Showing papers on "Power system simulation published in 2017"

A Distributionally Robust Optimization Model for Unit Commitment Considering Uncertain Wind Power Generation

Abstract: This paper proposes a distributionally robust optimization model for solving unit commitment (UC) problems considering volatile wind power generation. The uncertainty of wind power is captured by an ambiguity set that defines a family of wind power distributions, and the expected total cost under the worst-case distribution is minimized. Compared with stochastic programming, this method may have less dependence on the data of exact probability distributions. It should also outperform the conventional robust optimization methods because some distribution information can be incorporated into the ambiguity sets to generate less conservative results. In this paper, the UC model is formulated based on the typical two-stage framework, where the UC decisions are determined in a here-and-now manner, and the economic dispatch decisions are assumed to be wait-and-see , made after the observation of wind power outcomes. For computational tractability, the wait-and-see decisions are addressed by linear decision rule approximation, assuming that the economic dispatch decisions affinely depend on uncertain parameters as well as auxiliary random variables introduced to describe distributional characteristics of wind power generation. It is shown in case studies that this decision rule model tends to provide a tight approximation to the original two-stage problem, and the performance of UC solutions may be greatly improved by incorporating information on wind power distributions into the robust model.

Coordinated Control Strategy of a Battery Energy Storage System to Support a Wind Power Plant Providing Multi-Timescale Frequency Ancillary Services

Abstract: With increasing penetrations of wind generation on electric grids, wind power plants (WPPs) are encouraged to provide frequency ancillary services (FAS); however, it is a challenge to ensure that variable wind generation can reliably provide these ancillary services. This paper proposes using a battery energy storage system (BESS) to ensure the WPPs’ commitment to FAS. This method also focuses on reducing the BESS's size and extending its lifetime. In this paper, a state-machine-based coordinated control strategy is developed to utilize a BESS to support the obliged FAS of a WPP (including both primary and secondary frequency control). This method takes into account the operational constraints of the WPP (e.g., real-time reserve) and the BESS (e.g., state of charge [SOC], charge and discharge rate) to provide reliable FAS. Meanwhile, an adaptive SOC-feedback control is designed to maintain SOC at the optimal value as much as possible, and, thus, reduce the size and extend the lifetime of the BESS. The effectiveness of the control strategy is validated with an innovative multi-area interconnected power system simulation platform that can mimic realistic power systems operation and control by simulating real-time economic dispatch, regulating reserve scheduling, multi-area automatic generation control, and generators’ dynamic response.

Multistage Robust Unit Commitment With Dynamic Uncertainty Sets and Energy Storage

Abstract: The deep penetration of wind and solar power is a critical component of the future power grid. However, the intermittency and stochasticity of these renewable resources bring significant challenges to the reliable and economic operation of power systems. Motivated by these challenges, we present a multistage adaptive robust optimization model for the unit commitment (UC) problem, which models the sequential nature of the dispatch process and utilizes a new type of dynamic uncertainty sets to capture the temporal and spatial correlations of wind and solar power. The model also considers the operation of energy storage devices. We propose a simplified and effective affine policy for dispatch decisions, and develop an efficient algorithmic framework using a combination of constraint generation and duality-based reformulation with various improvements. Extensive computational experiments show that the proposed method can efficiently solve multistage robust UC problems on the Polish 2736-bus system under high dimensional uncertainty of 60 wind farms and 30 solar farms. The computational results also suggest that the proposed model leads to significant benefits in both costs and reliability over robust models with traditional uncertainty sets as well as deterministic models with reserve rules.

Stochastic Security-Constrained Scheduling of Coordinated Electricity and Natural Gas Infrastructures

Abstract: This paper proposes a coordinated stochastic model for studying the interdependence of electricity and natural gas transmission networks (referred to as EGTran). The coordinated model incorporates the stochastic power system conditions into the solution of security-constrained unit commitment problem with natural gas network constraints. The stochastic model considers random outages of generating units and transmission lines, as well as hourly forecast errors of day-ahead electricity load. The Monte Carlo simulation is applied to create multiple scenarios for the simulation of the uncertainties in the EGTran model. The nonlinear natural gas network constraints are converted into linear constraints and incorporated into the stochastic model. Numerical tests are performed in a six-bus system with a seven-node gas transmission network and the IEEE 118–bus power system with a ten-node gas transmission network. Numerical results demonstrate the effectiveness of EGTran to analyze the impact of random contingencies on power system operations with natural gas network constraints. The proposed EGTran model could be utilized by grid operators for the short-term commitment and dispatch of power systems in highly interdependent conditions with relatively large natural gas-fired generating units.

