used in Matlab MATPOWER.

The modern Distribution Systems (DS) require for accurate and fast Power Flow (PF) algorithms as a basis for other DS applications. Almost all decisions are taken based on accurate PF results and, possibly, they have to be taken in real time. In this paper, a new PF algorithm based on a linear programming approach is proposed. The graph theory is used for modeling the distribution network with some topological matrices. The proposed matrices are then utilized to develop a linear optimization model in rectangular form for PF in DS. Moreover, a linear load model is used for calculating the current injections in each system bus. This leads the PF equations to be linear with acceptable accuracy. In the paper the proposed PF algorithm is implemented on IEEE 18-bus and 33-bus test systems. The results show the accuracy and the performance of the proposed PF model compared to existing models. Since the optimization model is linear, the solution is global optimum. It facilitates the application of the accurate PF results in real-time optimization of DS.

Large-scale distribution systems (DSs) require an efficient power flow algorithm which can explicitly exploit their characteristics. This paper presents a novel power flow algorithm for radial and weakly meshed distribution systems (WMDSs) using a direct method (DM). The paper also develops a novel approach to simulate the voltage-controlled buses which is becoming increasingly important due to the introduction of distributed generations in DSs. The proposed power flow algorithm is constructed based on simple electrical circuit rules so that only a Z matrix expressing common impedances between loads is required for simulation. For WMDSs, only modification is to use the current divider rule to solve meshes. The simulation of PV-buses is presented using the Newton–Raphson solution algorithm. The validation and comparison of results in different systems show the simplicity and low computations of the proposed method which make it time-saving and very efficient for large-scale DSs.

현재의 배전계통의 전압은 변전소에서 단방향 조류를 고려하여 LDC에 의한 전압조정방법으로 ULTC 변압기의 랩을 변환하여 공급전압을 적정범위 내에서 유지되도록 운전하고 있다. 그러나 현재의 배전계통 운용은 소용량에서 대규모 용량에 이르기까지 다양한 용량의 PV 시스템이 배전계동에 연계되어 운전되는 것을 반영하지 못하고 있는 실정이다. 때문에 다수의 PV 시스템이 계통에 연계되어 양방향 조류가 발생하고 이로 인해 연계점의 전압변동이 발생하여도 이를 효과적으로 조정하지 못하여 계통의 전압이 적정범위 내에서 운용되지 못하는 경우가 발생할 수 있다.<BR> 따라서 본 논문에서는 다수 PV 시스템의 연계에 따른 양방향 조류의 발생을 고려하고 연계점의 전압변동에 따른 계통의 전압을 효과적으로 제어할 수 있도록 실시간 감시가 이루어지는 PV 시스템의 특정을 이용하고 기존의 LDC 전압조정방법을 개선하여 PV 시스템 연계 시에도 변전소에서 계통의 전압을 적정범위 내에서 조정할 수 있는 개선된 전압조정방법을 제안하였다.

Distributed generators (DGs) are nowadays most commonly used in distribution networks to meet the rising demand. The distribution network power flow is altered as more distributed generations are integrated with the distribution network. Analyzing and researching the network's power flow with distributed generation is an essential element of analyzing the distributed generation's influence on the networks. This study proposed new sites in the test network for the purpose of connecting DGs. Good results were obtained in improving the necessary network elements. Firstly, applying a Newton-Raphson method to measure the distribution network's power flow without distributed generations. Then the optimal power flow approach with DGs is set up based on many goals such as minimizing fuel cost, minimizing losses, voltage deviation, increasing efficiency, and the incremental fuel cost in the network appeared. Eventually, applying Particle Swarm to overcome the optimization problems. In MATLAB software environment and programing MATPOWER version 6.0, the simulation is evaluated and validated using the IEEE30 node method. The test results indicate that optimal power flow analysis with distributed generation will accomplish many networks aims and boost system economy.

This paper presents an optimal power flow dispatching for a grid-connected photovoltaic-battery energy storage system under grid-scheduled load-shedding to explore solar energy sufficiently and to benefit the electric vehicle battery swapping station at the charging demand side. The proposed system comprises a solar photovoltaic system, a battery energy storage system, and an electric vehicle battery swapping station. The optimization problem is formulated as a multi-objective optimization problem in a discrete-time domain to minimize the operational costs associated with the power flow drawn from the utility grid and the wearing cost of the hybrid system due to the frequent charging and discharging of the battery energy storage system when charging the depleted EV battery. A linear programming method determines the optimal power flow in the proposed system to charge the depleted battery for electric vehicles. Simulation results show the effectiveness of the developed model by providing the optimal dispatch power flow at the electric vehicle battery swapping station at the charging demand side. The comparative analysis with related works further underscores the competitive performance of the proposed optimization approach in enhancing energy resilience and cost efficiency.

