Abstract:

Abstract:The coordinated operation and comprehensive utilization of multi-energy sources require systematic research. A multi-energy microgrid (MEMG) is a coupling system with multiple inputs and outputs. In this paper, a system model based on unified energy flows is proposed to describe the static relationship, and an analogue energy storage model is proposed to represent the time-dependency characteristics of energy transfer processes. Then, the optimal dispatching model of an MEMG is established as a mixed-integer linear programming (MILP) problem using piecewise linear approximation and convex relaxation. Finally, the system model and optimal dispatching method are validated in an MEMG, including district electricity, natural gas and heat supply, and renewable generation. The proposed model and method provide an effective way for the energy flow analysis and optimization of MEMGs.

Abstract:In this paper, a coordinated control scheme for wind turbine generator (WTG) and supercapacitor energy storage system (ESS) is proposed for temporary frequency supports. Inertial control is designed by using generator torque limit considering the security of WTG system, while ESS releases its energy to compensate the sudden active power deficit during the recovery process of turbine rotor. WTG is modeled using the fatigue, aerodynamic, structure, turbulence (FAST) code, which identifies the mechanical loadings of the turbine and addresses electro-mechanical interactions in the wind energy system. A damping controller is augmented to the inertial control to suppress severe mechanical oscillations in the shaft and tower of the turbine during frequency supports. Furthermore, the result of small-signal stability analysis shows that the WTG-ESS tends to improve the stability of the whole multi-energy power grid. The major contributions of this paper will be validated by utilizing the proposed control method that combines the grid support capability and maintaining the integrity of structural design of the turbine for normal operations.

Abstract:Distributed integrated multi-energy systems (DIMSs) can be regarded as virtual power plants to provide additional flexibility to the power system. This paper proposes a robust active dynamic aggregation model for the DIMSs to describe the maximum feasible region. The aggregation model includes the power constraints, energy constraints, and ramping constraints to aggregate different types of resources in the DIMSs. The proposed generator-like and storage-like model does not depend on the ancillary service market and can be directly incorporated into the economic dispatch model of the power system. A novel algorithm based on the column-and-constraint generation algorithm and convex-concave procedure is proposed to solve the two-stage robust optimization problem, which is more efficient than the KKT-based algorithms. Finally, a case study of an actual DIMS is developed to demonstrate the effectiveness of the proposed model.

Abstract:In integrated energy systems (IESs), traditional fixed time-interval dispatching scheme is unable to adapt to the need of dynamic properties of the transient network, demand response characteristics, dispatching time scales in energy sub-systems and renewable power uncertainties. This scheme may easily result in uneconomic source-grid-load-storage operations in IES. In this paper, we propose a dispatching method for IES based on dynamic time-interval of model predictive control (MPC). We firstly build models for energy sub-systems and multi-energy loads in the power-gas-heat IES. Then, we develop an innovative optimization method leveraging trajectory deviation control, energy control, and cost control frameworks in MPC to handle the requirements and constraints over the time-interval of dispatching. Finally, a dynamic programming algorithm is introduced to efficiently solve the proposed method. Experiments and simulation results prove the effectiveness of the method.

Abstract:To enhance the flexible interactions among multiple energy carriers, i.e., electricity, thermal power and gas, a coordinated programming method for multi-energy microgrid (MEMG) system is proposed. Various energy requirements for both residential and parking loads are managed simultaneously, i.e., electric and thermal loads for residence, and charging power and gas filling requirements for parking vehicles. The proposed model is formulated as a two-stage joint chance-constrained programming, where the first stage is a day-ahead operation problem that provides the hourly generation, conversion, and storage towards the minimization of operation cost considering the forecasting error of photovoltaic output and load demand. Meanwhile, the second stage is an on-line scheduling which adjusts the energy scheme in hourly time-scale for the uncertainty realizations. Simulations have demonstrated the validity of the proposed method, i.e., collecting the flexibilities of thermal system, gas system, and parking vehicles to facilitate the operation of electrical networks. Sensitivity analysis shows that the proposed scheme can achieve a compromise between the operation efficiency and service quality.

