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Wind penetration is expected to reach substantially higher levels of penetration in the near future. A variable speed wind turbine generator, such as, the doubly-fed induction generator (DFIG) or the permanent magnet synchronous generator, does not naturally provide rotating inertia due to the converter interface, which leads to a reduction of the overall system inertial response. The replacement of the conventional generators which have governors also reduces primary frequency control capability. Multiple control strategies have been proposed to enable a DFIG to provide emulated inertial response through reducing rotor speed that can release some kinetic energy. However, this has no effect on primary settling frequency and may even bring a secondary frequency dip to the system due to rotor speed recovery. Moreover, the rotor speed is not guaranteed to stay in an allowable range during the reduction period. This paper proposes a new control strategy for DFIG to provide adequate inertial response with guaranteed rotor security. To mitigate the potential of the secondary frequency dip and improve the performance of primary frequency control, a dynamic demand control strategy is proposed to coordinate with DFIG control. The coordination strategy can provide fast frequency support from the time-scale of inertial response through primary frequency control. The proposed control can be realized in both small-scale and large-scale power systems. [ABSTRACT FROM AUTHOR]

Due to growing environmental concerns, wind power has taken a larger share of the generation market. While the increase in wind generation provides diversification of the supply, it also undermines system reliability by introducing uncertainty in power supply and decreasing the maneuverability of the grid in terms of VAR absorbance and provision. To restore the reliability of high wind penetrated systems, this paper proposes hierarchical voltage control (HVC). The proposed pattern generalization methodology is based on principle component analysis and a three-layer feedback architecture utilizing online state estimation. The proposed control includes both steady-state and dynamic constraints. Governed by an optimization trained with cases representing operating snapshots and solved via an active-set algorithm adopting stepwise linearization, the proposed HVC provides efficiency and adaptability. As a result, the proposed control provides adequate system support under a wide range of contingencies and operating conditions to enhance grid reliability. Its capability to regulate yearly round operations in real time is validated using a reduced Western Electricity Coordinating Council power system model. [ABSTRACT FROM AUTHOR]

Series flexible AC transmission systems devices, such as the variable series reactor, have the ability to continuously regulate the transmission line reactance so as to control power flow. This study presents a new approach to optimally locating such devices in the transmission network considering multiple operating states and contingencies. To investigate optimal investment, a single target year planning with three different load patterns is considered. The transmission contingencies may occur under any of the three load conditions and the coupling constraints between base case and contingencies are included. A reformulation technique transforms the original mixed integer non-linear programming model into mixed integer linear programming model. To further relieve the computational burden and enable the planning model to be directly applied to practical large-scale systems, a two-phase decomposition algorithm is introduced. Detailed numerical simulation results on IEEE 118-bus system and the Polish 2383-bus system illustrate the efficient performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Series flexible AC transmission systems devices, such as the variable series reactor, have the ability to continuously regulate the transmission line reactance so as to control power flow. This study presents a new approach to optimally locating such devices in the transmission network considering multiple operating states and contingencies. To investigate optimal investment, a single target year planning with three different load patterns is considered. The transmission contingencies may occur under any of the three load conditions and the coupling constraints between base case and contingencies are included. A reformulation technique transforms the original mixed integer non‐linear programming model into mixed integer linear programming model. To further relieve the computational burden and enable the planning model to be directly applied to practical large‐scale systems, a two‐phase decomposition algorithm is introduced. Detailed numerical simulation results on IEEE 118‐bus system and the Polish 2383‐bus system illustrate the efficient performance of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Use of actuator redundancy to achieve higher reliability is a widely accepted engineering design technique and is used in this study to build resiliency and ensure power system stability in the presence of high levels of renewables. This paper presents a new design method for fault-tolerant wide-area damping controllers (WADCs) using modal-based control allocation (MB-CA), which coordinates a set of actuators to contribute to damping of inter-area oscillations. In our proposed method, when an actuator fails or is unavailable (e.g., due to communication failure), the supervisory MB-CA distributes the control signals to the remaining healthy actuators based on effects on the modal system, desired control actions, and actuator constraints. Our proposed block offers the benefits of modular design where it is independent of the nominal WADC. The proposed method consists of mainly two design steps. The first step is to design a WADC based on a fault-free model using robust control methods. The second step is to design an MB-CA to manage actuator availability and constraints. To validate the feasibility and demonstrate the design principles, a set of comprehensive case studies are conducted on a modified 192-bus Western Electricity Coordinating Council system. Numerical results verify the effectiveness of the proposed approach in ensuring resiliency to different actuator failures and actuator availability. [ABSTRACT FROM PUBLISHER]

