Power Flow Limits Research Articles

Assessment and Countermeasures of the Operation Risk of Distribution Network with High Penetration of Distributed PV

Due to the severe intermittence, volatility and uncertainty of the output power, the integration of large scale photovoltaics (PVs) will inevitably impact the power flow and node voltage of a distribution network, and confront the network with higher operation risk. This paper carries out the operation risk assessment of distribution networks with high penetration of PV units, and develops measures to offset the risk. A probabilistic power flow calculation based on Monte Carlo method is proposed in this paper at first, then the operation risk assessment model for a distribution network is established based on the risk assessment indexes of node voltage and line power flow limit violation. The specific implementation of the risk assessment method is presented. Based on these works, specific risk countermeasures are proposed. The validity of the risk assessment method and effectiveness of the risk countermeasures are verified by simulation results.

Distributed optimal active power dispatch with energy storage units and power flow limits in smart grids

Dynamic optimal active power dispatch with energy storage units and power flow limits is an important problem in smart grids. This problem is usually described as a convex optimization model. In our model, not only the conventional equality and inequality constraints, energy storage units’ constraints and power flow constraints are considered, but also the energy storage units’ operational costs and the power price of the main grid are considered in the total costs. To solve this problem, a fully distributed algorithm based on the alternating direction method of multipliers (ADMM), the projected gradient method and the average consensus is proposed. The proposed algorithm can obtain the optimal output power settings of the energy storage units, distributed generators and the main grid for different demand loads with different initial states. In the proposed algorithm, firstly, the dispatch problem is decomposed into multiple subproblems on the basis of the alternating direction method of multipliers; then the subproblems can be solved according to the projected gradient method and the average consensus algorithm. In order to apply the projected gradient method, every bus is equipped with a bus agent which is responsible for information communication and the output power optimization calculation. Simulation studies demonstrate the effectiveness of the proposed algorithm. .

Consideration of Network Constraints in the Turkish Day Ahead Electricity Market

This paper proposes a new model for the Turkish Day Ahead Electricity Market including network equations. The existing one does not implicitly consider the power flow limitations, and these are considered separately that might result with a suboptimal day-ahead schedule. The dc network equations are added to the model, which is used to determine the Day Ahead System Sell and Buy Decisions and System Marginal Price in day-ahead planning. The impact of integration of network equations is exhibited using a small 6-bus network, mid-sized Turkish northwest sub-system, and full Turkish electric power system.

Assessment of Wind Power Integrated to the Power Systems Using Probabilistic Load Flow Based on PFV with LS

Power flow analysis (PFA) is one of the most important issues of power system analysis and design. This paper aims at developing and applying a high-speed sampling method to produce large-capacity sample set based on pattern feature vector with layer structure (PFV with LS) of IEEE 14-bus system data analytical methods. In this study, sampling based pattern vectors are constructed in three layers. The first and second layer vectors are very low dimensional, and the sampling of the third layer is in parallel for each local area. Samples generated by this sampling method can be applied to the calculation of probabilistic load flow (PLF) and probabilistic static security assessment. Simulation results show that the proposed method can improve efficiency of PLF analysis and probabilistic static security assessment. The advantages of using PLF based on PFV with LS as the power flow limit can minimize the complicated mathematical equations. Furthermore, the algorithm is very simple and accurate, especially when the system connected to the wind power.

Decentralized power control management with series transformerless H-bridge inverter in low-voltage smart microgrid based P/V droop control

This paper presents the power flow control between the main grid and the microgrid in 400 V low-voltage distribution network using series transformerless H-bridge inverter. This series converter is attached directly in series with the line, connecting the main grid and the microgrid with each other. It controls the real power flow depending on the state of both networks and by injecting series voltage that changes the microgrid side voltage. Therefore, the microgrid units will respond directly to the changes of the series converter set points and vice versa. Controlling the power flow in the line using the series converter is investigated by implementing two novel control strategies. The feasibility of the control strategies is validated during both capacitive and inductive operation modes. FFT analysis of the PCC voltage has been investigated to determine the THD caused by the series converter during both modes of operation. Also, system performance with and without P/V droop control and real power flow limit at PCC are also verified during both modes of operation. Several simulation cases have been demonstrated to investigate the feasibility of the series converter concept. SimPowerSystems and PLECS tool boxes of Matlab/Simulink software are utilized to implement the proposed work.

