Abstract:The paper provides a short history of the phasor measurement unit (PMU) concept. The origin of PMU is traced to the work on developing computer based distance relay using symmetrical component theory. PMUs evolved from a portion of this relay architecture. The need for synchronization using global positioning system (GPS) is discussed, and the wide area measurement system (WAMS) utilizing PMU signals is described. A number of applications of this technology are discussed, and an account of WAMS activities in many countries around the world are provided.

Abstract:With the integration of information technologies, power system operations are increasingly threatened by cyber-attacks. It has even been revealed that an attacker can inject false data into real-time measurements stealthily without knowing the full configuration (e.g., network topology) of a power system. In this paper, we present a comprehensive review on false data injection attacks which utilize barrier conditions, blind identification techniques and data driven approaches to overcome limitations of incomplete network information. We also point out future research topics for facilitating the detection and prevention of such false data attacks.

Abstract:This paper gives an overview of previous studies on photovoltaic (PV) devices, grid-connected PV inverters, control systems, maximum power point tracking (MPPT) control strategies, switching devices and transformer-less inverters. The literature is classified based on types of PV systems, DC/DC boost converters and DC/AC inverters, and types of controllers that control the circuit to ensure maximum power tracking and stabilization of load and input voltage. This is followed by the theoretical background of PV devices, an overview of MPPT controllers and common mode leakage current, and a detailed investigation of different inverter topologies regarding the ground leakage current. Furthermore, design principles of power converters, such as DC/DC boost converters, and single-phase inverters are discussed. The paper also discusses limitations and benefits in addition to the basic operating principles of several topologies. Finally, the proposed system is derived and its simulation results are discussed to offer the next generation of grid connected PV systems.

Abstract:With the development of smart grids, a renewable energy generation system has been introduced into a smart house. The generation system usually supplies a storage system with the capability to store the produced energy for satisfying a user’s future demand. In this paper, the main objective is to determine the best strategies of energy consumption and optimal storage capacities for residential users, which are both closely related to the energy cost of the users. Energy management with storage capacity optimization is studied by considering the cost of renewable energy generation, depreciation cost of storage and bidirectional energy trading. To minimize the cost to residential users, the non-cooperative game-theoretic method is employed to formulate the model that combines energy consumption and storage capacity optimization. The distributed algorithm is presented to understand the Nash equilibrium which can guarantee Pareto optimality in terms of minimizing the energy cost. Simulation results show that the proposed game approach can significantly benefit residential users. Furthermore, it also contributes to reducing the peak-to-average ratio (PAR) of overall energy demand.

Abstract:With the increasing quantity of DC electrical equipment, DC microgrids have been paid more and more attention. This paper proposes an approach to multi-objective optimisation of an energy management system (EMS) for a DC microgrid that includes a hybrid energy storage system (HESS). The operating and maintenance cost and the loss of power supply probability (LPSP) of the system are used as optimisation targets. The power flows of all distributed generators (DGs) in the DC microgrid during operating period are optimized. Based on the improved differential evolution (DE) algorithm, and by using the multi-objective non-dominated sorting method and the maximum membership degree principle (MMDP) of fuzzy control, the overall satisfaction degree of Pareto solutions to power flow optimization can be obtained. Simulation results verify the effectiveness of the proposed EMS optimization scheme, which is able to achieve an effective trade-off between the economy and the reliability of microgrid operation.

Abstract:Power flow transfer (PFT) analysis under various anticipated faults in advance is important for securing power system operations. In China, PSD-BPA software is the most widely used tool for power system analysis, but its input/output interface is easily adapted for PFT analysis, which is also difficult due to its computationally intensity. To solve this issue, and achieve a fast and accurate PFT analysis, a modular parallelization framework is developed in this paper. Two major contributions are included. One is several integrated PFT analysis modules, including parameter initialization, fault setting, network integrity detection, reasonableness identification and result analysis. The other is a parallelization technique for enhancing computation efficiency using a Fork/Join framework. The proposed framework has been tested and validated by the IEEE 39 bus reference power system. Furthermore, it has been applied to a practical power network with 11052 buses and 12487 branches in the Yunnan Power Grid of China, providing decision support for large-scale power system analysis.

