Modified IEEE 30-bus Test System Research Articles

Network-Constrained Transactive Coordination for Plug-In Electric Vehicles Participation in Real-Time Retail Electricity Markets

Uncoordinated adoption of plug-in electric vehicles (PEVs) imposes further load on the distribution network, and therefore may result in disruptive impacts on the grid. Transactive coordination of PEVs has been introduced as an effective approach to mitigate these negative consequences. This paper furthers efforts enabling PEVs to participate in a real-time retail electricity market under a transactive energy (TE) paradigm. In this regard, PEV owners will estimate their willingness to pay/accept using a user-friendly strategy and submit the estimated values to the retail market operator. Then using a network-constrained market clearing mechanism, the clearing prices, i.e., dual variables of active power balance constraints, will be calculated. Finally, these calculated clearing prices will be sent to whole PEVs and their actions have been determined. The proposed model is applied to the modified IEEE 33-bus test system combined with several low voltage feeders, and the results illustrate the effectiveness of the proposed model from viewpoints of PEV owners and utility.

Minimizing Wind Power Curtailment Using a Continuous-Time Risk-Based Model of Generating Units and Bulk Energy Storage

Wind power curtailment (WPC) occurs because of the non-correlation between wind power generation (WPG) and load, and also due to the fast sub-hourly variations of WPG. Recently, advances in energy storage technologies facilitate the use of bulk energy storage units (ESUs) to provide the ramping required to respond to fast sub-hourly variations of WPGs. To minimize the sub-hourly WPC probability, this paper addresses a generic continuous-time risk-based model for sub-hourly scheduling of energy generating units and bulk ESUs in the day-ahead unit commitment (UC) problem. Accordingly, the Bernstein polynomials are hosted to model the continuous-time risk-based UC problem with ESU constraints. Also, the proposed continuous-time risk-based model ensures that the generating units and ESUs track the sub-hourly variations of WPG, while the load and generation are balanced in each sub-hourly intervals. Finally, the performance of the proposed model is demonstrated by simulating the IEEE 24-bus Reliability and Modified IEEE 118-bus test systems.

Modeling and planning of smart buildings energy in power system considering demand response

The development of industry and the increasing of the energy demand in the today’s power system make it possible to maximize the potential of existing and renewable energy resources. On the other hand, using of these resources required efficient management and planning model, because without the adequate energy management, the power system cannot reach a high-performance model with maximum efficiency. Therefore, this paper first addresses the modeling of energy management in smart buildings having responsive/non-responsive devices and renewable photovoltaic resources. To manage the solar system employment, the KNX protocol is used. Also, the batteries are used in a way that they are charged at low power consumption and it will be as a generating unit during the peak-load time, therefore, the objective function is minimizing the power system loss and the related cost. Since the proposed model is nonlinear and has some complexity, the particle swarm algorithm (PSO) is used. To achieve the minimum losses, the best candidate buses are selected based on the proposed sensitivity analysis to manage the connected buildings. As a result, the function of the overall cost is based on the amount of energy produced and sold. Finally, the presented model is examined and evaluated on modified IEEE 30-bus test system based on the statistical analysis in different scenarios. Moreover, it is conclude from the planning that the operating cost significantly controls by the charge and discharge mechanism of the battery and the photovoltaic units.

Integrating Dynamic Line Rating in Security Constrained Optimal Power Flow Considering Wind Power Generation. (Dept. E )

Traditional optimal power flow (OPF) problem is solved considering static line rating (SLR) of the transmission lines which are constant values of power flow limits. This led to underutilization of the network and higher locational marginal prices (LMPs). Dynamic line rating (DLR) is one of the active solutions to enhance ampacity for overhead transmission lines (OHTL), especially with the penetration of high wind power without investing in an additional transmission line network. This paper investigates the effect of integrating the DLR on power dispatch with uncertainty levels due to renewable energy sources (RES) generation. The model propose is a multi-period security-constrained OPF based on particle swarm optimization (SCOPF/PSO) that takes into consideration the steady-state heat-balance equation (SS-HBE) of the OHTL and the ramp-up time of generation units. The problem is a multi-objective optimization one; the main objective is to maximize the social welfare (SW) by minimizing total system operation cost and maximizing the revenue from the energy consumers, whereas the second objective is to minimize the thermal emissions. To demonstrate the effectiveness of the proposed model, a case study is applied to the modified IEEE 30-bus test system. The results expound on the effectiveness of the proposed approach.