This paper introduces a continuously variable series reactor (CVSR) to the transmission expansion planning (TEP) problem. The CVSR is a flexible ac transmission system (FACTS)-like device, which has the capability of controlling the overall impedance of the transmission line. However, the cost of the CVSR is about one-tenth of a similar rated FACTS device, which potentially allows large numbers of devices to be installed. The multi-stage TEP with the CVSR considering the $N-1$ security constraints is formulated as a mixed-integer linear programming model. The nonlinear part of the power flow introduced by the variable reactance is linearized by a reformulation technique. To reduce the computational burden for a practical large-scale system, a decomposition approach is proposed. The detailed simulation results on the IEEE 24-bus and a more practical Polish 2383-bus system demonstrate the effectiveness of the approach. Moreover, the appropriately allocated CVSRs add flexibility to the TEP problem and allow reduced planning costs. Although the proposed decomposition approach cannot guarantee global optimality, a high-level picture of how the network can be planned reliably and economically considering CVSR is achieved. [ABSTRACT FROM PUBLISHER]

There are two general categories of demand response (DR): price-based and incentive-based DR programs. Each one has its own benefits taking advantage of different aspects of flexible demand. In this paper, both categories of DR are modeled based on the demand-price elasticity concept to design an optimum scheme for achieving the maximum benefit of DR. The objective is to not only reduce costs and improve reliability but also to increase customer acceptance of a DR program by limiting price volatility. Time of use (TOU) programs are considered for a price-based scheme designed using a monthly peak and off-peak tariff. For the incentive-based DR, a novel optimization is proposed that in addition to calculation of an adequate and a reasonable amount of load change for the incentive, the best times to realize the DR is found. This optimum threshold maximizes benefit considering the comfort level of customers as a constraint. Results from a reduced model of the WECC show the proposed DR program leads to a significant benefit for both the load serving entities (LSEs) and savings in customer's electricity payment. It also reduces both the average and standard deviation of the monthly locational marginal price (LMP). The proposed DR scheme maintains simplicity for a small customer to follow and for LSEs to implement. [ABSTRACT FROM AUTHOR]

This article presents a magnetic amplifier-based power flow controller as a new approach to control power flow based on a magnetically saturated reactor concept. The magnetic amplifier-based power flow controller uses the magnetic field as control medium to decrease the operating energy losses and increase system reliability. By providing continuous impedance, the magnetic amplifier-based power flow controller can suppress the inter-area oscillation and improve the system stability. A model of magnetic amplifier-based power flow controller is built and verified by lab experiments. A control strategy implementing the magnetic amplifier-based power flow controller is proposed to demonstrate the application of this new device to damp low-frequency oscillation in an interconnected power system. A comparative analysis of the controller's performance is carried out and incorporated with various input signals and multiple loading conditions. The simulations are conducted by power systems CAD (PSCAD, Manitoba Hydro International Ltd., Winnipeg, Canada). The results show the effectiveness of the controller in damping inter-area oscillations. [ABSTRACT FROM AUTHOR]

In this study, implementation of flatness-based control on doubly fed induction generator (DFIG) is investigated. Flatness-based approach is well adopted to control systems in two-level control structure where the tasks of planning, trajectory generation, and tracking the desired trajectories can be easily separated. As a result, the system is decoupled into two trivial linear systems. While in vector control the trajectories are found using PI controllers, in the proposed control structure the trajectories are computed directly, through algebraic equations. Desired active and reactive power are used to develop the set points for trajectory generation. Tracking of the desired trajectories is guaranteed through feedback linearization. The two-level control structure enables active power control and the opportunity for wind plants to contribute in frequency regulation. The proposed control shows promising results in tracking the desired reactive power and the active power across a variety of scenarios and in providing ancillary service to support the frequency regulation of the grid. [ABSTRACT FROM AUTHOR]