Abstract:As a typical scenario of distributed integrated multi-energy system (DIMS), industrial park contains complex production constraints and strong associations between industrial productions and energy demands. The industrial production process (IPP) consists of controllable subtasks and strict timing constraints. Taking IPP as a control variable of optimal scheduling, it is an available approach that models the IPP as material flow into an extension energy hub (EH) to achieve the optimization of industrial park. In this paper, considering the coupling between the production process and energy demands, a model of IPP is proposed by dividing the process into different adjustable steps, including continuous subtask, discrete subtask, and storage subtask. Then, a transport model of material flow is used to describe the IPP in an industrial park DIMS. Based on the concept of EH, a universal extension EH model is proposed considering the coupling among electricity, heat, cooling, and material. Furthermore, an optimal scheduling method for industrial park DIMS is proposed to improve the energy efficiency and operation economy. Finally, a case study of a typical battery factory is shown to illustrate the proposed method. The simulation results demonstrate that such a method reduces the operation cost and accurately reflects the operation state of the industrial factory.

Abstract:Integrated electrical and heating systems (IEHSs) are promising for increasing the flexibility of power systems by exploiting the heat energy storage of pipelines. With the recent development of advanced communication technology, distributed optimization is employed in the coordination of IEHSs to meet the practical requirement of information privacy between different system operators. Existing studies on distributed optimization algorithms for IEHSs have seldom addressed packet loss during the process of information exchange. In this paper, a distributed paradigm is proposed for coordinating the operation of an IEHS considering communication packet loss. The relaxed alternating direction method of multipliers (R-ADMM) is derived by applying Peaceman-Rachford splitting to the Lagrangian dual of the primal problem. The proposed method is tested using several test systems in a lossy communication and transmission environment. Simulation results indicate the effectiveness and robustness of the proposed R-ADMM algorithm.

Abstract:Although the deployment of alternating current (AC)-busbar plug-in electric vehicle (PEV) charging station with photovoltaic (PV) is a promising alternative, the interaction among subsystems always causes the instability problem. Meanwhile, the conventional generalized Nyquist criterion (GNC) is complex, and it is not suitable for the design of the AC system. Therefore, this paper proposes a modified infinity-one-norm (MION) stability criterion based on the impedance method to assess the stability of the foresaid charging station. Firstly, the typical structure and operation modes of the charging station are studied. Furthermore, each subsystem impedance matrix is built by small-signal method, and the MION stability criterion based on impedance method is proposed to assess the charging station stability. Compared with the previous simplified stability criteria based on the norm, the proposed criterion has lower conservatism. Furthermore, the design regulation for the controller parameters is provided, and the stability recovery way is provided by connecting the doubly-fed line and energy storage equipment, which are selected based on intermediate variable, i.e., short-circuit ratio (SCR). Finally, the effectiveness and conservatism of the proposed stability criterion are validated through simulation and experimental results.

Abstract:In the face of the pressing environmental issues, the past decade witnessed the booming development of the distributed energy systems (DESs). A notable problem of DESs is the inevitable uncertainty that may make DESs deviate significantly from the deterministically obtained expectations, in both aspects of optimal design and economic operation. It thus necessitates the sensitivity analysis to quantify the impacts of the massive parametric uncertainties. This paper aims to give a comprehensive quantification, and carries out a multi-stage sensitivity analysis on DESs from the perspectives of evaluation criteria, optimal design and economic operation. First, a mathematical model of a DES is developed to present the solutions to the three stages of the DES. Second, the Monte-Carlo simulation is carried out subject to the probabilistic distributions of the energy, technical and economic parameters. Based on the simulation results, the variance-based Sobol method is applied to calculate the individual importance, interactional importance and total importance of various parameters. The comparison of the multi-stage results shows that only a few parameters play critical roles while the uncertainty of most of the massive parameters has little impact on the system performance. In addition, the influence of parameter interactions in the optimal design stage are much stronger than that in the evaluation criteria and operation strategy stages.

