scholarly journals A Market-Driven Management Model for Renewable-Powered Undergrid Mini-Grids

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7881
Author(s):  
Tatiana González Grandón ◽  
Fernando de Cuadra García ◽  
Ignacio Pérez-Arriaga
Keyword(s):  
Programming Model ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Spot Prices ◽  
Load Following ◽  
Comparison Results ◽  
Solar Battery ◽  
Operating Strategies ◽  
Uncertain Input ◽  
Hybrid Solar Battery

Renewable-powered “undergrid mini-grids” (UMGs) are instrumental for electrification in developing countries. An UMG can be installed under a—possibly unreliable— main grid to improve the local reliability or the main grid may “arrive” and connect to a previously isolated mini-grid. Minimising costs is key to reducing risks associated with UMG development. This article presents a novel market-logic strategy for the optimal operation of UMGs that can incorporate multiple types of controllable loads, customer smart curtailment based on reliability requirements, storage management, and exports to and imports from a main grid, which is subject to failure. The formulation results in a mixed-integer linear programming model (MILP) and assumes accurate predictions of the following uncertain parameters: grid spot prices, outages of the main grid, solar availability and demand profiles. An AC hybrid solar-battery-diesel UMG configuration from Nigeria is used as a case example, and numerical simulations are presented. The load-following (LF) and cycle-charging (CC) strategies are compared with our predictive strategy and HOMER Pro’s Predictive dispatch. Results prove the generality and adequacy of the market-logic dispatch model and help assess the relevance of outages of the main grid and of spot prices above the other uncertain input factors. Comparison results show that the proposed market-logic operation approach performs better in terms of cost minimisation, higher renewable fraction and lower diesel use with respect to the conventional LF and CC operating strategies.

scholarly journals Integrated day-ahead energy procurement and production scheduling

2018 ◽  
Vol 66 (11) ◽  
pp. 950-963 ◽  
Author(s):  
Egidio Leo ◽  
Sebastian Engell
Keyword(s):  
Production Scheduling ◽  
Programming Model ◽  
Production Capacity ◽  
Electricity Consumption ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Production Schedule ◽  
Sources Of Uncertainty ◽  
Continuous Power ◽  
The Cost

Abstract For the optimal operation of power-intensive plants, a challenge which is addressed in this work is to simultaneously determine the optimal production schedule and the optimal day-ahead electricity commitment. In order to ensure stability of the power grid, the electricity suppliers impose a daily electricity commitment to large consumers. The consumers have to commit one day in advance to the amount of energy they are going to purchase and use for a horizon of 24 hours (with an hourly discretization) and in case the actual electricity consumption differs significantly from the committed profile, the consumer is obliged to pay penalties. Since the consumers have to commit to the electricity suppliers before the actual electricity demand is known, uncertainty needs to be taken into account. A stochastic mixed-integer linear programming model is developed to consider two critical sources of uncertainty: equipment breakdowns and deviation prices. Equipment breakdowns can reduce the production capacity and make the actual electricity consumption deviate from the day-ahead electricity commitment. The application of the proposed approach to a continuous power-intensive plant shows the benefit gained from the solution of the stochastic model instead of the deterministic counterpart in terms of reduction of the cost of the energy.

scholarly journals Optimal Operation of Soft Open Points-Based Energy Storage in Active Distribution Networks by Considering the Battery Lifetime

2021 ◽  
Vol 8 ◽  
Author(s):  
Jian Wang ◽  
Niancheng Zhou ◽  
Anqi Tao ◽  
Qianggang Wang
Keyword(s):  
Energy Storage ◽  
Reactive Power ◽  
Programming Model ◽  
Distribution Networks ◽  
Optimal Operation ◽  
Mixed Integer ◽  
Operation Model ◽  
Battery Lifetime ◽  
Battery Degradation ◽  
Active Distribution Networks

Soft open point-based energy storage (SOP-based ES) can transfer power in time and space and also regulate reactive power. These characteristics help promote the integration of distributed generations (DGs) and reduce the operating cost of active distribution networks (ADNs). Therefore, this work proposed an optimal operation model for SOP-based ES in ADNs by considering the battery lifetime. First, the active and reactive power equations of SOP-based ES and battery degradation cost were modeled. Then, the optimal operation model that includes the operation cost of ADNs, loss cost, and battery degradation cost was established. The mixed integer nonlinear programming model was transformed to a mixed integer linear programming model derived through linearization treatment. Finally, the feasibility and effectiveness of the proposed optimization model are verified by the IEEE33 node system.

Optimization of Thermal Power Plants Operation in the German De-Regulated Electricity Market Using Dynamic Programming

2012 ◽  
Author(s):  
G. Scarabello ◽  
S. Rech ◽  
A. Lazzaretto ◽  
A. Christidis ◽  
G. Tsatsaronis
Keyword(s):  
Electricity Market ◽  
Power Plants ◽  
Thermal Power ◽  
Optimal Operation ◽  
Renewable Energies ◽  
Combined Cycle ◽  
Mixed Integer ◽  
Programming Approach ◽  
Thermal Power Plants ◽  
Spot Prices

The prospect of clean electrical energy generation has recently driven to massive investments on renewable energies, which in turn has affected operation and profits of existing traditional thermal power plants. In this work several coal-fired and combined cycle power units are simulated under design and off-design conditions to adequately represent the behavior of all modern thermal units included in the German power system. A dynamic optimization problem is then solved to estimate the short-run profits obtained by these units using the spot prices of the German electricity market (EEX) in years 2007–2010. The optimization model is developed using a Mixed Integer Linear Programming approach to take the on-off status into account and reduce computational effort. New market scenarios with increasing renewable shares (and consequently different spot prices) are finally simulated to analyze the consequences of a larger capacity of renewable energies on the optimal operation of traditional thermal power plants.

scholarly journals Optimal Design of Isolated Mini-Grids with Deterministic Methods: Matching Predictive Operating Strategies with Low Computational Requirements

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4214 ◽  
Author(s):  
Andrea Micangeli ◽  
Davide Fioriti ◽  
Paolo Cherubini ◽  
Pablo Duenas-Martinez
Keyword(s):  
Optimal Design ◽  
Rural Areas ◽  
Search Space ◽  
Mixed Integer ◽  
Computational Time ◽  
Swarm Optimization ◽  
Load Following ◽  
Operating Strategies ◽  
Electricity Access ◽  
Better Than

The lack of electricity access is increasingly concentrated in rural areas of developing countries, in which mini-grids are often a suitable solution; however, given the high risks, it is crucial to minimize costs. This paper aims at analyzing existing methodologies for the optimal design of mini-grids combined with different operating strategies. Typical system operations, like the load-following (LFS) and cycle charging (CCS) strategies, are compared with the more demanding predictive strategies based on Mixed-Integer Linear Programming (MILP). The problem is formulated and solved with Particle Swarm Optimization (PSO), so to simulate traditional and predictive operating strategies. Two reformulations based on the proposed Search Space Update are also detailed and compared with the so-called one-shot MILP model, which is able to con-jointly optimize both the design and the operation of the system, in order to reduce computational requirements with the predictive strategy. The results, tailored with data from a rural mini-grid in Kenya, highlight that heuristic methodologies can perform better than the traditional MILP approach, both in terms of optimality and computational time, especially when advanced operating strategies are considered. Conventional operating strategies (LFS or CCS) appear to be sub-optimal, but require very little computational requirements, which makes them suitable for preliminary designs.

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.

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