A shortage of U.S. trained power and energy engineers has been predicted in the near future. One approach to solve this problem involves increasing the number of students choosing to study engineering, especially by exposing more students to engineering at an early age, even before high school. This paper presents the curricula and assessment of two summer programs for middle and high school students. We introduced electric and renewable energy concepts, engineering design, and MicroGrid related projects to the students. The survey results indicate that both programs improved students' levels of engineering knowledge, interest in learning and participating in engineering projects, and their intention to choose an engineering career; however, students' confidence in succeeding in engineering or science did not show improvement, which may impact students' willingness to choose engineering as a major. A positive attitude towards engineering among high school students had improved after the program but not among the middle school group. Improving the image of electrical engineering in general, and power systems engineering in particular, remains a challenge. [ABSTRACT FROM PUBLISHER]

To allow for high penetration of distributed generation and alternative energy units, it is critical to minimize the complexity of generator controls and the need for close coordination across regions. We propose that existing controls be replaced by a two-tier structure of local control operating within a global context of situational awareness. Flatness as an extension of controllability for nonlinear systems is a key to enable planning and optimization at various levels of the grid in this structure. In this study, flatness-based control for automatic generation control (AGC) of a multi-machine system with high penetration of wind energy is investigated. The local control tracks the reference phase which is obtained through economic dispatch at the global control level. As a result of applying the flatness-based method, the n machine system is decoupled into n linear controllable systems in canonical form. Therefore, the control strategy results in a distributed AGC formulation which is significantly easier to design and implement compared to conventional AGC. Practical constraints such as generator ramping rates can be considered in designing the local controllers. The proposed strategy demonstrates promising performance in mitigating frequency deviations and the overall structure could facilitate operation of other nontraditional generators. [ABSTRACT FROM PUBLISHER]

The traditional unit commitment and economic dispatch approaches with deterministic spinning reserve requirements are inadequate given the intermittency and unpredictability of wind power generation. Alternative power system scheduling methods capable of aggregating the uncertainty of wind power, while maintaining reliable and economic performance, need to be investigated. In this paper, a probabilistic model of security-constrained unit commitment is proposed to minimize the cost of energy, spinning reserve and possible loss of load. A new formulation of expected energy not served considering the probability distribution of forecast errors of wind and load, as well as outage replacement rates of various generators is presented. The proposed method is solved by mixed integer linear programming. Numerical simulations on the IEEE Reliability Test System show the effectiveness of the method. The relationships of uncertainties and required spinning reserves are verified. [ABSTRACT FROM PUBLISHER]

Abstract: This paper addresses the problem introduced by the slack bus in load flow solutions with uncertain nodal powers. While balancing powers in the system the slack bus will also absorb all uncertainty. The results obtained are of no practical interest unless realistic constraints are imposed on slack power production/consumption. Two methods of dealing with these constraints are investigated suitable for implementation within the recently developed boundary load flow. [Copyright &y& Elsevier]

Abstract: One of the fundamental tenets in deregulation of the power system is to provide fair and open access to transmission facilities. This requires that market participants, both power brokers and generation companies, have complete and timely information as to the transmission availability. The present system of posting available transmission capacities (ATC) is useful but limited because there is no information to predict how these ATCs will change with changing power transfers. It has been proposed that all traders have access to the real-time data of the full transmission model, i.e., state estimator results from the control centers, but this may be too complex and voluminous to be useful to the traders. Instead, making DC power flow data for real-time conditions may provide enough transmission data for traders to make knowledgeable decisions. In this paper, we show how the results of a DC state estimator can be accurately made available to all concerned. [Copyright &y& Elsevier]

In this paper, the numerical analysis of a multistage formulation of the distribution expansion problem developed is presented. The approximate objective function is employed without sacrificing optimality. A complete nonlinear mathematical programming optimization is employed to identify the global optimum. The algorithm is applied here to two practical test cases. Details of the input data and configuration of test systems as well as the solutions are listed and discussed. Computational considerations are addressed. [ABSTRACT FROM AUTHOR]

In this paper, the objectives and detailed analysis of the multistage distribution expansion are presented. The problem is modeled as a directed graph minimum edge cost network flow problem. This new formulation details a multistage framework within a single mathematical program while addressing several deficiencies of previous approaches. The accuracy of a single step approximation of the objective function, without using the conventional linearization techniques, is discussed. Each of the constraints is introduced in terms of industry standard practices. Detailed numerical results for practical study cases are provided in a separate paper. [ABSTRACT FROM AUTHOR]

With deregulation of the power generation sector, the necessity for an enhanced and open communication infrastructure to support an increasing variety of ancillary services is apparent. A duplex and distributed communication system seems to be the most suitable solution to meet and ensure good quality of these services. Parameters needed and additional limits introduced by this new communication topology must be investigated and defined. This paper focuses on the communication network requirements for a third party load frequency control service. Data communication models are proposed based on queuing theory. Simulation is performed to model the effects of certain types of signal delays on this ancillary service. [ABSTRACT FROM AUTHOR]

Considers congestion influence on bidding strategies in an electricity market. Hierarchical model of bidding process; Solution method; Numerical results; Conclusion.