Joint Regulation of Power Flow and Short Circuit Current Limitations with the Aid of a Phase-Shifting Transformer

The efficiency of installation of the phase-shifting transformer (PST) in the power supply system of St. Petersburg and the Leningrad Oblast’ is examined, making it possible to execute power flow management within the specified range and limit short-circuit currents to values that do not exceed the breaking capacity of the switching equipment. Its optimal parameters were found, based on analysis of various PST operating modes. Proceeding from this, design calculation of the magnetic core and transformer windings was performed.

Optimal Allocation of ESSs for Mitigating Fluctuation in Active Distribution Network

As distributed generations (DGs) are occupying an increasing proportion in active distribution network, the fluctuation of bus voltage becomes severe because of their intermittent and stochastic characteristics. Energy Storage System (ESS) can be adopted as an effective means to mitigate this fluctuation. This paper proposes a methodology for the optimal allocation of ESSs based on the novel optimal affine power flow (OAPF) approach. Affine models of wind turbine generation (WTG), photovoltaic (PV) system, and ESS are built while considering uncertainty characters of their power outputs. The objective function is set to minimize the capital investment of ESSs and the penalty costs of bus voltage fluctuations. The complex affine arithmetic based distribution power flow is used to ensure that constraints on power flow limits, voltage limits, and ESS operational limits are satisfied. The optimization problem is solved by an improved immune genetic algorithm (IIGA). The proposed approach is verified via a modified IEEE 33-bus system with a high penetration of DGs. Results show that the optimal allocation of ESSs can satisfy both the technical and economic requirements under such an uncertain environment.

The challenges of estimating the impact of distributed energy resources flexibility on the TSO/DSO boundary node operating points

The increasing penetration of renewable energy sources characterized by a high degree of variability and uncertainty is a complex challenge for network operators that are obligated to ensure their connection while keeping the quality and security of supply. In order to deal with this variable behavior and forecast uncertainty, the distribution networks are equipped with flexible distributed energy resources capable of adjusting their operating point to avoid technical issues (voltage problems, congestion, etc.). Within this paradigm, the flexibility that, in fact, can be provided by such resources, needs to be estimated/forecasted up to the transmission network node (primary substation) and requires new tools for TSO/DSO coordination. This paper addresses this topic by developing a methodology capable of finding the flexibility area while taking into account the technical grid constraints. The proposed approach is based on the formulation of a single optimization problem which is run several times, according with the expected precision for the flexibility area estimation. To each optimization problem run, a different objective function belonging to a family of straight lines is assigned. This allows exploring the active and reactive power flow limits at the TSO/DSO boundary nodes – which define the flexibility area. The effectiveness of the proposed model has been evaluated on two test networks and the results suggest a step forward in the TSO/DSO coordination field. Nevertheless, further investigations to study the effect of assets with discrete control nature (e.g., on load tap changers – OLTC, capacitor banks) on the occurrence of disjoint flexibility areas should be carried.

A chance constrained optimal reserve scheduling approach for economic dispatch considering wind penetration

The volatile wind power generation brings a full spectrum of problems to power system operation and management, ranging from transient system frequency fluctuation to steady state supply and demand balancing issue. In this paper, a novel wind integrated power system day-ahead economic dispatch model, with the consideration of generation and reserve cost is modelled and investigated. The proposed problem is first formulated as a chance constrained stochastic nonlinear programming U+0028 CCSNLP U+0029, and then transformed into a deterministic nonlinear programming U+0028 NLP U+0029. To tackle this NLP problem, a three-stage framework consists of particle swarm optimization U+0028 PSO U+0029, sequential quadratic programming U+0028 SQP U+0029 and Monte Carlo simulation U+0028 MCS U+0029 is proposed. The PSO is employed to heuristically search the line power flow limits, which are used by the SQP as constraints to solve the NLP problem. Then the solution from SQP is verified on benchmark system by using MCS. Finally, the verified results are feedback to the PSO as fitness value to update the particles. Simulation study on IEEE 30-bus system with wind power penetration is carried out, and the results demonstrate that the proposed dispatch model could be effectively solved by the proposed three-stage approach.