Abstract:Power system controlled islanding is an emergency control to stop the propagation of disturbances and to avoid blackouts. This paper presents a three-stage method for intentional controlled islanding of power systems. It enables to search out reasonable islanding cutsets, which have the minimum load-generation imbalance or the minimal power flow disruption, without low-voltage problems. In the first stage, a self-adaptive graph simplification algorithm is proposed to obtain a two-terminal graph as a suitable islanding cutset search area from the original power network graph model. In the second stage, an islanding cutset search algorithm is designed to find all of islanding cutsets, including the minimum load-generation imbalance cutset, in the two-terminal graph. In the third stage, an islanding scheme checking algorithm is developed to examine the outputs of stage two. It uses the depth first search algorithm to determine reasonable islanding cutsets without low-voltage problems. The IEEE 30-bus system and the IEEE 118-bus system are utilized to demonstrate the proposed method. The simulation results show its validity and accuracy in large-scale power systems.

Abstract:Smart electricity utilization (SEU) is one of the most important components in a smart grid. It is crucial to evaluate efficiency, safety, and demand response capability of electricity users to achieve the smart use of electricity. The analytic hierarchy process (AHP) uses subjective criteria to determine index weights in multi-criteria decisionmaking problems, while the entropy method provides objectivity in determining index weights. Taking into account the uncertainty of expert scoring and user data, a hybrid interval analytic hierarchy process (IAHP) and interval entropy (IE) method is proposed for electricity user evaluation (EUE). Specifically, in the proposed method, electricity users are evaluated in terms of energy efficiency, safety monitoring, and demand response. The weights of EUE indices are calculated under uncertainty. The proposed approach derives subjective weights of EUE indices by the IAHP with expert scoring as input data, and determines objective weights of EUE indices by the IE method with user data as inputs. In order to obtain the optimal combined index weights, the two weights are normalized by a selected weight factor. Numerical case studies illustrate the effectiveness and advantages of the proposed approach, which combines subjective and objective information to derive the optimal combined index weights.

Abstract:In recent years, failure recovery after faults is concerned and discussed worldwide as an important and hot topic. Facing the challenge of heavy loads and ultrahigh voltage transmission, it’s urgent to propose some solutions to enhance transient voltage stability for failure recovery. Therefore, a novel dynamic volt ampere reactive (VAR) planning methodology is proposed in this paper to help failure recovery and improve transient voltage stability after contingencies. First, a transient voltage fluctuation (TVF) index is proposed to evaluate transient voltage condition after faults. Then dynamic compensation sensitivity is presented for searching the best candidate locations. Following that, the dynamic VAR planning methodology based on an improved Tent chaos multi-objective algorithm is discussed in detail. There are two optimization objects in the optimization. One is to minimize TVF to enhance transient voltage stability for failure recovery. And the other optimization is to minimize dynamic VAR investment cost and operation cost. Finally, IEEE 39 power system and a practical power system are analyzed and discussed. The proposed dynamic VAR planning methodology can support enough reactive power for failure recovery. With the least SVC planning amount and the power loss cost, it can greatly decrease the system TVF index and enhance the transient voltage stability. It’s proved that the proposed dynamic VAR planning optimization is effective and helpful for safety operation of power system.

Abstract:The high penetration of distributed renewable energy raises a higher concern for the safe and economic operation of the smart grid. Distributed batteries equipped in demand-side can not only contribute to the reliability and security of the grid, but also make profits by participating in the electricity market, especially when distributed batteries are combined and operated by an aggregator. Considering the well-operated mechanism of performance based regulation (PBR) in the U.S. electricity market, it becomes increasingly lucrative for batteries to participate not only in energy markets for energy arbitrage, but also in ancillary service markets to provide regulation and peakload shaving services. In this study, distributed batteries are operated and coordinated by the aggregator, which simultaneously submits offers to the energy and the ancillary service markets as an individual entity. An optimal decision model is formulated for the aggregator to determine the operation and bidding strategy for the distributed batteries by considering the characteristics of batteries, including the terms of capacity, efficiency and degradation cost. Finally, a numerical case is conducted to evaluate the benefits of the decision model.