Distributed generation (DG), which is interlinked with distribution system, will inevitably have an impact to system. In the paper, a reliability evaluation method is proposed, which is based on the analysis to the structure and power flow of distribution system with distributed generation. First, a new concept, the smallest unit, is put forward for improving the fault traversal networks times. The authors use the depth-first search in data structure to divide distribution system into several the smallest units, and propose the islanding operation mode to increase the reliability of the system. Distribution system will be automatically turned into the islanding operation mode once faults occur. To evaluate quantitatively the reliability of distribution system, Monte Carlo simulation method is used by simulating the running status of distribution system. At last, the calculation results of actual case show that the proposed method is available to evaluate the reliability of distribution system with distributed generation.

This paper proposes an approach for optimal power flow considering several contingency states. Initially, contingency selection is conducted to measure how much a specific contingency may affect the operation cost. Then, some severe contingencies are incorporated into optimal power flow problem. All considered states, normal and contingency states, are simulated simultaneously. Thus, if contingency occurs, it can be ensured that all constraints such as generation limit, transmission limit and ramp rate will be satisfied. To solve the problem, quadratic programming is applied. IEEE 30 bus system is used as test system to show the ability of the proposed approach.

This paper develops an effective control framework for DC voltage control and power-sharing of Multi-Terminal DC (MTDC) grids based on an Optimal Power Flow (OPF) procedure and the voltage-droop control. In the proposed approach, an OPF algorithm is executed at the secondary level to find optimal reference of DC voltages and active powers of all voltage-regulating converters. Then, the voltage droop characteristics of voltage-regulating converters, at the primary level, are tuned based on the OPF results such that the operating point of the MTDC grid lies on the voltage droop characteristics. Consequently, the optimally-tuned voltage droop controller leads to the optimal operation of the MTDC grid. In case of variation in load or generation of the grid, a new stable operating point is achieved based on the voltage droop characteristics. By execution of a new OPF, the voltage droop characteristics are re-tuned for optimal operation of the MTDC grid after the occurrence of the load or generation variations. The results of simulation on a grid inspired by CIGRE B4 DC grid test system demonstrate efficient grid performance under the proposed control strategy.

In this paper two loss allocation (LA) schemes based on the principle of equivalent bilateral exchanges (EBEs) and the network Z-bus matrix are compared with each other. The modified IEEE 14-bus network has been selected as case study. Several operating conditions such as, load increment and system congestions are applied to the test system in order to evaluate the loss allocation methods. In the case of network congestions optimal power flow is used based on a P.S.O. method. An economic analysis with these LA methods is also carried out. Results show that these economic indexes are very close to the marginal costs derived from an optimal power flow (OPF) approach with the advantage of reducing volatility. They also indicate that the allocation schemes produce loss allocations that are appropriate and they behave in a physically reasonable manner while the congestion is occurred.

The study of power system planning, security and control is crucial for determining optimal power flow (OPF), a highly non-linear complicated issue. The functioning of the power system remains complex when Renewable energy sources are connected to the grid along traditional generators. This review paper describes various techniques applicable to the power system networks accessible in the literature. The conventional optimisation algorithms have been reintroduced, while the power systems have been heavily predisposed over the last few years. The most crucial technical, adaptive and economic tool in this context is OPF. In this paper, we compare OPF approaches related to objective functions. Aside from computational power, the case study network and publication dates for these algorithms are described. Finally, we will address some of the basic challenges that arise from the new OPF approach to the modern grid. Mainly, optimisation techniques are compared in terms of reliability, accurateness, faster convergence and applicability for single and multiple objective functions. Initially, the paper discusses types of networks such as AC or DC, constraints and their objectives on OPF, mathematical and different optimisation techniques reviewed. The heuristic and meta-heuristic algorithms, like genetic algorithm and Jaya algorithm, were compared for various operational parameters. In this work, OPF with single- or multi-objective functions such as voltage stability, voltage deviation, emission, cost and losses, consisting of conventional and renewable energy resources were considered. Additionally, Pseudo-code algorithms were presented for some recently evolved algorithms to ease the understanding of the readers.