Presents information on a study which characterized the price behavior in the electricity industry in California. Background on the hourly-unconstrained market clearing prices; Methodology of the study; Results and discussion.

Discusses optimal trade-offs in distribution protection design. Goal programming; Fuzzy goal programming; Formulation.

With the recent proliferation of open-source packages for computing, power system differential-algebraic equation (DAE) modeling and simulation are being revisited to reduce the programming efforts. Existing open-source tools require manual efforts to develop code for numerical equations, sparse Jacobians, and discontinuous components. This paper proposes a hybrid symbolic-numeric framework, exemplified by an open-source Python-based library ANDES, which consists of a symbolic layer for descriptive modeling and a numeric layer for vector-based numerical computation. This method enables the implementation of DAE models by mixing and matching modeling components, through which models are described. In the framework, a rich set of discontinuous components and standard transfer function blocks are provided besides essential modeling elements for rapid modeling. ANDES can automatically generate robust and fast numerical simulation code, as well as and high-quality documentation. Case studies present a) two implementations of turbine governor model TGOV1, b) power flow computation time break down for MATPOWER systems, c) validation of time-domain simulation with commercial software using three test systems with a variety of models, and d) the full eigenvalue analysis for Kundur's system. Validation shows that ANDES closely matches the commercial tool DSATools for power flow, time-domain simulation, and eigenvalue analysis. [ABSTRACT FROM AUTHOR]

This paper investigates the stability problem of wide-area damping controllers with intermittent information transmission. Due to the interruption in communication links between remote measurements and damping controller or from the damping controller to the damping actuators, the closed-loop system might become unstable. The instability is strongly related to the duration of interruption of information transmission. To estimate instability, this paper formulates the problem as continuous/discrete-time switched system and the stability conditions are derived using time-scale theory. This method allows us to handle continuous and discrete dynamics as two pieces of the same framework, such that the system will switch between a continuous-time subsystem (when the communication occurs without any interruption) and a discrete-time subsystem (when the communication fails). The contribution is to estimate the maximum allowable value of the time of interruption of information transmission that does not violate the exponential stability of the closed-loop system. The findings are useful in specifying the minimum requirements for communication infrastructure and the time to activate remedial action schemes. Simulations are performed based on both linear and nonlinear systems to validate the theoretical development. [ABSTRACT FROM AUTHOR]

Inadequate frequency response can arise due to a high penetration of wind turbine generators (WTGs) and requires a frequency support function to be integrated in the WTG. The appropriate design for these controllers to ensure adequate response has not been investigated thoroughly. In this paper, a safety supervisory control (SSC) is proposed to synthesize the supportive modes in WTGs to guarantee performance. The concept, region of safety (ROS), is stated for safe switching synthesis. An optimization formula is proposed to calculate the largest ROS. By assuming a polynomial structure, the problem can be solved by a sum of squares program. A feasible result will generate a polynomial, the zero sublevel set of which represents the ROS and is employed as the safety supervisor. A decentralized communication architecture is proposed for small-scale systems. Moreover, a scheduling loop is suggested so that the supervisor updates its boundary with respect to the renewable penetration level to be robust with respect to variations in system inertia. The proposed controller is first verified on a single-machine three-phase nonlinear microgrid, and then implemented on the IEEE 39-bus system. Both results indicate that the proposed framework and control configuration can guarantee adequate response without excessive conservativeness. [ABSTRACT FROM AUTHOR]