Robust operating zones identification for energy storage day-ahead operation

Abstract This paper presents a tool to robustly allocate the allowable operating zones of active and reactive power margins for multi-energy storage systems (ESSs) without violating typical distribution system constraints. This tool helps ESSs to manage its day-ahead energy independently without violating the power system constraints. The main contribution is considering the power uncertainties (loads and renewable energy) without taking very conservative decisions. For defining a robust operating zone (ROZ) for ESSs; first, a particle swarm optimization (PSO) algorithm detects the day-ahead worst-case power flow due to loads, renewable energy sources (RESs), and contingency uncertainties. Second, a second-order cone programming problem (SOCP) optimizer determines the maximum charge and discharge active powers for each ESS that maintains safe system operation limits (voltage limits, cables capacity, and reverse power flow limits). While an uncertainty budget designed by the fuzzy expert, the PSO uses this budget to reshape its searching space with less conservatism. Case studies with one hundred different uncertainty scenarios are conducted on a real 41-bus Canadian system. Simulation results have shown that the proposed algorithm provides robust operating zones for ESSs that consider uncertainties with reducing conservatism.

Market based procurement of energy and ancillary services from Renewable Energy Sources in deregulated environment

An increasing utilization of Renewable Energy Sources (RES) in electricity generation increases the need of Ancillary Services (AS) in power system. This paper proposes a market based approach for participation of Renewable Power Producers (RPP) to clear both energy and AS in day-ahead market under disaggregated framework. This approach is based on sequential clearing of Energy Market (EM) and Ancillary Service Market (ASM) such that the cost of procuring these services is minimized and feasible solution is obtained. This optimization problem is formulated and solved using Optimal Power Flow (OPF) technique which considers all transmission constraints and power flow limits. The AS considered in the present work is limited to Reserves Market (RM) such as Ten Minute Spinning Reserve (TMSR) and Thirty Minute Replacement Reserves (TMRR) only. The ability of RPPs like Wind Power Plant (WPP) and Photo-Voltaic Plant (PVP) with conventional power producers to provide both energy and AS has been demonstrated by considering a modified 7 unit test system.

Enhanced ant colony optimization to solve the optimal power flow with ecological emission

Enhanced ant colony optimization algorithm is exhibit to resolve the optimal power flow with ecological emission in this article. The chief objective is to reduce the total fuel cost of fossil thermal power generators and ecological emission. The exhibited technique sustains the satisfactory level of retaining the bus voltages, real and reactive power and power flow in transmission lines. It minimizes the computational time with satisfying all the power flow limitations. The projected technique validates on an IEEE 30 and 118 bus test system. The simulation results were promising when compared with the other techniques. Further, the outcomes clear that this technique is effective for resolving the power system with large ranged networks.

Fundamental Study of Voltage Stability in a Power System with Large Penetration of Photovoltaic Generation Considering Induction Motor Dynamics

SUMMARYBecause of global warming, attention to photovoltaic (PV) generation has increased, and considerable PV generation capacity will be installed in the power system. In Japan, most PV generation will be connected to the distribution system, which will cause changes in power flow in the power system. Forward power flow (flow from the higher voltage system to the lower voltage system) will be reduced and reverse power flow may occur. Because of the change in power flow, the voltage characteristics will also be changed. Consequently, it is expected that the penetration of PV generation will have some impact on voltage stability. In previous studies, the voltage characteristics in a simple power system model consisting of one infinite bus, one load, and one PV power source, have been investigated. It was found that there is not only a forward power flow limit but also a reverse power flow limit (the left nose in the PV curve), and that when the output power from PV generation is very large, the left nose sometimes has some impact on voltage stability. In this paper, the voltage stability in a simple power system model considering the dynamics of an induction motor is discussed.

A Novel Thermo-Mechanical Model to Assess the Dynamic Thermal Rating of Multi-Span Overhead Transmission Lines

The power flow limits of transmission lines are set in order to ensure a given level of security to the electric system; their improper definition can reduce system reliability, increase the curtailment of renewable energy sources or create barriers to the free trading of energy. Unlike the previous literature, the Dynamic Thermal Rating procedure here proposed takes into account not only that the temperature of conductors can vary by for different weather conditions, but also the mechanical interaction between spans, due to their different elongation and to the consequent rotation of insulator strings. The developed tool is able to forecast the time trend of conductor temperatures, tensions, sags and clearances at each span, or to indicate which current can be carried for a given time before a clearance or temperature constraint is violated. Several case studies compares the results of this novel method with the outcomes of the traditional ruling span technique, especially when using High-Temperature Low-Sag (HTLS) conductors, having non-linear behaviour with respect to temperature.