Abstract:In this paper, a multi-stage stochastic model is presented for a renewable distributed generation (RDG)- owning retailer to determine the trading strategies existing in a competitive electricity market. Uncertainties associated with wholesale electricity market price, clients’ consumption and power output of wind resources are considered through auto regressive integrated moving average (ARIMA) approach. In the proposed method, three trading floors are addressed for the retailer to hedge against the uncertainties. In the first stage, the retailer participates in day-ahead market to supply the clients and in the second stage, intraday market is addressed to allow the retailer to modify the schedule of its clients’ consumption/RDG production. Due to unfavorable uncertainties, especially in renewable power production, real-time market is considered in the third stage to diminish the uncertainty at power delivery time. Cost function of wind resources considering capital, operation and maintenance (O&M) cost is incorporated in the objective function to increase the applicability of the mechanism. The proposed approach is formulated for risk-averse and risk-taker retailer through conditional value at risk (CVaR) approach. In order to study the impact of retail strategies on consumption pattern and consumers’ electricity bills, time-of-use (TOU) demand response programs are discussed in this paper. Formulating the problem, the mixed integer non-linear programming (MILNP) problem is transformed into mixed integer linear programming (MILP) by jointly using decomposition and disjunctive constraints. Finally, a case study containing wind power resources, energy storage system and retailer is considered to analyze the proficiency of the proposed approach.

Abstract:Offshore wind farm (OWF) is the largest renewable energy resource. The electrical interconnection cost of OWFs is a considerable fraction of the overall design cost of the farm. In order to minimize the investment and operational costs, this paper proposes an optimization formulation to find the optimal electrical interconnection configuration of wind turbines (WTs), and the optimal cable sizing simultaneously. This simultaneous minimization of total trenching length and cable dimensions creates a complex optimization problem that is solved by the harmony search (HS) algorithm. In this paper, two distinct methods of full and partial optimal cable sizing are considered to comprehensively assess the optimal interconnection layout of OWFs. Furthermore, various shipping and burying costs as well as various WTs power ratings are considered in order to investigate their impact on the optimal electrical interconnection system. The optimal electrical interconnection design obtained by the HS algorithm corresponds to a lower cost that together with the technological developments can help policy makers increase the use of offshore wind energy as a feasible unlimited renewable resource in their energy production portfolios.

Abstract:Weather forecasting is crucial to both the demand and supply sides of electricity systems. Temperature has a great effect on the demand side. Moreover, solar and wind are very promising renewable energy sources and are, thus, important on the supply side. In this paper, a large vector autoregression (VAR) model is built to forecast three important weather variables for 61 cities around the United States. The three variables at all locations are modeled as response variables. Lag terms are used to capture the relationship between observations in adjacent periods and daily and annual seasonality are modeled to consider the correlation between the same periods in adjacent days and years. We estimate the VAR model with 16 years of hourly historical data and use two additional years of data for out-of-sample validation. Forecasts of up to six-hours-ahead are generated with good forecasting performance based on mean absolute error, root mean square error, relative root mean square error, and skill scores. Our VAR model gives forecasts with skill scores that are more than double the skill scores of other forecasting models in the literature. Our model also provides forecasts that outperform persistence forecasts by between 6% and 80% in terms of mean absolute error. Our results show that the proposed time series approach is appropriate for very short-term forecasting of hourly solar radiation, temperature, and wind speed.

Abstract:This paper addresses the control design and the experimental validation of a current mode control for a three phase voltage source rectifier. The proposed control law is able to fulfill the voltage regulation and the current tracking control objectives despite of unbalanced and distorted grid voltages. The proposed control law consists of two loops, which are referred as inner tracking loop and the outer voltage regulation loop. The inner loop is designed to provide damping to the system, which also includes and adaptive mechanism. The construction of the current reference is based on the positive component detection of the grid voltage. Therefore, the current produced by the power rectifier is proportional to the fundamental component of the grid voltage, despite of the presence of unbalanced grid voltages. The voltage regulation loop is designed as a proportional-integral controller, which is aimed to regulate the DC output voltage to a desired level. Finally, experimental results are obtained in an experimental prototype of 2 kW to evaluate the performance of the proposed controller.