A power distribution system operates most efficiently with voltage deviations along a feeder kept to a minimum and must ensure all voltages remain within specified limits. Recently with the increased integration of photovoltaics, the variable power output has led to increased voltage fluctuations and violation of operating limits. This paper proposes an optimization model based on a recently developed heuristic search method, grey wolf optimization, to coordinate the various distribution controllers. Several different case studies on IEEE 33 and 69 bus test systems modified by including tap changing transformers, capacitors and photovoltaic solar panels are performed. Simulation results are compared to two other heuristic-based optimization methods: harmony search and differential evolution. The simulation results show the effectiveness of the method and indicate the usage of reactive power outputs of PVs facilitates better voltage magnitude profile. [ABSTRACT FROM AUTHOR]

A key component to understanding demand response programs design is elasticity, which reflects customer reaction to economic offers. In this work, customer elasticity for Incentive Based Demand Response (IBDR) programs is estimated using data from two nation wide surveys and integrated with a detailed residential load model. In addition, incentive based elasticity is calculated at the individual appliance level since this is more effective for operations than at an aggregate value for a feeder. The concept of appliance base elasticity is derived from various contributions of each appliance in the aggregate load signal and the necessity of use for the customer. Results show that the needed customer incentive for certain loads, such as, lighting and washing is less than HVAC, but since the HVAC energy share in total load is much higher generally, it has greater elasticity. Considering the important role of HVAC in the aggregate load signal, the elasticity is studied in more detail using estimates of different thermostat settings. Analysis shows that elasticity of HVAC decreases while average power increases. To disaggregate the load signal for each appliance, a constrained non-negative matrix factorization (CNMF) method is proposed. In addition, this method is used to decompose the HVAC signal to identify different thermostat settings. [ABSTRACT FROM AUTHOR]

In this paper, we study the stabilization properties of Continuous/Discrete switched systems using the dwell time approaches. The considered system switches between a continuous-time subsystem evolving on time intervals with variable lengths and a discrete-time subsystem with variable discrete step sizes. Since the time domain is non-uniform, and the stability of the discrete-time subsystem with variable discrete step sizes does not depend only on the dynamic of the system, but also on the length of the discrete steps, the usual conditions of dwell time approaches may not be applicable to stabilize this special class of switched systems. Motivated by that, stabilizing dwell time and average dwell time conditions are derived by introducing the time scales theory and numerical examples are proposed to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

An MILP-based distributed energy management for the coordination of networked microgrids is proposed in this paper. Multiple microgrids and the utility grid are coordinated through iteratively adjusted price signals. Based on the price signals received, the microgrid controllers (MCs) and distribution management system (DMS) update their schedules separately. Then, the price signals are updated according to the generation–load mismatch and distributed to MCs and DMS for the next iteration. The iteration continues until the generation–load mismatch is small enough, i.e., the generation and load are balanced under agreed price signals. Through the proposed distributed energy management, various microgrids and the utility grid with different economic, resilient, emission and socio-economic objectives are coordinated with generation–load balance guaranteed and the microgrid customers' privacy preserved. In particular, a piecewise linearization technique is employed to approximate the augmented Lagrange term in the alternating direction method of multipliers (ADMM) algorithm. Thus, the subproblems are transformed into mixed integer linear programming (MILP) problems and efficiently solved by open-source MILP solvers, which would accelerate the adoption and deployment of microgrids and promote clean energy. The proposed MILP-based distributed energy management is demonstrated through various case studies on a networked microgrids test system with three microgrids. [ABSTRACT FROM AUTHOR]

In this work, we present a three-stage multiobjective mixed-integer linear programming (MILP) for the optimal expansion planning and operation of isolated multienergy microgrids in remote areas. By selecting the optimal distributed generators (DGs) and energy storage systems (ESSs) mix selection, siting, sizing, and scheduling in the remote microgrid, the proposed model is targeted to minimize the annualized total cost of microgrids while enhancing the performance of the system, i.e., minimizing the voltage deviations and line power loss. To represent the electricity and heat flow between generation resources and various electrical, heating, and cooling loads in the isolated microgrid, linearized power flow, and heat flow constraints are employed in the proposed optimization model. The available capacity of DGs and ESSs are modeled as discrete constants instead of continuous variables for practical purpose. Numerical simulation results on a remote microgrid consisting of DGs, ESSs, and various loads validate the proposed method. [ABSTRACT FROM AUTHOR]

