scholarly journals Robust Optimization for Electricity Generation

2020 ◽  
Author(s):  
Haoxiang Yang ◽  
David P. Morton ◽  
Chaithanya Bandi ◽  
Krishnamurthy Dvijotham
Keyword(s):  
Renewable Energy ◽  
Robust Optimization ◽  
Electric Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Optimization Problem ◽  
Convex Relaxation ◽  
Electric Power System ◽  
Robust Convex Optimization ◽  
Robust Optimization Problem

We consider a robust optimization problem in an electric power system under uncertain demand and availability of renewable energy resources. Solving the deterministic alternating current (AC) optimal power flow (ACOPF) problem has been considered challenging since the 1960s due to its nonconvexity. Linear approximation of the AC power flow system sees pervasive use, but does not guarantee a physically feasible system configuration. In recent years, various convex relaxation schemes for the ACOPF problem have been investigated, and under some assumptions, a physically feasible solution can be recovered. Based on these convex relaxations, we construct a robust convex optimization problem with recourse to solve for optimal controllable injections (fossil fuel, nuclear, etc.) in electric power systems under uncertainty (renewable energy generation, demand fluctuation, etc.). We propose a cutting-plane method to solve this robust optimization problem, and we establish convergence and other desirable properties. Experimental results indicate that our robust convex relaxation of the ACOPF problem can provide a tight lower bound.

scholarly journals Hybrid Imperialist Competitive and Grey Wolf Algorithm to Solve Multiobjective Optimal Power Flow with Wind and Solar Units

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2891 ◽  
Author(s):  
Jalel Ben Hmida ◽  
Mohammad Javad Morshed ◽  
Jim Lee ◽  
Terrence Chambers
Keyword(s):  
Power Systems ◽  
Electric Power ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Flow Analysis ◽  
Electric Power System ◽  
Energy Integration ◽  
Grey Wolf ◽  
Optimal Power ◽  
Grey Wolf Algorithm

The optimal power flow (OPF) module optimizes the generation, transmission, and distribution of electric power without disrupting network power flow, operating limits, or constraints. Similarly to any power flow analysis technique, OPF also allows the determination of system’s state of operation, that is, the injected power, current, and voltage throughout the electric power system. In this context, there is a large range of OPF problems and different approaches to solve them. Moreover, the nature of OPF is evolving due to renewable energy integration and recent flexibility in power grids. This paper presents an original hybrid imperialist competitive and grey wolf algorithm (HIC-GWA) to solve twelve different study cases of simple and multiobjective OPF problems for modern power systems, including wind and photovoltaic power generators. The performance capabilities and potential of the proposed metaheuristic are presented, illustrating the applicability of the approach, and analyzed on two test systems: the IEEE 30 bus and IEEE 118 bus power systems. Sensitivity analysis has been performed on this approach to prove the robustness of the method. Obtained results are analyzed and compared with recently published OPF solutions. The proposed metaheuristic is more efficient and provides much better optimal solutions.

scholarly journals Evaluation of Wind Energy Accommodation Based on Two-Stage Robust Optimization

2020 ◽  
Vol 26 (3) ◽  
pp. 61-68
Author(s):  
Kunpeng Tian ◽  
Weiqing Sun ◽  
Dong Han ◽  
Ce Yang
Keyword(s):  
Renewable Energy ◽  
Power System ◽  
Wind Energy ◽  
Robust Optimization ◽  
Optimization Problem ◽  
Mixed Integer ◽  
Master Problem ◽  
Two Stage ◽  
Energy Accommodation ◽  
Robust Optimization Problem

Large-scale renewable energy integration brings unprecedented challenges to electric power system planning and operation. The paper aims at economic dispatch and the safe operation of high penetration renewable energy power systems. According to the principle of power system dispatchability, the assessment of wind energy accommodation is formulated into a two-stage robust optimization problem with a min-max-min structure. Based on the benders algorithm, the intractable robust optimization problem is transformed into the form of sub-problem and master problem. Strong duality theory and big-M method are used to recast the sub problem into a mixed integer linear programming. The envelope of wind energy accommodation can be obtained by using commercial software to solve the master problem and sub problem alternately. For the realization of arbitrary wind power within the envelope, the amount of wind energy leakage and load shedding in power system operation are acceptable. An example of modified IEEE 39-bus test systems is used to verify the effectiveness and practicability of the evaluation method.

scholarly journals Methodology of optimum unit commitment of energy systems with renewable energy sources

