scholarly journals Manual Frequency Restoration Reserve Activation Clearing Model

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5793
Author(s):  
Christos Roumkos ◽  
Pandelis N. Biskas ◽  
Ilias Marneris
Keyword(s):  
Programming Model ◽  
Mixed Integer ◽  
Second Step ◽  
Spot Markets ◽  
Activation Process ◽  
Whole Process ◽  
Balancing Energy ◽  
The Cross ◽  
Frequency Restoration Reserve ◽  
European Markets

The integration of the European markets has started with the successful coupling of spot markets (day-ahead and intra-day) and is expected to continue with the coupling of balancing markets. In this paper, the optimization model for the activation of manual frequency restoration reserve (mFRR) is presented. The model incorporates all order types agreed among the European transmission system operators (TSOs) to be included in the Manually Activated Reserves Initiative (MARI) project. Additionally, the model incorporates the buying curve (demand) of mFRR with the possible tolerance band defined by the TSOs, order clearing constraints and the cross-zonal capacity (CZC) constraints, forming a mixed integer linear programming model. The methodology employs two distinct steps: In the first step, an order conversion process is employed for the markets applying the central-scheduling scheme, and in the second step, the mFRR activation process is executed by solving the presented model. The whole process is tested using a case, including twenty-five European control areas. The attained clearing results indicate that price convergence is achieved among the involved control areas, along with a reduction in the overall balancing costs mainly due to the imbalance netting that is implicitly performed during the joint mFRR balancing energy (BE) clearing process and due to the cross-border exchange of mFRR BE.

scholarly journals A Dynamic Shelter Location and Victim Resettlement Model Considering Equitable Waiting Costs

2020 ◽  
Vol 17 (2) ◽  
pp. 471 ◽  
Author(s):  
Donghai Wang ◽  
Menghao Xi ◽  
Yingzhen Chen
Keyword(s):  
Programming Model ◽  
Homeless People ◽  
Mixed Integer ◽  
Yushu Earthquake ◽  
Location Allocation ◽  
Whole Process ◽  
Allocation Process ◽  
General Algebraic Modeling System ◽  
Waiting Cost

Catastrophic natural disasters cause devastating damage and leave a huge number of homeless people. Waiting for resettlement in a post-disaster environment brings human suffering, which is defined by waiting cost in this paper. Taking into account waiting cost and fairness consideration simultaneously, a mixed integer linear programming model is constructed for the multiperiod location-allocation process. Two fairness indicators are incorporated to guarantee both the whole-process equity and the periodic equity. The model is implemented in the General Algebraic Modeling System (GAMS) and solved by the CPLEX solver. An illustrative example is provided to explain the model characteristics. Furthermore, a case study of the Yushu earthquake is conducted to demonstrate the applicability of the model to practical problems.

scholarly journals Modeling Framework Simulating the TERRE Activation Optimization Function

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2966
Author(s):  
Christos Roumkos ◽  
Pandelis Biskas ◽  
Ilias Marneris
Keyword(s):  
Programming Model ◽  
Mathematical Formulation ◽  
Mixed Integer ◽  
Test Case ◽  
Modeling Framework ◽  
Implementation Framework ◽  
Proposed Model ◽  
Balancing Energy ◽  
Optimization Function ◽  
Optimized Allocation

The Trans-European Replacement Reserve Exchange (TERRE) project is the European implementation project for exchanging Balancing Energy (BE) from Replacement Reserves (RR). Its main objective is to operate a common European platform that gathers all RR Balancing Energy Orders (BEOs) from Transmission System Operators’ (TSOs) local BE markets into a Common Merit Order List (CMOL). It provides an optimized allocation of RR, covering all TSOs’ RR BE needs, by executing the Activation Optimization Function (AOF). In this paper, the mathematical formulation of the AOF is presented, which explicitly incorporates all standard products and constraints that are provisioned in the approved implementation framework. The clearing problem is formulated as a Mixed Integer Linear Programming model and solved within an iterative algorithm for the handling of Paradoxically Accepted Orders (PAOs). The modeling framework allows the coordination of two distinct market setups, i.e., the self-dispatch and central dispatch. To this end, a BEO conversion pre-process is executed for markets applying the central-dispatch setup, in order to attain the BE quantities for inclusion in the CMOL. The proposed model is evaluated using a test case including six countries that participate in the TERRE project (Portugal, Spain, France, Great Britain, Switzerland, Italy) as well as Greece.