The benefits of networked microgrids in terms of economics and resilience are investigated and validated in this work. Considering the stochastic unintentional islanding conditions and conventional forecast errors of both renewable generation and loads, a two-stage adaptive robust optimization is proposed to minimize the total operating cost of networked microgrids in the worst scenario of the modeled uncertainties. By coordinating the dispatch of distributed energy resources (DERs) and responsive demand among networked microgrids, the total operating cost is minimized, which includes the start-up and shut-down cost of distributed generators (DGs), the operation and maintenance (O&M) cost of DGs, the cost of buying/selling power from/to the utility grid, the degradation cost of energy storage systems (ESSs), and the cost associated with load shedding. The proposed optimization is solved with the column and constraint generation (C&CG) algorithm. The results of case studies demonstrate the advantages of networked microgrids over independent microgrids in terms of reducing total operating cost and improving the resilience of power supply. [ABSTRACT FROM AUTHOR]

Wind generation has gained widespread use as a renewable energy source. Most wind turbines and other renewables connected to the grid through converters result in a reduction in the natural inertial response to grid frequency changes. The doubly-fed induction generator (DFIG) can be controlled to compensate for this reduction and, in fact, provide faster response than traditional synchronous machines. This paper proposes to design observer based output feedback linear quadratic regulator (LQR) and $H_{\infty }$ control laws to realize the inertia emulation function and deliver fast frequency support. The aim is to track the reference speed by a diesel synchronous generator (DSG) in order to reach the desired inertia. The control signal is computed based on a reduced order model using the balanced truncation technique. A comparison with selective modal analysis (SMA) and balanced truncation model reduction techniques is presented. Comprehensive results show the effective emulation of synthetic inertia by implementing the control laws on a nonlinear three-phase diesel-wind system. The proposed technique is analyzed for different short circuit ratio (SCR) scenarios. [ABSTRACT FROM AUTHOR]

Abstract: Critical Load Levels (CLLs) are load levels at which a new binding or non-binding constraint occurs. Successful prediction of CLLs is very useful for identifying congestion and price change patterns. This paper extends the existing work to completely solve the problem of predicting the Previous CLL and Next CLL around the present operating point for an AC Optimal Power Flow (ACOPF) framework. First, quadratic variation patterns of system statuses such as generator dispatches, line flows, and Lagrange multipliers associated with binding constraints with respect to load changes are revealed through a numerical study of polynomial curve-fitting. Second, in order to reduce the intensive computation with the quadratic curve-fitting approach in calculating the coefficients of the quadratic pattern, an algorithm based on three-point quadratic extrapolation is presented to get the coefficients. A heuristic algorithm is introduced to seek three load levels needed by the quadratic extrapolation approach. The proposed approach can predict not only the CLLs, but also the important changes in system statuses such as new congestion and congestion relief. The high efficiency and accuracy of the proposed approach is demonstrated on a PJM 5-bus system and the IEEE 118-bus system. [Copyright &y& Elsevier]

Presents a study which examined the feasibility of a bilateral market for load following in the electric industry. Method of the study; Results and discussion; Conclusion.

In this study, a distributed energy management for community microgrids considering phase balancing and peak shaving is proposed. In each iteration, the house energy management system (HEMS) installed in each house minimises its electricity costs and the costs associated with the discomfort of customers due to deviations in indoor temperature from customers' set points. At the community level, the microgrid central controller (MCC) schedules the distributed energy resources (DERs) and energy storage based on the received load profiles from customers and the forecast energy price at the point of common coupling. The MCC updates the energy price for each phase based on the amount of unbalanced power between generation and consumption. The updated energy price and unbalanced power for each phase are distributed to the HEMSs on corresponding phases. When the optimisation converges, the unbalanced power of each phase is close to zero. Meanwhile, the schedules of DERs, energy storage systems and the energy consumption of each house are determined by the MCC and HEMSs, separately. In particular, the phase balancing and peak shaving are considered in the proposed distributed energy management model. The effectiveness of the proposed distributed energy management has been demonstrated by case studies. [ABSTRACT FROM AUTHOR]