Abstract:Power grids include entities such as home-microgrids (H-MGs), consumers, and retailers, each of which has a unique and sometimes contradictory objective compared with others while exchanging electricity and heat with other H-MGs.Therefore, there is the need for a smart structure to handle the new situation. This paper proposes a bilevel hierarchical structure for designing and planning distributed energy resources (DERs) and energy storage in H-MGs by considering the demand response (DR). In general, the upper-level structure is based on H-MG generation competition to maximize their individual and/or group income in the process of forming a coalition with other H-MGs. The upper-level problem is decomposed into a set of low-level market clearing problems. Both electricity and heat markets are simultaneously modeled in this paper. DERs, including wind turbines (WTs), combined heat and power (CHP) systems, electric boilers (EBs), electric heat pumps (EHPs), and electric energy storage systems, participate in the electricity markets. In addition, CHP systems, gas boilers (GBs), EBs, EHPs, solar thermal panels, and thermal energy storage systems participate in the heat market. Results show that the formation of a coalition among H-MGs present in one grid will not only have a significant effect on programming and regulating the value of the power generated by the generation resources, but also impact the demand consumption and behavior of consumers participating in the DR program with a cheaper market clearing price.

Abstract:In an integrated energy distribution system (IEDS), an energy hub has been introduced and deemed to be a suitable tool for managing and integrating multi-party energy forms. Due to different energies having diverse characteristics and being coupled with each other, it is difficult for an energy hub to implement the optimal scheduling of multiple energy sources. Therefore, an energy optimization management model is proposed based on the Stackelberg game, which considers the exergy conversion of multi-party energy sources in different operation modes. The problem is solved by the two-layer distributed optimization algorithm, in which the energy hub acts as the leader and is followed by the users. Furthermore, in order to alleviate the deception, malicious tampering, subpeption, and other secure risks in energy trading, blockchain is introduced into the energy hub and the concept of exergy coin (EC) is proposed. A credit-based blockchain framework and concurrent block building consensus process is explored to reduce the calculation cost and promote the exergy trading efficiency. Finally, the case study shows how the proposed method can effectively optimize energy scheduling and configure a more reasonable energy solution.

Abstract:Microgrids with hybrid renewable energy sources are increasing and it is a promising solution to electrify remote areas where distribution network expansion is not feasible or not economical. Standalone microgrids with environment-friendly hybrid energy sources is a cost-effective solution that ensures system reliability and energy security. This paper determines the optimal capacity, energy dispatching and techno-economic benefits of standalone microgrid in remote area in Tamilnadu, India. Microgrids with hybrid energy sources comprising photovoltaic (PV), wind turbine (WT), battery energy storage system (BESS) and diesel generator (DG) are considered in this paper. Various case studies are implemented with hybrid energy sources and for each case study a comparative analysis of techno-economic benefits is demonstrated. Eight different configurations of hybrid energy sources are modeled with renewable fractions of 50%, 60%, 65%, and 100%, respectively. The optimization analysis is carried out using Hybrid Optimization Model for Electric Renewable (HOMER) software. Impact of demand response is also demonstrated on energy dispatching and techno-economic benefits. Simulation results are obtained for the optimal capacity of PV, WT, DG, converter, and BESS, charging/discharging pattern, state of charge (SOC), net present cost (NPC), cost of energy (COE), initial cost, operation cost, fuel cost, greenhouse gas emission penalty and payback period considering seasonal load variation. It is observed that PV+BESS is the most economical configuration. COE in standalone microgrid is higher than the conventional grid price. The results show that CO₂ emissions in hybrid PV+WT+DG+BESS are reduced by about 68% compared with the traditional isolated distribution system with DG.