Integrated Optimization of Combined Generation and Transmission Expansion Planning Considering Bus Voltage Limits

A novel integrated optimization method is proposed to combine both generation and transmission line expansion problem considering bus voltage limit. Most of the existing researches on the combined generation and transmission expansion planning cannot consider bus voltages and reactive power flow limits because they are mostly based on the DC power flow model. In this paper the AC power flow model and nonlinear constraints related to reactive power are simplified and modified to improve the computation time and convergence. The proposed method has been successfully applied to Garver's six-bus system which is one of the most frequently used small scale sample systems to verify the transmission expansion method.

Novel Multiagent-Based Scheme for Voltage Control Coordination in Smart Grids

AbstractIn this paper, a new multiagent-based voltage control scheme is proposed. The algorithm dynamically adapts the settings of control devices, such as the automatic voltage regulator of generators, transformer with under-load tap changer, and flexible alternating current transmission systems (FACTS), to optimize operational objectives. The objectives are controlling the generator excitation current, reducing transmission power loss, maintaining voltage stability, and improving voltage profile. The constraint is to keep the technical capability limits of system equipment and the transmission line power-flow limits. Furthermore, the effect of load model on voltage control dynamics is addressed. Peer-to-peer device communication is developed to facilitate information exchange among agents. The proposed scheme coordinates the operation of installed voltage control devices on both low voltage and high voltage levels. A simulation test model is implemented using a parallel computing arrangement for a 30-bu...

Stochastic optimal power flow by multi-variate Edgeworth expansions

Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only steady-state variable limits have been used as security constraints. In many systems voltage stability and small-signal stability also play an important role in constraining the operation.Recently an extension of the stochastic optimal power flow formulation that included constraints for voltage stability as well as small-signal stability was proposed. This was done by approximating the voltage stability and small-signal stability constraint boundaries with second order approximations in parameter space. In this article an alternative solution method to this problem will be proposed. The new improved solution method, which is based on Edgeworth series expansions, is both more efficient and accurate.We also give details on convexity of the problem and discuss some computational issues.

A Multi-Objective Contingency Constrained Optimal Power Flow Based on Composite Security Index Using Genetic Algorithm and Newton Method

Market economic constraints in the deregulated environment may force the power system to operate closer to its security limits there by decreasing the overall security margins. Efforts are needed to check the security before a set of transactions is accepted and to take preventive or corrective control actions as soon as these are deemed insufficient. This paper proposes a multi-objective contingency constrained optimal power flow to enhance the system security as well as to ensure the economic operation of the system. In order to reduce the high dimensionality of contingency constrained optimal power flow, only the critical contingencies are identified with the help of the developed composite security index and the corresponding constraints are used for the problem formulation. The composite security index which is a function of both power flow and bus voltage limit violations gives an accurate differentiation between the secure and non-secure states of the power system. Weight based Genetic algorithm is used as the optimization tool and the results obtained are validated using the conventional Newton method of optimization. The effectiveness of the method is tested on a practical Indian utility 62 bus system.

Using Sprott Chaos Synchronization-Based Voltage Relays for Protection of Microdistribution Systems Against Faults

This paper proposes the use of Sprott chaos synchronization (SCS)-based voltage relays for fault protection in microdistribution systems (MDSs). The Sprott chaos system is used as a voltage detector to track the dynamic errors between the normal signal and disturbance signals. The proposed voltage relay is used to detect disturbances, such as serious voltage sag and swell, and uses a critical trigger time to isolate the fault section. It is proposed that the restoration strategy then restores the unfaulted but blackout zones, and confirms security operations, including load-power balance, power generation limits, voltage limits, and power-flow limits. Computer simulations are conducted by using an IEEE 30-bus power system and MDSs, to show the effectiveness of the proposed method.

Computational Analysis of Different Artificial Intelligence Based Optimization Techniques for Optimal Power Flow and Economic Load Dispatch Problem

The purpose of this paper is to present a computational Analysis of various Artificial Intelligence based optimization Techniques used to solve OPF problems. The various Artificial Intelligence methods such as Genetic Algorithm(GA), Particle Swarm Optimization(PSO), Bacterial Foraging Optimization(BFO), ANN are studied and analyzed in detail. The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost and transmission loss etc. or maximizes social welfare, load ability etc. while maintaining an acceptable system performance in terms of limits on generators’ real and reactive powers, power flow limits, output of various compensating devices etc. Traditionally, Classical optimization methods were used effectively to solve optimal power flow. But, recently due to the incorporation of FACTS devices and deregulation of power sector the traditional concepts and practices of power systems are superimposed by an economic market management and hence OPF have become more complex. So, in recent years, Artificial Intelligence (AI) methods have been emerged which can solve highly complex OPF problems at faster rate.