In this study, a distributed energy management for community microgrids considering phase balancing and peak shaving is proposed. In each iteration, the house energy management system (HEMS) installed in each house minimises its electricity costs and the costs associated with the discomfort of customers due to deviations in indoor temperature from customers' set points. At the community level, the microgrid central controller (MCC) schedules the distributed energy resources (DERs) and energy storage based on the received load profiles from customers and the forecast energy price at the point of common coupling. The MCC updates the energy price for each phase based on the amount of unbalanced power between generation and consumption. The updated energy price and unbalanced power for each phase are distributed to the HEMSs on corresponding phases. When the optimisation converges, the unbalanced power of each phase is close to zero. Meanwhile, the schedules of DERs, energy storage systems and the energy consumption of each house are determined by the MCC and HEMSs, separately. In particular, the phase balancing and peak shaving are considered in the proposed distributed energy management model. The effectiveness of the proposed distributed energy management has been demonstrated by case studies. [ABSTRACT FROM AUTHOR]

Highlights • A distributed, privacy-preserving microgrid energy management system is proposed. • Price signal is used to guide the decision making of system operator and customers. • Thermal dynamic model of houses is considered to enable intelligent load control. • The integration of network power flow constraints leads to locational energy price. Abstract A distributed energy management system for community microgrids is developed in this paper. Unlike a centralized optimization-based energy management system, it schedules distributed energy resources and energy storage systems, as well as residential appliances, indirectly through iterative interaction between the microgrid central controller and home energy management systems, based on price signals. In each iteration, the microgrid central controller adjusts the scheduling of distributed energy resources and energy storage systems at the microgrid level. Meanwhile, the home energy management system of each house adjusts the scheduling of residential appliances. Then, the energy price at each bus is updated according to the unbalanced power between generation and demand. The optimization converges when the unbalanced power of all buses is close to zero, i.e., the microgrid central controller and home energy management systems reach an agreement on the energy price and generation/consumption. In particular, a detailed thermal dynamic model of the house is integrated into the HEMS scheduling for intelligent control of the heating, ventilation, and air-conditioning system by customers. The distribution network is also considered to make the energy price signal locational. Results of case studies validate the efficacy of the proposed distributed energy management system. [ABSTRACT FROM AUTHOR]

Series FACTS devices are one of the key enablers for very high penetration of renewables due to their capabilities in continuously controlling power flows on transmission lines. This paper proposes a bilevel optimization model to optimally locate variable series reactor and phase shifting transformer in the transmission network considering high penetration of wind power. The upper level problem seeks to minimize the investment cost on series FACTS, the cost of wind power curtailment, and possible load shedding. The lower level problems capture the market clearing under different operating scenarios. Due to the poor scalability of $B\theta$ formulation, the shift factor structure of FACTS allocation is derived. A customized reformulation and decomposition algorithm is designed and implemented to solve the proposed bilevel model with binary variables in both upper and lower levels. Detailed numerical results based on 118-bus system demonstrate the efficient performance of the proposed planning model and the important role of series FACTS for facilitating the integration of wind power. [ABSTRACT FROM AUTHOR]

Frequency performance has been a crucial issue for islanded microgrids. On the one hand, most distributed energy resources are converter-interfaced and do not inherently respond to frequency variations. On the other hand, current inertia emulation approach cannot provide guaranteed response. In this paper, a model reference control based inertia emulation strategy is proposed for diesel-wind systems. Desired inertia can be precisely emulated through the proposed strategy. A typical frequency response model with parametric inertia is set to be the reference model. A measurement at a specific location delivers the information about the disturbance acting on the diesel-wind system to the reference model. The objective is for the speed of the diesel generator to track the reference so that the desired inertial response is realized. In addition, polytopic parameter uncertainty will be considered. The control strategy is configured in different ways according to different operating points. The parameters of the reference model are scheduled to ensure adequate frequency response under a predefined worst case. The controller is implemented in a nonlinear three-phase diesel-wind system fed microgrid using the Simulink software platform. The results show that exact synthetic inertia can be emulated and adequate frequency response is achieved. [ABSTRACT FROM AUTHOR]

This paper proposes a Mixed Integer Conic Programming (MICP) model for community microgrids considering the network operational constraints and building thermal dynamics. The proposed multi-objective optimization model optimizes not only the operating cost, including fuel cost, electricity purchasing/selling, storage degradation, voluntary load shedding and the cost associated with customer discomfort as a result of the room temperature deviation from the customer setting point, but also several performance indices, including voltage deviation, network power loss and power factor at the Point of Common Coupling (PCC). In particular, we integrate the detailed thermal dynamic model of buildings into the distribution optimal power flow (D-OPF) model for the optimal operation. Thus, the proposed model can directly schedule the heating, ventilation and air-conditioning (HVAC) systems of buildings intelligently so as to to reduce the electricity cost without compromising the comfort of customers. Results of numerical simulation validate the effectiveness of the proposed model and significant savings in electricity cost with network operational constraints satisfied. [ABSTRACT FROM AUTHOR]