Abstract:In an active distribution grid, renewable energy sources (RESs) such as photovoltaic (PV) and energy storage systems (e.g., superconducting magnetic energy storage (SMES)) can be combined with consumers to compose a microgrid (MG). The high penetration of PV causes high fluctuations of tie-line power flow and highly affects power system operations. This can lead to several technical problems such as voltage fluctuations and excessive power losses. In this paper, a fuzzy logic control based SMES method (FSM) and an optimized fuzzy logic control based SMES method (OFSM) are proposed for minimizing the tie-line power flow. Consequently, the fluctuations and transmission power losses are decreased. In FSM, SMES is used with a robust fuzzy logic controller (FLC) for controlling the tie-line power flow. An optimization model is employed in OFSM to simultaneously optimize the input parameters of the FLC and the reactive power of the voltage source converter (VSC) of SMES. The objective function of minimizing the tie-line power flow is incorporated into the optimization model. Particle swarm optimization (PSO) algorithm is utilized to solve the optimization problem while the constraints of the utility power grid, VSC, and SMES are considered. The simulation results demonstrate the effectiveness and robustness of the proposed methods.

Abstract:In recent years, as a promising option to improve the overall efficiency of energy utilization and absorptive capacity of renewable energies, the integrated energy system (IES) has raised great interest in academies and industries. Multi-energy flow (MF) calculation, which differs from the traditional power flow calculation, plays a basic role in analyzing IES. MF calculation based on Newton-Raphson method has been proposed in literature, but its calculation efficiency is not high. In this paper, a fast decoupled MF (FDMF) calculation method for IES is proposed. Its main idea is to replace the original Jacobian matrix of MF calculation based on Newton-Raphson method with a diagonal and constant Jacobian matrix by the transformation. The simulations demonstrate that the proposed FDMF method can increase the calculation efficiency by at least 4 times with high calculation accuracy.

Abstract:The sharp increase in the total installed capacity of natural gas generators has intensified the dynamic interaction between the electricity and natural gas systems, which could induce cascading failure propagation across the two systems that deserves intensive research. Considering the distinct time response behaviors of the two systems, this paper discusses an integrated simulation approach to simulate the cascading failure propagation process of integrated electricity and natural gas systems (IEGSs). On one hand, considering instantaneous re-distribution of power flows after the occurrence of disturbance or failure, the steady-state AC power flow model is employed. On the other hand, gas transmission dynamics are represented by dynamic model to capture the details of its transition process. The interactions between the two systems, intensified by energy coupling components (such as gas-fired generator and electricity-driven gas compressor) as well as the switching among the operation modes of compressors during the cascading failure propagation process, are studied. An IEGS composed of the IEEE 30-bus electricity system and a 14-node 15-pipeline gas system is established to illustrate the effectiveness of the proposed simulation approach, in which two energy sub-systems are coupled by compressor and gas-fired generator. Numerical results clearly demonstrate that heterogeneous interactions between electricity and gas systems would trigger the cascading failure propagation between the two coupling systems.

Abstract:Battery energy storage system (BESS) has already been studied to deal with uncertain parameters of the electrical systems such as loads and renewable energies. However, the BESS have not been properly studied under unbalanced operation of power grids. This paper aims to study the modelling and operation of BESS under unbalanced-uncertain conditions in the power grids. The proposed model manages the BESS to optimize energy cost, deal with load uncertainties, and settle the unbalanced loading at the same time. The three-phase unbalanced-uncertain loads are modelled and the BESSs are utilized to produce separate charging/discharging pattern on each phase to remove the unbalanced condition. The IEEE 69-bus grid is considered as case study. The load uncertainty is developed by Gaussian probability function and the stochastic programming is adopted to tackle the uncertainties. The model is formulated as mixed-integer linear programming and solved by GAMS/CPLEX. The results demonstrate that the model is able to deal with the unbalanced-uncertain conditions at the same time. The model also minimizes the operation cost and satisfies all security constraints of power grid.

Abstract:The estimation of sequence or symmetrical components and frequency in three-phase unbalanced power system is of great importance for protection and relay. This paper proposes a new H_∞ filter based on sparse model to track the sequence components and the frequency of three-phase unbalanced power systems. The inclusion of sparsity improves the error convergence behavior of estimation model and hence short-duration non-stationary PQ events can easily be tracked in the time domain. The proposed model is developed using l₁ norm penalty in the cost function of H_∞ filter, which is quite suitable for estimation across all the three phases of an unbalanced system. This model uses real state space modeling across three phases to estimate amplitude and phase parameters of sequence components. However, frequency estimation uses complex state space modeling and Clarke transformation generates a complex measurement signal from the unbalanced three-phase voltages. The state vector used for frequency estimation consists of two state variables. The proposed sparse model is tested using distorted three-phase signals from IEEE-1159-PQE database and the data generated from experimental laboratory setup. The analysis of absolute and mean square error is presented to validate the performance of the proposed model.