Multi‐stage risk‐based dispatch considering short‐term reliability of transmission lines

The reliability of transmission lines (TLs) has great influences on the safe operation of power systems. Random failures from TLs can be caused by multiple uncertainties such as the high load current. In this study, a multi-stage risk-based dispatch model is proposed to minimise the sum of generation cost and risk cost. Impacts of natural ageing, load current, health condition and disaster weather on the short-term reliability of TLs are studied. For ensuring the operation security of power systems in the post-contingency stage, the dynamic thermal rating (DTR) technology is implemented to improve capacities of TLs for coping with the potential overload. In order to solve this non-linear optimiation problem caused by load current-dependent failure probabilities and thermal rating constraints, a double-iteration solving strategy is proposed. In exterior iterations, the sequential linear programming is applied to decouple bilinear terms of the risk cost and locally linearise failure probabilities. Meanwhile, in interior iterations, the Benders decomposition is utilised to further divide the model into the main problem and the sub-problem for coordinating the preventive and corrective control and checking the feasibility of DTR, respectively. Proposed approaches are validated on a modified IEEE 24-bus test system.

A Novel Operational Model for Interconnected Microgrids Participation in Transactive Energy Market: A Hybrid IGDT/Stochastic Approach

Recently, the decarbonization of the electric power system has led to substantial efforts for designing a pathway toward 100% renewable energy resources (RERs). In this article, we propose a novel operational model for the effective participation of the interconnected microgrids with 100% RERs in the transactive energy market. The novelty of the proposed model is mostly related to the use of transactive energy technology for developing the free energy trading environment for the microgrids with 100% RERs as the local energy-trading market to establish a dynamic energy balance in the system. To capture the intermittencies in the system, a hybrid version of the stochastic programming and information gap decision theory (IGDT) method with the risk-averse and risk-seeker strategies is proposed in the deregulated environment. The proposed model is validated by selecting the modified IEEE 14-bus test system. The results indicate the effectiveness of the proposed model in providing the same percentage of cost-saving for microgrids when they simultaneously participate in the transaction energy market. The cooperative energy interactions of the microgrids in the transactive energy market based on the proposed model lead to 18.34% cost-saving for them in comparison with the base model.

Reliability Enhanced Multi-objective Economic Dispatch Strategy for Hybrid Renewable Energy System with Storage

An optimal dispatch strategy for the economic operation of hybrid renewable energy system with storage is presented in this paper. Solar photovoltaic (PV), Wind and Battery Storage are the prime components of interest constituting the hybrid system. In addition to the economic aspect of the systems, the formulation focuses on renewable prioritized operation, system reliability and environmental sustainability enhancement. Being a multi-objective (MO) problem, a modified non-dominated sorting particle swarm optimization is used for solving the problem, considering operational cost, pollutant emission, and expected energy not served as operational objectives. The non-dominated sorting particle swarm optimization (NSPSO) is augmented with crowding distance technique, stochastic weight trade-off and chaotic mutation approaches, to control the exploration of global and particle bests, alleviating premature convergence, and enhancing solution search capability. A two-stage approach is used to derive the best solution. A modified IEEE 30-bus test system is used to demonstrate the results. By using the proposed approach, a lower and wider Pareto front is obtained, in comparison with prominent optimization approaches.

Scenario-based probabilistic multi-stage optimization for transmission expansion planning incorporating wind generation integration

Integrated transmission expansion planning (TEP) and generation expansion planning (GEP) with Wind Farms (WFs) is addressed in this paper. The optimal number of expanded lines, the optimal capacity of WFs installed capacity, and the optimal capacity of wind farms lines (WFLs) are determined through a new TEP optimization model. Furthermore, the optimum capacity additions including conventional generating units is obtained in the proposed model. The Benders decomposition approach is used for solving the optimization problem, including a master problem and two sub-problems with internal scenario analysis. In order to reduce the computational burden of the multi-year and multi-objective expansion planning problem, a multi-stage framework is presented in this paper. The uncertainties of wind speed and system demand along with contingency scenarios lead to a probabilistic optimization problem. Moreover, in the proposed model, the planning time horizon is divided into three predefined stages. This multi-stage approach is used to increase the proposed model accuracy in a power system with a high level of wind power penetration. Hence, in this paper a scenario-based probabilistic multi-stage model for transmission expansion planning is proposed, incorporating optimal WFs integration. It is recognized that high wind penetration increases the transmission expansion investment cost, but based on the reduction of the investment cost of conventional units, the total system cost will be smaller. This result emphasizes the main advantage of wind generating system over the conventional generating system. This planning methodology is applied to the modified IEEE 24-bus test system and simplified Iran 400-kV real system to show the feasibility of the proposed algorithm.