Abstract:Currently, small islands are facing an energy supply shortage, which has led to considerable concern. Establishing an island microgrid is a relatively good solution to the problem. However, high investment costs restrict its application. In this paper, micro pumped storage (MPS) is used as an energy storage system (ESS) for islands with good geographical conditions, and deferrable appliance is treated as the virtual power source which can be used in the planning and operational processes. Household acceptance of demand response (DR) is indicated by the demand response participation degree (DRPD), and a sizing optimization model for considering the demand response of household appliances in an island microgrid is proposed. The particle swarm optimization (PSO) is used to obtain the optimal sizing of all major devices. In addition, the battery storage (BS) scheme is used as the control group. The results of case studies demonstrate that the proposed method is effective, and the DR of deferrable appliances and the application of MPS can significantly reduce island microgrid investment. Sensitivity analysis on the total load of the island and the water head of the MPS are conducted.

Abstract:Demand response has the potential to bring significant benefits to the optimal sizing of distributed generation (DG) resources for microgrids planning. This paper presents an integrated resources planning model considering the impact of interruptible loads (IL) and shiftable loads (SL) in microgrids, which simultaneously deals with supply side and demand side resources and minimizes the overall planning cost of the microgrid. The proposed model can be applied to offer a quantitative assessment how IL and SL can contribute to microgrid planning. The pure peak clipping model with IL and SL is also provided for comparisons. Moreover, sensitivity analysis of parameters in the model is performed. Numerical results confirm that the proposed model is an effective method for reducing the planning cost of microgrids. It was also found that the major contributing factors of IL and SL have great impact on the economic benefits of the proposed model in low-carbon economy environments.

Abstract:This paper presents a novel integrated framework for simulating the charging load of an electric vehicle charging station. The framework is built based on the cellular automaton model, including five modules: vehicle generation, charging station, lane change, speed update and boundary clear. The proposed framework can effectively stimulate the system dynamics of the traffic system and charging power process in a charging station. Case studies have verified its feasibility and effectiveness.

Abstract:Short-circuit fault current suppression is a very important issue in modern large-interconnected power networks. Conventional short-circuit current limiters, such as superconducting fault current limiters, have to increase additional equipment investments. Fast power electronics controlled flexible AC transmission system (FACTS) devices have opened a new way for suppressing the fault current levels, while maintaining their normal functionalities for steady-state and transient power system operation and control. Thyristor controlled phase shifting transformer (TCPST) is a beneficial FACTS device in modern power systems, which is capable of regulating regional power flow. The mathematical model for TCPST under different operation modes is firstly investigated in this study. Intuitively, the phase shifting angle control can adjust the equivalent impedance of TCPST, but the effect has been demonstrated to be weak. Therefore, a novel transformer excitation impedance switching (EIS) control method, is proposed for fault current suppressing, according to the impedance characteristics of TCPST. Simulation results on IEEE 14-bus system have shown considerable current limiting characteristic of the EIS control under various fault types. Also, analysis of the timing requirement during fault interruption, overvoltage phenomenon, and ancillary mechanical support issues during EIS control is discussed, so as to implement the proposed EIS control properly for fast fault current suppression.

Abstract:In this paper, a battery energy storage system (BESS) based control method is proposed to improve the damping ratio of a target oscillation mode to a desired level by charging or discharging the installed BESS using local measurements. The expected damping improvement by BESS is derived analytically for both a single-machineinfinite-bus system and a multi-machine system. This BESS-based approach is tested on a four-generator, twoarea power system. Effects of the power converter limit, response time delay, power system stabilizers and battery state-of-charge on the control performance are also investigated. Simulation results validate the effectiveness of the proposed approach.