Integrated Transmission and Distribution System Power Flow and Dynamic Simulation Using Mixed Three-Sequence/Three-Phase Modeling

Abstract: The interactions between distribution and transmission systems have increased significantly in recent years. However, in traditional power system simulation tools, transmission and distribution systems are separately modeled and analyzed. Hence, it is difficult to analyze the impacts of distribution systems on transmission systems and their interactions in detail. To facilitate the analysis of integrated transmission and distribution (T&D) systems, a novel modeling framework is proposed in this paper, where the transmission system is modeled as one subsystem in three-sequence detail, while each distribution system connected to it is represented as a subsystem and modeled in three-phase detail. With this modeling approach, unbalanced conditions at the boundary between T&D systems and within the transmission system can be represented. The integrated T&D power flow is solved by iteratively solving a three-sequence power flow for the transmission system and a three-phase power flow for each distribution system. Furthermore, a new dynamic simulation algorithm for integrated T&D system is proposed. The main challenge in developing this integrated T&D dynamic simulation is associated with different network representations in the transmission and distribution systems. With a partitioned solution approach adopted for dynamic simulation, the multi-area Thevenin equivalent approach is utilized in the network solution step to address this challenge. The proposed algorithms have been tested against an all electromagnetic transient simulation.

Security-Constrained Unit Commitment With Flexible Uncertainty Set for Variable Wind Power

Abstract: Power system operation has recently witnessed major challenges, which are often due to large-scale integrations of wind power generation. In this paper, a two-stage robust security-constrained unit commitment (SCUC) model is proposed for managing the wind power uncertainty in the hourly scheduling of power system generation. Different from previous studies on robust SCUC, which considered a predefined uncertainty set, the proposed method applies a flexible uncertainty set for managing the variable wind power generation. The proposed method seeks a feasible and economic dispatch in the flexible uncertainty set, takes into account wind spillage and load curtailment risks, and makes a tradeoff between the optimal wind power absorption and the economic grid operation. Several case studies are applied to the proposed method and the corresponding solutions are analyzed in the paper. The impacts of major factors, including flexible generation resources and power transmission capacity, on the proposed solution are also discussed. The numerical results demonstrate the merits of the proposed method for managing large variations in the hourly wind power generation and lowering the power system operation cost in uncertain conditions.

PyPSA: Python for Power System Analysis

Abstract: Python for Power System Analysis (PyPSA) is a free software toolbox for simulating and optimising modern electrical power systems over multiple periods. PyPSA includes models for conventional generators with unit commitment, variable renewable generation, storage units, coupling to other energy sectors, and mixed alternating and direct current networks. It is designed to be easily extensible and to scale well with large networks and long time series. In this paper the basic functionality of PyPSA is described, including the formulation of the full power flow equations and the multi-period optimisation of operation and investment with linear power flow equations. PyPSA is positioned in the existing free software landscape as a bridge between traditional power flow analysis tools for steady-state analysis and full multi-period energy system models. The functionality is demonstrated on two open datasets of the transmission system in Germany (based on SciGRID) and Europe (based on GridKit).

Chance-Constrained Two-Stage Unit Commitment Under Uncertain Load and Wind Power Output Using Bilinear Benders Decomposition

Abstract: In this paper, we study unit commitment (UC) problems considering the uncertainty of load and wind power generation. UC problem is formulated as a chance-constrained two-stage stochastic programming problem where the chance constraint is used to restrict the probability of load imbalance. In addition to the conventional mixed integer linear programming formulation using Big-M, we present the bilinear mixed integer formulation of chance constraint, and then derive its linear counterpart using the McCormick linearization method. Then, we develop a bilinear variant of the Benders decomposition method, which is an easy-to-implement algorithm, to solve the resulting large-scale linear counterpart. Our results on typical IEEE systems demonstrate that (i) the bilinear mixed integer programming formulation is stronger than the conventional one and (ii) the proposed Benders decomposition algorithm is generally an order of magnitude faster than using a professional solver to directly compute both linear and bilinear chance-constrained UC models.