Vulnerability Assessment for Power Transmission Lines under Typhoon Weather Based on a Cascading Failure State Transition Diagram

The analysis of the fault propagation path of transmission lines and the method of identification of vulnerable lines during typhoon weather conditions is of great significance. In this context, this paper introduces the failure probability model of transmission lines under such conditions by considering both wind speed and the load of the lines. The Monte Carlo simulation (MCS) and the DC model based on OPA are applied to simulate the failure of transmission lines. The cascading failure state transition diagram (CFSTD) is proposed based on the failure chains and the criticality ranking of nodes in CFSTD by the average weight coefficient (AWC) for identifying vulnerable lines of the power grid under such conditions. A new weight in CFSTD is proposed to describe the vulnerability of each line and a new resilience index is used to assess the impacts of a typhoon on the system. The proposed method is demonstrated by using the modified IEEE 118-bus test system. Results show that the method proposed in this paper can simulate the fault propagation path, and identify the critical components of power grid under a typhoon.

Optimal Allocation of FACTS Devices in Restructured Power Systems Integrated Wind Generation

This paper proposes an approach to optimally allocate flexible AC transmission system (FACTS) devices in market-based restructured power systems based on Expected Benefit (EB) and installation cost of FACTS devices (FDs). The aims of the approach are minimizing device investment cost, and the locational marginal pricing (LMP) differences between buses to maximize revenue. This revenue is defined as the difference between EB with and without FACTS installation. The expected cost includes operating cost not only under normal condition but also under contingencies along with their associated probabilities to occur. The proposed method accurately evaluates the annual cost and benefits obtainable by FACTS devices installation by formulating a large-scale optimization problem that contains power flow analyses for a large number of system states representing annual power system operations. The objectives for normal state are maximizing social welfare by minimizing LMPs differences between buses and minimizing of generations re-scheduling, while the objectives in case of contingency are maximizing social welfare as well as minimizing compensations paid for generations re-scheduling and load shedding cost. The overall problem is solved using both Particle Swarm optimization (PSO) for attaining optimal FACTS devices setting and allocation as main problem and optimal power flow to calculate the operating costs and benefits as sub optimization problem. The effectiveness of the proposed approach is demonstrated on modified IEEE 14-bus test system and IEEE 118-bus test system.

Analytically derived fixed termination time for stepwise inertial control of wind turbines—Part II: Application strategy

By applying stepwise inertial control (SIC) on wind turbines (WTs), a secure system frequency response after large active power imbalances in the system can be achieved. In Part I of this paper (Ding et al., submitted for publication), a novel approach for determining when to terminate the SIC is presented. In this context, a new analytical expression for a fixed termination time (FTT) is derived. In order to optimally implement the FTT concept, both the parameters of the system frequency response (SFR) model and the incremental power during the SIC process must be known. This paper is providing answers to these questions and furthermore proposes an advanced application strategy for the FTT concept. The new strategy improves the frequency nadirs and prevents the WTs’ rotor speed from violating the lower permissible limit during the SIC process. Using the least squares algorithm, the unknown SFR model parameters are estimated from the frequency measured at the point of common coupling (PCC) of the wind farm. The incremental active power is determined considering the effect of the incremental power on the frequency nadirs and the releasable kinetic energy of the WTs. The performance of the proposed new application strategy is verified using a modified IEEE 39-bus test system.

Use of Hybrid Phase Shifter for Congestion Management in A Grid with RESs and EVs: Transmission Efficiency Benefit in Comparison with Phase Shifting Transformer

Integration of renewable energy sources (RESs) and electric vehicles (EVs) to electric power grids is increasing. These RESs and EVs may introduce major problems to grid such as transmission lines congestion. Owing to the causative factors nature, congestion may regularly happen and continue forlong commulative time. Thus, transmission efficiency (TE) is a major factorwhen relieving congestion. Congestion can be relieved by using phase shifting transformers (PSTs), hybrid phase shifters (HPSs), or flexible AC transmission system (FACTS) devices. However, PSTs have technical drawbacks such as their large steps, which may result in increased losses, and FACTS devices cost is high. This paper investigates benefits of using an HPS rather than a PST in terms of TE. As HPS operates continuously, it provides more precise control of active power flow than PST. A modified IEEE-14 bus test system is used and a security margin is kept in each simulated case with HPS/PST. Results revealed higher TE when an HPS is used. Thus, RESs and EVs can be more optimally hosted with HPSs.