Abstract:In this paper, a fast fault detection scheme for voltage source converter based high-voltage direct current (VSC-HVDC) transmission systems is proposed. Based on Bergeron model equations, the remote terminal voltage of an adopted transmission system is calculated in terms of the local measured current and voltage signals. Subsequently, the computed voltage of the remote terminal is compared with the corresponding actual measured-communicated value. Provided that the considered transmission system is functioning well, the difference between the computed and measured voltages is almost zero. However, a considerable virtual voltage arises for fault conditions. When the voltage difference exceeds a predetermined threshold, a fault condition can be detected. Although a reliable communication link is required, the delay for detecting the fault is not caused by the communication time. For evaluation purpose, a detailed simulation is developed using PSCAD/EMTDC with various fault locations, including the cases near the inside or outside of the protected transmission system. The results corroborate a fast detection scheme depending on a moderate sampling/processing frequency level. A high security level is verified even with the worst external faults, or with the misaligned measured samples at the terminals. This corroborates the suitability of the proposed scheme for protecting multi-terminal HVDC systems.

Abstract:We address the problem of optimally re-routing the feeders of urban distribution network in Milano, Italy, which presents some peculiarities and significant design challenges. Milano has two separate medium-voltage (MV) distribution networks, previously operated by two different utilities, which grew up independently and incoordinately. This results in a system layout which is inefficient, redundant, and difficult to manage due to different operating procedures. The current utility UNARETI, which is in charge of the overall distribution system, aims at optimally integrating the two MV distribution networks and moving to a new specific layout that offers advantages from the perspectives of reliability and flexibility. We present a mixed-integer programming (MIP) approach for the design of a new network configuration satisfying the so-called 2-step ladder layout required by the planner. The model accounts for the main electrical constraints such as power flow equations, thermal limits of high-voltage (HV)/MV substation transformers, line thermal limits, and the maximum number of customers per feeder. Real power losses are taken into account via a quadratic formulation and a piecewise linear approximation. Computational tests on a small-scale system and on a part of the Milano distribution network are reported.

Abstract:Composite load model of Western Electricity Coordinating Council (WECC) is a newly developed load model that has drawn great interest from the industry. To analyze its dynamic characteristics with both mathematical and engineering rigors, a detailed mathematical model is needed. Although composite load model of WECC is available in commercial software as a module and its detailed block diagrams can be found in several public reports, there is no complete mathematical representation of the full model in literature. This paper addresses a challenging problem of deriving detailed mathematical representation of composite load model of WECC from its block diagrams. In particular, we have derived the mathematical representation of the new DER_A model. The developed mathematical model is verified using both MATLAB and PSS/E to show its effectiveness in representing composite load model of WECC. The derived mathematical representation serves as an important foundation for parameter identification, order reduction and other dynamic analysis.

Abstract:In this paper, the model of strategic wind power offering in the day-ahead (DA) market is proposed considering the uncertainties of wind power production, and price forecasting of DA and real-time (RT) market. The wind power deviation in the RT market is settled with the two-price mechanism based on the deviation direction and the relation between the locational marginal prices (LMPs) of DA and RT. Instead of using the point forecasting for the DA and RT LMPs, the uncertainties of LMP forecasting are modeled. In addition, the correlation between the forecasting errors of DA and RT LMP are directly modeled instead of generating the correlated scenarios. Finally, the opitmal offered quantity of wind power in the DA market is derived using the probability theory based on the probabilistic wind power forecasting. The case study using the price data of actual DA and RT from Midcontinent Independent System Operator (MISO) validates the effectiveness of the proposed model. It shows that the correlation of the forecasting errors of DA and RT LMP has a significant impact on the wind power quantity offered by DA and revenue results.