scholarly journals A Mixed-Integer Convex Programming Algorithm for Security-Constrained Unit Commitment of Power System with 110-kV Network and Pumped-Storage Hydro Units

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3646 ◽  
Author(s):  
Shunjiang Lin ◽  
Guansheng Fan ◽  
Yuan Lu ◽  
Mingbo Liu ◽  
Yi Lu ◽  
...  
Keyword(s):  
Convex Programming ◽  
Power Flow ◽  
Large Scale ◽  
Unit Commitment ◽  
Power Grids ◽  
Mixed Integer ◽  
Regional Power ◽  
Central Cities ◽  
Active Power Flow ◽  
Pumped Storage

The secure operation of 110-kV networks should be considered in the optimal generation dispatch of regional power grids in large central cities. However, since 110-kV lines do not satisfy the premise of R << X in the direct current power flow (DCPF) model, the DCPF, which is mostly applied in the security-constrained unit commitment (SCUC) problem of high-voltage power grids, is no longer suitable for describing the active power flow of regional power grids in large central cities. Hence, the quadratic active power flow (QAPF) model considering the resistance of lines is proposed to describe the network security constraints, and an SCUC model for power system with 110-kV network and pumped-storage hydro (PSH) units is established. The analytical expressions of the spinning reserve (SR) capacity of PSH units are given considering different operational modes, and the SR capacity of PSH units is included in the constraint of the SR capacity requirement of the system. The QAPF is a set of quadratic equality constraints, making the SCUC model a mixed-integer nonlinear non-convex programming (MINNP) model. To reduce the computational complexity of solving the model when applied in actual large-scale regional networks, the QAPF model is relaxed by its convex hull, and the SCUC model is transformed into a mixed-integer convex programming (MICP) model, which can be solved to obtain the global optimal solution efficiently and reliably by the mature commercial solver GUROBI (24.3.3, GAMS Development Corporation, Guangzhou, China). Test results on the IEEE-9 bus system, the PEGASE 89 bus system and the Shenzhen city power grid including the 110-kV network demonstrate that the relaxed QAPF model has good calculation accuracy and efficiency, and it is suitable for solving the SCUC problem in large-scale regional networks.

scholarly journals Optimal Unit Commitment by Considering High Penetration of Renewable Energy and Ramp Rate of Thermal Units-A case study in Taiwan

2019 ◽  
Vol 9 (3) ◽  
pp. 421 ◽  
Author(s):  
Shiue-Der Lu ◽  
Meng-Hui Wang ◽  
Ming-Tse Kuo ◽  
Ming-Chang Tsou ◽  
Rui-Min Liao
Keyword(s):  
Power Generation ◽  
Renewable Energy ◽  
Large Scale ◽  
Unit Commitment ◽  
Computation Time ◽  
Power Grids ◽  
Mixed Integer ◽  
Ramp Rate ◽  
Priority List ◽  
Generation Cost

When large amounts of wind power and solar photovoltaic (PV) power are integrated into an independent power grid, the intermittent renewable energy destabilizes power output. Therefore, this study explored the unit commitment (UC) optimization problem; the ramp rate was applied to solve problems with 30 and 10 min of power shortage. The data of actual unit parameters were provided by the Taiwan Power Company. The advanced priority list method was used together with a combination of a generalized Lagrangian relaxation algorithm and a random feasible directions algorithm to solve a large-scale nonlinear mixed-integer programming UC problem to avoid local and infeasible solutions. The results showed that the proposed algorithm was superior to improved particle swarm optimization (IPSO) and simulated annealing (SA) in terms of the minimization of computation time and power generation cost. The proposed method and UC results can be effective information for unit dispatch by power companies to reduce the investment costs of power grids and the possibility of renewable energy being disconnected from the power system. Thus, the proposed method can increase the flexibility of unit dispatch and the proportion of renewable energy in power generation.

Determination of Marginal Power Flows Based on an Adaptive Gradual Load Increase Trajectory

Vestnik MEI ◽  
2021 ◽  
pp. 20-30
Author(s):  
Natalya L. Batseva ◽  
◽  
Vasiliy A. Sukhorukov ◽  
Keyword(s):  
Power Flow ◽  
Active Power ◽  
Power Grids ◽  
Small Signal ◽  
Mode Change ◽  
Operation Speed ◽  
Load Increase ◽  
Active Power Flow ◽  
Change Vector ◽  
The Difference

The aim of the study is to develop a technique for searching an adaptive gradual load increase trajectory for power grids with a chain structure and to test this technique on the monitored 500 kV backbone grid sections. The technique for searching an adaptive gradual load increase trajectory was developed proceeding from the theoretical data about the chain structures of power grids and about the specific features of their operation modes. The voltage levels at the 500 kV backbone grid nodes and normalized phase angles across the ties included in the studied section and in the adjacent monitored sections are adopted as criteria for monitoring loss of small-signal aperiodic stability in the section under study. Special attention is paid to active power flows through the monitored adjacent sections with respect to the section under study. The proposed technique was tested on two monitored sections of the backbone 500 kV grid. The numerical analysis results have shown that under certain grid configuration and mode conditions, the marginal active power flow determined according to the proposed technique is either higher than the marginal active power flow determined using the mode change vector with the difference between the values from 54 MW to 319 MW, or lower than the marginal flow, with the difference between the values from 121 MW to 228 MW. It has been established that the difference between the values is caused by higher or lower loading of the monitored adjacent sections with respect to the section under study. Grid configuration and mode conditions has also been found in which the marginal active power flows determined according to the proposed technique and the mode change vector are almost identical with one another with the difference making about 15 MW. The subsequent algorithmic implementation of the procedure and development of the relevant software will make it possible to apply it to a larger number of monitored sections and to study various grid configuration and mode conditions for accumulating statistical data. If the software operation speed requirements in a close-to-real-time mode are satisfied, the software will be adapted to the Stability Margin Monitoring System software package. On the whole, the testing of the proposed technique for chain-shaped grids allowed us to conclude that the procedure can be used for searching an adaptive gradual loading trajectory and determining marginal active power flows in regard of small-signal aperiodic stability using the power system analysis model corresponding to the current grid configuration and mode conditions.