A multi-period scheduling strategy for ADN considering the reactive power adjustment ability of DES

Nowadays, the active distribution network (ADN) is facing great challenges on safe operation and coordinated scheduling. To resolve these issues, a novel multi-period active-reactive coordination scheduling strategy efficient solution method is proposed in this paper after addressing the uncertainty of DG and load by probabilistic scenario method. Firstly, based on the second-order cone relaxation (SOCR), the power flow equations are convexized and relaxed to transform the original model into mixed integer second-order cone programming (MISOCP). Then, the controllable resources such as on-load tap changer (OLTC), capacitor banks (CB) and ESS are accurately linearized, so the model is converted to 0–1 MISOCP problem. Finally, compared with the existing strategies, numerical tests on the modified IEEE 33-bus test system demonstrate that on the premise of realizing the maximum utilization of DG, the proposed strategy can also achieve the purposes of energy-saving, loss reduction and improvement in voltage level and the utilization of ESS. Meanwhile, the accuracy and efficiency of the 0–1 MISOCP model are verified through four operating schemes. In addition, the sensitivity analysis of adjustment step and action time of the discrete adjustment devices on optimization results is carried out in detail.

Integrated transmission expansion and PMU planning considering dynamic thermal rating in uncertain environment

Dynamic line rating (DLR) technologies are fast becoming a key instrument in power systems with high penetration of wind farms, because power companies can reduce the value of wind power spillage and also can postpone the investments of transmission lines by using DLR equipment. However, what the authors know about DLR is largely based on empirical studies that investigate how to change the capacity of transmission lines with changing the weather data. Therefore, lack of a mathematical model for estimating the capacity of lines by considering the weather conditions across the line and wind farm generations can be accounted as a research gap of DLR problems. This study proposes a solution for transmission expansion planning considering DLR technologies. Also, this study seeks to develop a model, which will help to address the research gap of DLR problems. The geostatistical analysis is used to develop a mathematical model, which can provide the relationship between wind farms as well as the capacity of lines calculated based on the weather conditions across the line. The efficiency of the proposed model is examined on a modified IEEE 118-bus test system.

Optimal power flow by means of improved adaptive differential evolution

Optimal power flow (OPF) problem is a large-scale, non-convex, multi-modal, and non-linear constrained optimization problem, which has been widely used in power system operation. Because of these features, solving the OPF problem is a very popular and challenging task in power system optimization. In recent years, many advanced optimization methods are employed to deal with the OPF problem. However, most of these methods are unconstrained. In this paper, an enhanced adaptive differential evolution (JADE) with self-adaptive penalty constraint handling technique, referred to as EJADE-SP, is proposed to obtain the optimal solution of the OPF problem. The EJADE-SP is an enhanced version of JADE, where four improvements are proposed to enhance the performance of JADE when solving the OPF problem: i) crossover rate (CR) sorting mechanism is introduced to allow individuals to inherit more good genes; ii) re-randomizing parameters (CR and scale factor F) to maintain the search efficiency and diversity; iii) dynamic population reduction strategy is used to accelerate convergence; and iv) self-adaptive penalty constraint handling technique is integrated to deal with the constraints. To verify the effectiveness of the proposed method, it is applied to the OPF problem on a modified IEEE 30-bus test system, which combines stochastic wind energy and solar energy with conventional thermal power generators. The simulation results demonstrate that the proposed approach can be an effective alternative for the OPF problem.

Adaptive protection scheme for microgrids based on SOM clustering technique

Microgrids are penetrating into the power systems at an unprecedented rate. The reason is the mutual economic and environmental benefits of microgrids, both for power grid utility and the consumers. Some special features of microgrids such as, the two main operational conditions called, islanded and grid-connected modes, and being composed of various types of distributed energy resources along with different uncertainties cause some tough challenges to protection and control systems. From the protection aspect, the coordination of overcurrent relays protection will become a difficulty, due to the extensive changes in the fault current levels sensed by these devices. In this paper, a new adaptive protection coordination scheme based on Self-Organizing Map (SOM) clustering algorithm is proposed for digital overcurrent relays equipped with several setting groups. Considering the similarity of mis-coordinated relay pairs for the clustering purpose, the proposed protection scheme focuses on solving the mis-coordination between main/backup relay pairs. As a case study, a modified IEEE 33-bus test system is used as a microgrid. In the case study, a synchronous distributed generation and two electric vehicle charging stations are installed. The results suggest that not only the proposed method is fully capable and flexible to significantly improve the mis-coordination of overcurrent relay pairs, but it can also ameliorate the operating time of relay.