Power System Toolbox

Abstract: This chapter provides some insights into the dynamic simulation programs and typical model parameters so that a reader can become a more proficient user. It then discusses the Power System Toolbox (PST), a MATLAB‐based power system simulation software, which is fairly straightforward to learn and use. Power flow computation is the determination of the steady‐state flow of power from the generators to the loads. The chapter covers the power flow data requirements, provides brief descriptions of the algorithms, and illustrates with an example. A power flow formulation requires generation and load as the bus data, and the power network connections as the branch data. A general purpose simulation program provides a large variety of dynamic models to choose from. These models are standardized so that equipment manufacturers can provide dynamic data for performance verification in simulation programs.

Risk Adjustable Day-Ahead Unit Commitment With Wind Power Based on Chance Constrained Goal Programming

Abstract: The impact of wind power forecast uncertainty has been amplified by the deepening wind power penetration. To guarantee system security and reliability, sufficient dispatchable generation and transmission capacities have to be reserved. Currently, research has been carried out to improve system operational performance by optimizing schedules considering uncertainty. However, most methods are designed to cover a given risk level of uncertainty, which is determined ex ante . With the increase in wind power capacity, defining the risk level a priori without considering the unit commitment (UC) may limit the scheduling efficiency. Essentially, there is no absolute standard for acceptable risk exposure. Instead, there is a tradeoff between the risk and the cost of reserve capacity. Therefore, it is necessary to develop a tool to enable a flexible and comprehensive consideration of the risk level. In this paper, by combining chance constrained programming and goal programming, a novel model based on chance constrained goal programming is proposed to optimize the risk adjustable UC problem. To facilitate an efficient solution, the proposed model is transferred into a tractable mixed integer linear programming problem by a deterministic equivalent and piecewise linearization. Case studies are performed on an IEEE 118-bus system to illustrate the effectiveness and efficiency of the model.

Integration of power-to-hydrogen in day-ahead security-constrained unit commitment with high wind penetration

Abstract: The increasing integration of variable wind generation has aggravated the imbalance between electricity supply and demand. Power-to-hydrogen (P2H) is a promising solution to balance supply and demand in a variable power grid, in which excess wind power is converted into hydrogen via electrolysis and stored for later use. In this study, an energy hub (EH) with both a P2H facility (electrolyzer) and a gas-to-power (G2P) facility (hydrogen gas turbine) is proposed to accommodate a high penetration of wind power. The EH is modeled and integrated into a security-constrained unit commitment (SCUC) problem, and this optimization problem is solved by a mixed-integer linear programming (MILP) method with the Benders decomposition technique. Case studies are presented to validate the proposed model and elaborate on the technological potential of integrating P2H into a power system with a high level of wind penetration (HWP).

Adaptive Robust Network-Constrained AC Unit Commitment

Abstract: This paper presents an adaptive robust network-constrained AC unit commitment (AC-UC) model. This model is formulated as a min–max–min optimization problem, which allows representing the uncertain nature of wind power productions in terms of bounded intervals. A tri-level decomposition algorithm using primal and dual cutting planes is introduced to solve this AC-UC problem and to find a robust commitment schedule withstanding the worst realizations of uncertain wind power. To reduce the computation burden and to obtain a tractable formulation, the AC power flow equations are convexified using a Signomial transformation. The proposed AC-UC model is illustrated using the IEEE 24-bus reliability test system. Simulation results demonstrate the efficiency of the proposed approach.

Generic Dynamic Models for Modeling Wind Power Plants and Other Renewable Technologies in Large-Scale Power System Studies

Abstract: With the tremendous growth of wind power worldwide in the past decade, there has been an equally great demand for simplified, standard, and publicly available models for simulating wind power generators in commercially available power system simulation tools for stability analysis. Several efforts have been on the way to meet this need. The Western Electricity Coordinating Council's Renewable Energy Modeling Task Force has successfully achieved this goal and more recently has been working on expanding these models to include the ability to model complex plants, energy storage, and frequency response capabilities. This paper presents an account of these latest developments.

Wind-Friendly Flexible Ramping Product Design in Multi-Timescale Power System Operations

Abstract: With increasing wind power penetration in the electricity grid, system operators are recognizing the need for additional flexibility, and some are implementing new ramping products as a type of ancillary service. However, wind is generally thought of as causing the need for ramping services, not as being a potential source for the service. In this paper, a multi-timescale unit commitment and economic dispatch model is developed to consider the wind power ramping product (WPRP). An optimized swinging door algorithm with dynamic programming is applied to identify and forecast wind power ramps (WPRs). Designed as positive characteristics of WPRs, the WPRP is then integrated into the multi-timescale dispatch model that considers new objective functions, ramping capacity limits, active power limits, and flexible ramping requirements. Numerical simulations on the modified IEEE 118-bus system show the potential effectiveness of WPRP in increasing the economic efficiency of power system operations with high levels of wind power penetration. It is found that WPRP not only reduces the production cost by using less ramping reserves scheduled by conventional generators, but also possibly enhances the reliability of power system operations. Moreover, wind power forecasts play an important role in providing high-quality WPRP service.