scholarly journals A Novel Strategy to Reduce Computational Burden of the Stochastic Security Constrained Unit Commitment Problem

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3777
Author(s):  
Cristian Camilo Marín-Cano ◽  
Juan Esteban Sierra-Aguilar ◽  
Jesús M. López-Lezama ◽  
Álvaro Jaramillo-Duque ◽  
Juan G. Villegas
Keyword(s):  
Decision Making ◽  
Power Systems ◽  
Large Scale ◽  
Unit Commitment ◽  
Reaction Times ◽  
Mixed Integer ◽  
Feasible Region ◽  
Solution Strategy ◽  
Unit Commitment Problem ◽  
Joint Strategy

The uncertainty related to the massive integration of intermittent energy sources (e.g., wind and solar generation) is one of the biggest challenges for the economic, safe and reliable operation of current power systems. One way to tackle this challenge is through a stochastic security constraint unit commitment (SSCUC) model. However, the SSCUC is a mixed-integer linear programming problem with high computational and dimensional complexity in large-scale power systems. This feature hinders the reaction times required for decision making to ensure a proper operation of the system. As an alternative, this paper presents a joint strategy to efficiently solve a SSCUC model. The solution strategy combines the use of linear sensitivity factors (LSF) to compute power flows in a quick and reliable way and a method, which dynamically identifies and adds as user cuts those active security constraints N − 1 that establish the feasible region of the model. These two components are embedded within a progressive hedging algorithm (PHA), which breaks down the SSCUC problem into computationally more tractable subproblems by relaxing the coupling constraints between scenarios. The numerical results on the IEEE RTS-96 system show that the proposed strategy provides high quality solutions, up to 50 times faster compared to the extensive formulation (EF) of the SSCUC. Additionally, the solution strategy identifies the most affected (overloaded) lines before contingencies, as well as the most critical contingencies in the system. Two metrics that provide valuable information for decision making during transmission system expansion are studied.

scholarly journals Backbone—An Adaptable Energy Systems Modelling Framework

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3388 ◽  
Author(s):  
Niina Helistö ◽  
Juha Kiviluoma ◽  
Jussi Ikäheimo ◽  
Topi Rasku ◽  
Erkka Rinne ◽  
...  
Keyword(s):  
Power Plants ◽  
Large Scale ◽  
Unit Commitment ◽  
Energy Systems ◽  
Mixed Integer ◽  
Investment Planning ◽  
Planning And Scheduling ◽  
Modelling Framework ◽  
Wide Range ◽  
Systems Modelling

Backbone represents a highly adaptable energy systems modelling framework, which can be utilised to create models for studying the design and operation of energy systems, both from investment planning and scheduling perspectives. It includes a wide range of features and constraints, such as stochastic parameters, multiple reserve products, energy storage units, controlled and uncontrolled energy transfers, and, most significantly, multiple energy sectors. The formulation is based on mixed-integer programming and takes into account unit commitment decisions for power plants and other energy conversion facilities. Both high-level large-scale systems and fully detailed smaller-scale systems can be appropriately modelled. The framework has been implemented as the open-source Backbone modelling tool using General Algebraic Modeling System (GAMS). An application of the framework is demonstrated using a power system example, and Backbone is shown to produce results comparable to a commercial tool. However, the adaptability of Backbone further enables the creation and solution of energy systems models relatively easily for many different purposes and thus it improves on the available methodologies.

Study and Application on Real Time Optimum Operation for Plant Units

2005 ◽  
Author(s):  
Yanfen Liao ◽  
Jiejin Cai ◽  
Xiaoqian Ma
Keyword(s):  
Power Plant ◽  
Large Scale ◽  
Unit Commitment ◽  
Operating Cost ◽  
Target Function ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Coal Consumption ◽  
Allocation Model ◽  
Load Demand

The optimum unit commitment is to determine an optimal scheme which can minimize the system operating cost during a period while the load demand, operation constrains of the individual unit are simultaneously satisfied. Since it is characterized as a nonlinear, large scale, discrete, mixed-integer combinatorial optimization problem with constrains, it is always hard to find out the theoretical optimal solution. In this paper, a method combining the priority-order with dynamic comparison is brought out to obtain an engineering optimal solution, and is validated in a power plant composed of three 200MW and two 300MW units. Through simulating the on-line running datum from the DCS system in the power plant, the operating cost curves are obtained in different units, startup/shut-down mode and load demand. According to these curves, an optimum unit commitment model is established based on equal incremental rate principle principle. Make target function be minimum gross coal consumption, the results show that compared with the duty-chief-mode that allocates the load based on operators’ experience, the units’ mean gross coal consumption rate is reduced about 0.5g/(kW·h) when operating by this unit commitment model, and its economic profit is far more than the load economic allocation model that doesn’t considered the units’ start-up/shut-down.

Optimal long-term unit commitment in large scale systems including fuel constrained thermal and pumped-storage hydro

1989 ◽  
Vol 4 (3) ◽  
pp. 1065-1073 ◽  
Author(s):  
K. Aoki ◽  
M. Itoh ◽  
T. Satoh ◽  
K. Nara ◽  
M. Kanezashi
Keyword(s):  
Large Scale ◽  
Unit Commitment ◽  
Large Scale Systems ◽  
Pumped Storage
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