Using Dynamic Thermal Rating and Energy Storage Systems Technologies Simultaneously for Optimal Integration and Utilization of Renewable Energy Sources

Nowadays, optimal integration and utilization of renewable energy sources (RES) are of the most challenging issues in power systems. The wind and solar generation units' maximum production may or may not occur at peak consumption times resulting in non-optimal utilization of these resources. As a solution to this problem, energy storage systems (ESS) are embedded in networks. However, the power transfer from RES to ESS may lead to network congestion. In this paper, the simultaneous application of dynamic thermal rating (DTR) technology and ESS devices is proposed. The DTR is used to overcome the problem of transmission lines limited capacity and ESS is responsible for mitigating curtailment of RESs energy production by saving their generated energy in non-peak hours. The RESs generation and lines’ ratings are calculated based on hourly actual weather elements. For evaluating the proposed method, a linearized formulation of DC-OPF is used in the problem definition and also simulated on a modified IEEE 30-bus test system including a wind farm, solar park, and ESS devices by using MATLAB software. In addition, different comparisons are performed demonstrating the remarkable and better performance of the proposed method compared to previously introduced methods.

Coordinated Planning With Predetermined Renewable Energy Generation Targets Using Extended Two-Stage Robust Optimization

Coordinated planning is an effective method to balance investment costs and benefits in achieving high renewable target under the renewable-driven power system expansion wave. This paper proposes a coordinated planning model to support the efficient achievement of renewable target considering economy of the system by accounting for the interaction among source, grid, and energy storage system. An adaptive two-stage min-max-min robust optimization model is formulated to take into account renewable target as well as the uncertainty associated with renewable production and load demand. To reduce the conservatism of robust optimization, uncertain budget, multiple uncertain sets, and data-driven method are used to design uncertain sets. The resulting model is transformed into a tractable bi-level programming through strong duality theory and big-M method. A customized column-and-constraint generation algorithm is used to solve the bi-level programming. Simulation results presented for the modified IEEE 30-bus test system corroborates the effectiveness of the methodology, which finds siting and sizing of renewable energy sources and energy storage systems as well as transmission expansion schemes. It is capable to provide a flexible planning tool driven by renewable target under a reasonable computational burden.

Enhancing Hosting Capacity of Uncertain and Correlated Wind Power in Distribution Network With ANM Strategies

To settle the large-scale integration of wind power, it is necessary to enhance the wind power hosting capacity of distribution network. To this end, this paper proposes a stochastic mixed-integer linear programming (MILP) model to enhance the hosting capacity of distribution network with active network management (ANM) strategies. The considered ANM strategies include power factor control, reactive power compensation and network reconfiguration. The coordination of these strategies enables the distribution network to accommodate more wind power without violating its constraints. The proposed model relaxes the original nonlinear power flow equations into linear format, so that a near optimal solution can be obtained with moderate computational burden. The wind power and load demand are inherently variable due to the influence of various factors. Moreover, the output powers of multiple wind turbines (WTs) located at adjacent sites of a wind farm are spatially correlated. To represent the uncertain loads, the roulette wheel mechanism is used to generate the load samples. In addition, a combined method of inverse transformation and Nataf transformation is established to deal with the uncertain and correlated wind power. Then, scenario combination and reduction are conducted to generate representative scenarios. Finally, the feasibility and accuracy of the proposed method are verified via numerical tests on the modified IEEE 33-bus test system.

Using Microgrids for Critical Load Restoration in Distribution Systems

Abstract This paper proposes a restoration strategy using microgrids to restore power to critical loads to enhance distribution system resilience after an extreme event. The restoration problem is posed as an optimization problem to maximize the number of critical loads restored after the extreme event has resulted into multiple faults. After the fault, the restoration strategy alters the topological structure of the distribution network by removing the faulted lines and applies minimum spanning tree algorithm to find a possible topology that will be used for the restoration. The service time to the restored critical loads is incorporated as one of the constraints to ensure continuous supply for the duration of the outage. The problem is modeled as a mixed-integer linear program (MILP) and solved using the CPLEX solver on the MATLAB platform. The effectiveness of the proposed restoration strategy is validated using the modified IEEE 33-bus test system under multiple fault scenarios that represent damage resulted from the extreme event.