Analysis on the Penetration Level of Wind Farm Considering Transient Stability Constraint and Uncertainty of Wind Power

2020 ◽  
Vol 13 (7) ◽  
pp. 1078-1086
Author(s):  
Bai Hao ◽  
Huang Andi ◽  
Zhou Changcheng
Keyword(s):  
Wind Power ◽  
Energy Function ◽  
Wind Farm ◽  
Transient Stability ◽  
Programming Model ◽  
Forecast Error ◽  
Credibility Theory ◽  
Mixed Integer ◽  
Stability Constraint ◽  
Level Problem

Background: The penetration level of a wind farm with transient stability constraint and static security constraint has been a key problem in wind power applications. Objective: The study explores maximum penetration level problem of wind considering transient stability constraint and uncertainty of wind power out, based on credibility theory and corrected energy function method. Methods: According to the corrected energy function, the transient stability constraint of the power grid is transferred to the penetration level problem of a wind farm. Wind speed forecast error is handled as a fuzzy variable to express the uncertainty of wind farm output. Then this paper builds a fuzzy chance-constrained model to calculate wind farm penetration level. To avoid inefficient fuzzy simulation, the model is simplified to a mixed integer linear programming model. Results: The results validate the proposed model and investigate the influence of grid-connection node, wind turbine characteristic, fuzzy reliability index, and transient stability index on wind farm penetration level. Conclusion: The result shows that the model proposed in this study can consider the uncertainty of wind power out and establish a quantitative transient stability constraint to determine the wind farm penetration level with a certain fuzzy confidence level.

scholarly journals Optimal Placement and Sizing of D-STATCOM in Radial and Meshed Distribution Networks Using a Discrete-Continuous Version of the Genetic Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1452
Author(s):  
Cristian Mateo Castiblanco-Pérez ◽  
David Esteban Toro-Rodríguez ◽  
Oscar Danilo Montoya ◽  
Diego Armando Giral-Ramírez
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimization Method ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Power Balance ◽  
Continuous Version ◽  
Discrete Part

In this paper, we propose a new discrete-continuous codification of the Chu–Beasley genetic algorithm to address the optimal placement and sizing problem of the distribution static compensators (D-STATCOM) in electrical distribution grids. The discrete part of the codification determines the nodes where D-STATCOM will be installed. The continuous part of the codification regulates their sizes. The objective function considered in this study is the minimization of the annual operative costs regarding energy losses and installation investments in D-STATCOM. This objective function is subject to the classical power balance constraints and devices’ capabilities. The proposed discrete-continuous version of the genetic algorithm solves the mixed-integer non-linear programming model that the classical power balance generates. Numerical validations in the 33 test feeder with radial and meshed configurations show that the proposed approach effectively minimizes the annual operating costs of the grid. In addition, the GAMS software compares the results of the proposed optimization method, which allows demonstrating its efficiency and robustness.

scholarly journals New general mixed-integer linear programming model for mobile workforce management

2021 ◽  
Author(s):  
András Éles ◽  
István Heckl ◽  
Heriberto Cabezas
Keyword(s):  
Programming Model ◽  
Time Windows ◽  
Mutual Exclusion ◽  
Parallel Execution ◽  
Mixed Integer ◽  
Management Problem ◽  
Routing Problem ◽  
Workforce Management ◽  
Computational Performance ◽  
Wide Range

AbstractA mathematical model is introduced to solve a mobile workforce management problem. In such a problem there are a number of tasks to be executed at different locations by various teams. For example, when an electricity utility company has to deal with planned system upgrades and damages caused by storms. The aim is to determine the schedule of the teams in such a way that the overall cost is minimal. The mobile workforce management problem involves scheduling. The following questions should be answered: when to perform a task, how to route vehicles—the vehicle routing problem—and the order the sites should be visited and by which teams. These problems are already complex in themselves. This paper proposes an integrated mathematical programming model formulation, which, by the assignment of its binary variables, can be easily included in heuristic algorithmic frameworks. In the problem specification, a wide range of parameters can be set. This includes absolute and expected time windows for tasks, packing and unpacking in case of team movement, resource utilization, relations between tasks such as precedence, mutual exclusion or parallel execution, and team-dependent travelling and execution times and costs. To make the model able to solve larger problems, an algorithmic framework is also implemented which can be used to find heuristic solutions in acceptable time. This latter solution method can be used as an alternative. Computational performance is examined through a series of test cases in which the most important factors are scaled.

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