Vestnik IGEU ◽  
2020 ◽  
pp. 25-38
Author(s):  
S.G. Obukhov ◽  
G.N. Klimova ◽  
A. Ibrahim
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
Electric Power ◽  
Optimization Problem ◽  
Unit Commitment ◽  
Renewable Energy Sources ◽  
Electric Power Systems ◽  
Electric Power System ◽  
Energy Sources ◽  
Particle Swarm Algorithm

One of the promising ways to improve the reliability and efficiency of power supply for customers in the areas remote from central electrical grid is the use of hybrid power systems with renewable energy sources. The primary task of designing such systems is the unit commitment of the generating equipment that provides the optimal technical and economic indexes of the electric power system. The stochastic nature of generation and nonlinearity of the characteristics of power plants cause a high complexity of solving this problem, which, from a mathematical point of view, is formulated as an optimization problem. An accurate and reliable solution of this optimization problem increases the efficiency of design and operation of hybrid electric power systems with renewable energy sources. And it is a vital task of modern power industry. A probabilistic-statistical methods and models for the analysis of experimental data are used to construct climatic time series and graphs of electrical loads. In addition, to study the operating modes of the electric power system the MatLab system is used for the simulation and modeling, and an evolutionary particle swarm algorithm is used to solve the optimization problem. The original model of solar radiation is used as a part of this methodology. This model provides forecasting the key characteristics of solar radiation in any geographical point of Russia including the areas that have no results of routine actinometric observation. Weibull distribution function is used to forecast daily variations of wind speed. It enhances the validity of forecasting of electricity generation of wind-driven power plant at daily time interval. As a result of the research, a method of optimum unit commitment has been developed for the equipment of electric power systems based on renewable energy sources. The use of the particle swarm algorithm as a part of the methodology provides reliable and accurate determination of the extremum of the objective function, which increases the efficiency of design and operation of hybrid electric power systems with renewable energy sources. The method has been tested on practical examples of optimum unit commitment for the equipment of electric power systems of various configurations and has proven its effectiveness. The technique is implemented as a software application, which ensures the convenience of its practical application. The obtained results can be used by companies involved in the design and operation of electric power systems using renewable energy generating units.

scholarly journals Towards 100% Renewables by 2030: Transition Alternatives for a Sustainable Electricity Sector in Isla de la Juventud, Cuba

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2862
Author(s):  
Mika Korkeakoski
Keyword(s):  
Renewable Energy ◽  
Power System ◽  
Electric Power ◽  
Renewable Energy Sources ◽  
Electric Power System ◽  
Electricity Production ◽  
Energy Sources ◽  
Cuban Government ◽  
Isla De La Juventud ◽  
Near Future

Renewable Energy Sources (RES) have become increasingly desirable worldwide in the fight against global climate change. The sharp decrease in costs of especially wind and solar photovoltaics (PV) have created opportunities to move from dependency on conventional fossil fuel-based electricity production towards renewable energy sources. Renewables experience around 7% (in 2018) annual growth rate in the electricity production globally and the pace is expected to further increase in the near future. Cuba is no exception in this regard, the government has set an ambitious renewable energy target of 24% RES of electricity production by the year 2030. The article analyses renewable energy trajectories in Isla de la Juventud, Cuba, through different future energy scenarios utilizing EnergyPLAN tool. The goal is to identify the best fit and least cost options in transitioning towards 100% electric power systemin Isla de la Juventud, Cuba. The work is divided into analysis of (1) technical possibilities for five scenarios in the electricity production with a 40% increase of electricity consumption by 2030: Business As Usual (BAU 2030, with the current electric power system (EPS) setup), VISION 2030 (according to the Cuban government plan with 24% RES), Advanced Renewables (ARES, with 50% RES), High Renewables (HiRES, with 70% RES), and Fully Renewables (FullRES, with 100% RES based electricity system) scenarios and (2) defining least cost options for the five scenarios in Isla de la Juventud, Cuba. The results show that high penetration of renewables is technically possible even up to 100% RES although the best technological fit versus least cost options may not favor the 100% RES based systems with the current electric power system (EPS) setup. This is due to realities in access to resources, especially importation of state of the art technological equipment and biofuels, financial and investment resources, as well as the high costs of storage systems. The analysis shows the Cuban government vision of reaching 24% of RES in the electricity production by 2030 can be exceeded even up to 70% RES based systems with similar or even lower costs in the near future in Isla de la Juventud. However, overcoming critical challenges in the economic, political, and legal conditions are crucially important; how will the implementation of huge national capital investments and significant involvement of Foreign Direct Investments (FDI) actualize to support achievement of the Cuban government’s 2030 vision?

Sign in / Sign up

Export Citation Format

Share Document