This study proposes a robust optimisation-based optimal scheduling model for microgrid operation considering constraints of islanding capability. The objective is to minimise the total operation cost, including generation cost and spinning reserve cost of local resources as well as purchasing cost of energy from the main grid. To ensure the resiliency of a microgrid and improve the reliability of the local electricity supply, the microgrid is required to maintain enough spinning reserve (both up and down) to meet local demand and accommodate local renewable generation when the supply of power from the main grid is interrupted suddenly, i.e. microgrid transitions from grid-connected into islanded mode. Prevailing operational uncertainties in renewable energy resources and load are considered and captured using a robust optimisation method. With proper robust level, the solution of the proposed scheduling model ensures successful islanding of the microgrid with minimum load curtailment and guarantees robustness against all possible realisations of the modelled operational uncertainties. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro-turbine, a diesel generator and a battery demonstrate the effectiveness of the proposed scheduling model. [ABSTRACT FROM AUTHOR]

This study proposes a robust optimisation‐based optimal scheduling model for microgrid operation considering constraints of islanding capability. The objective is to minimise the total operation cost, including generation cost and spinning reserve cost of local resources as well as purchasing cost of energy from the main grid. To ensure the resiliency of a microgrid and improve the reliability of the local electricity supply, the microgrid is required to maintain enough spinning reserve (both up and down) to meet local demand and accommodate local renewable generation when the supply of power from the main grid is interrupted suddenly, i.e. microgrid transitions from grid‐connected into islanded mode. Prevailing operational uncertainties in renewable energy resources and load are considered and captured using a robust optimisation method. With proper robust level, the solution of the proposed scheduling model ensures successful islanding of the microgrid with minimum load curtailment and guarantees robustness against all possible realisations of the modelled operational uncertainties. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, a micro‐turbine, a diesel generator and a battery demonstrate the effectiveness of the proposed scheduling model. [ABSTRACT FROM AUTHOR]

A hardware testbed platform emulating multiple-area power system scenario dynamics has been established aiming at multiple time-scale real-time emulations. In order to mimic real power flow situations in the utility system, the load emulators have to behave like real ones in both their static and dynamic characteristics. A constant-impedance, constant-current, and constant-power (ZIP) model has been used for static load types, while a three-phase induction motor model has been built to represent dynamic load types. In this paper, ways of modeling ZIP and induction motor loads and the performance of each load emulator are discussed. Comparisons between simulation and experimental results are shown as well for the validation of the emulator behaviors. A real-time composite power load emulator is then demonstrated with desired characteristics and detailed transients for representing a power system PQ bus dynamics. [ABSTRACT FROM PUBLISHER]

An introduction is presented in which the editor discusses various reports within the issue on topics including dynamic synchrophasor estimation, voltage controllability and renewable energy.

A fast islanding detection tool can help power dispatchers monitor and control power system operations. Frequency monitoring network (FNET) is a low cost and quickly deployable wide-area phasor measurement system at the distribution system level. The frequency disturbance recorder (FDR) in FNET is actually a single-phase phasor measurement unit (PMU) installed at ordinary 120 V outlets in the sense that it measures the voltage phase angle, amplitude, and frequency from a single-phase voltage source. Based on the data collected by the FDRs deployed in the North American power grid, two islanding detection methods, the frequency difference method and the change of angle difference method, are proposed. The nine real cases recorded, including islanding cases, generation trip cases, load shedding cases and oscillation cases, are presented to verify the proposed methods of islanding detection. Sensitivity analysis on the thresholds of the frequency deviation and angle deviation is done based on the real measurement data for obtaining the insensitive interval of two thresholds. The results show that the proposed methods can correctly detect power system islanding, and will not be falsely triggered by generation trips, load shedding and system oscillations. [ABSTRACT FROM PUBLISHER]

This paper resulted from the research aimed at introducing modeling and simulation as a major methodological approach for enhancing power engineering education. The reasons for such an approach an explained first. Different options and uses of the modeling and simulation tools are discussed next. Several implementations of the teaching examples ate outlined. The paper ends with the conclusions reached based on the study. [ABSTRACT FROM AUTHOR]