Flexible power system operation accommodating uncertain wind power generation using transmission topology control: an improved linearised AC SCUC model

Abstract: Stochastic security constrained unit commitment (SSCUC) based on a DC model could be problematic in AC networks because the DC model is potentially inaccurate. However, solving SSCUC problems using an AC model is still very challenging. Accordingly, an improved linearised AC optimal power flow (ILACOPF) model is provided in order to optimise the SSCUC problem. The proposed SSCUC model includes a linear representation of network losses and reactive power and bus voltage magnitudes. Moreover, in this study, transmission switching (TS), a powerful tool for grid side flexibility, is introduced and utilised to facilitate the mitigation of the uncertainty of wind power generation. Nevertheless, solving the SSCUC problem with TS in a full AC network is still one of the challenges in practical implementation, which is facilitated by the proposed ILACOPF model. Additionally, the aim of this study is to develop a more accurate power flow model to obtain a more realistic SSCUC solution using TS. The proposed ILAC-SSCUC model using TS is formulated as a mixed-integer linear programme, being solved by the proposed effective solution approach based on Benders’ decomposition. Numerical simulations on a 6-bus and IEEE 118-bus systems have been performed to evaluate the effectiveness of the method.

Stochastic Multi-Timescale Power System Operations With Variable Wind Generation

Abstract: This paper describes an integrated operational simulation tool that combines various stochastic unit commitment and economic dispatch models together that consider stochastic loads and variable generation at multiple operational timescales. The tool includes four distinct configurable sub-models within: day-ahead security-constrained unit commitment (SCUC), real-time SCUC, real-time security-constrained economic dispatch (SCED), and automatic generation control (AGC). The unit commitment and dispatch sub-models within can be configured to meet multiple load and variable generation (VG) scenarios with configurable first stage and second-stage decisions determined where first-stage decisions are passed on and second-stage decisions are later determined by other sub-models in a continuous manner. The progressive hedging algorithm (PHA) is applied to solve the stochastic models to maintain the computational tractability of the proposed models. Comparative case studies, considering various configurations of stochastic and deterministic sub-models are conducted in low wind and high wind penetration scenarios to highlight the advantages of the stochastic programming during different decision-making processes. The effectiveness of the proposed method is evaluated with sensitivity tests using both economic and short-term reliability metrics to provide a broader view of its impact at different timescales and decision-making processes.

Combined control and power hardware in-the-loop simulation for testing smart grid control algorithms

Abstract: Distribution networks are becoming increasingly ‘smarter’, as well as more complex, with the addition of power electronic devices, information and communication technologies, smart meters, and more. As a result, advanced control strategies to manage such networks are becoming necessary. These strategies need to be thoroughly tested and validated, before they can be implemented in a real network. For this reason, a smart grid control algorithm testing chain is proposed, that aims to gradually test control algorithms, in all their development stages, using increasingly advanced laboratory setups. In addition, the interfacing options and challenges of each stage of the chain are highlighted. The proposed testing chain is substantiated in an optimal centralised coordinated voltage control (CVC) algorithm and the final stage of the chain, namely the combination of control and power hardware-in-the-loop simulation, is presented in this study. As a specific example, the management technique for a storage system is implemented as part of the CVC algorithm. The laboratory results demonstrate that the proposed setup, despite its high complexity, enables the algorithm to be effectively and realistically tested as part of the overall system.

Distributed finite-time cooperative control of droop-controlled microgrids under switching topology

Abstract: As a small-scale power system, microgrid (MG) will lose support from the main grid if it switches to islanded mode because of the pre-planned scheduling or unplanned disturbances. To synchronise the frequency and voltage to their reference values, a secondary frequency and voltage cooperative control is proposed in this study. The proposed secondary control can synchronise the frequency and voltage to their reference values in finite time and achieve the active power sharing simultaneously. Moreover, it is suitable for switching communication architecture. The MG is considered as multi-agent systems and the system stability is proved by multi-agent theory and finite-time stability theory. A simulation system is established in Matlab/Simulink environment, and the results show the effectiveness of the proposed controller.