This paper presents a fuzzy-multiple objective optimization methodology to plan stand-alone electricity generation systems. The optimization process considers three main objectives, namely technology cost, environmental and societal impacts. For each feasible solution of the Pareto set, a system reliability index is evaluated along the lifetime of the project. As a key contribution, the decision making process is carried out by applying a fuzzy satisfaction method (FSM). The FSM accounts simultaneously four key performance indexes (KPI): technical, economic, environmental and social. The novelty of the proposal lies on the inclusion of societal impact (local wealth creation) in the FSM used here to select the more appropriate solution. Previous contributions on FSM only accounts two of four indexes considered in this paper. The methodology was applied in a Colombian case study. The results show the importance of the simultaneous consideration of technical, economic, environmental and social objectives in the evaluation of off-grid energization solutions.

This paper aims at optimizing the energy management of a smart power plant composed of wind turbines coupled with a Lithium Ion storage device in order to fulfill a power production commitment to the utility grid. The application of this case study is typically related to islanded electric grids. Our work particularly investigates and compares two classes of energy management strategies for design purpose: a first capable of providing the global optimum of the power flow planning from a Linear Programming (LP) approach thanks to a priori knowledge of future events in the environment; a second, based on a classical control heuristic without any a priori knowledge on the future, applicable in real time. Beyond the future objectives in terms of system design (techno-economical sizing optimization), the comparison of both approaches also aims at improving the predefined heuristic from the analysis of the ideal reference provided by the global LP optimizer. In this scope, a linear power flow model of the power plant is developed in compliance with a LP solver (Cplex). A particular attention is paid to the techno-economic optimization including storage cost evaluation, commitment failure penalties and exploitation gains. Simulations and optimizations are carried out over one year in order to take variability and seasonal features of the wind potential into account.

In this article an optimal storage sizing based on technical and economical modeling is presented. A focus is made on wind power producers participating in day-ahead markets for island networks and energy storage using Li-Ion and H2/O2 batteries. The modeling approach is based on power flow models and detailed optimization-oriented techniques. An importance is given to the storage device ageing effects on the overall hybrid system levelized cost of the energy. The results are presented for the special case of renewable power integration in the French islands networks. The analysis obtained after the results shows the importance of this type of modeling tool for decision making during the initial conceptual design level.

The improvement of reliability indexes as the energy not supplied is a major issue in electricity markets. This paper proposes a new multiple-objective optimization formulation to solve the problem of outage rate reduction of electric transmission lines due to back-flashover phenomena from technical and economical viewpoint. The method allows us to determine the trade-offs (Pareto front) between the outage rate of the transmission line and the investment costs of adding insulation or reducing grounding impedance at each tower. Improved results are obtained when compared to the traditional approach based on a standardized tower-by-tower design. The use of different objectives provides a broad set of noninferior design solutions to the engineer in order to make the final selection when compared to the single-objective—construction costs—formulation, where the minimum cost solution is directly provided by the optimization algorithm. The proposed methodology was successfully tested on a real case consisting of a 230 kV transmission line project, 85.4 km long, with 180 towers.

This paper presents a cost-effective optimization model for transmission line lightning performance design. The objective is to determine the appropriate insulation level and a particular grounding scheme of each support for a given line outage rate requirement due to the back-flashover phenomena at a minimum overall cost. To ensure a minimum global investment cost, the constraints associated with the individual lightning behavior of each tower section are relaxed depending on the regional atmospheric activity and on the particular characteristics of the soil, and therefore on the costs of the required grounding and insulation systems at each tower location, enforcing the appropriate lightning behavior of the complete transmission line. The proposed model is based upon a linear-integer programing problem formulation and solutions are obtained from the application of a three-layer hierarchical design methodology. The proposal has been tested in a 230 kV transmission line, 85.4 km long, with 180 towers. Results are presented and compared with designs obtained through by a conventional grounding optimization with important reductions in investment costs, encouraging the use and further development of the methodology.

This paper presents the design of several reduced order robust control strategies for the air supply of a hybrid fuel cell power generator. The management of the air dynamic entering the fuel cell is assured by the control of the air flow of a compressor. The air supply subsystem is controlled to keep a desired oxygen excess ratio, thus improving the fuel cell dynamic performance. Robustness analysis studies are performed, these robust properties are contrasted with classic control strategies, demonstrating the advantage of the multivariable reduced order robust methodologies.

In this paper a techno-economic comparison of an energy storage system (ESS) sizing for three intermittent renewables, wind, wave and PV power, with regard to two electricity grid services is presented. The first service consists of output hourly smoothing, based on day-ahead power forecasts (S1). The second service supplies year-round guaranteed power (S2). This leads to an annual default time rate (DTR) for which the actual power supplied to the grid does not match the day-ahead power bid within a given tolerance. A heuristic optimization based on an Adaptive Storage Operation (ASO) scheduling is developed in this study. ASO enables the minimal 5%-DTR ESS capacity, power, energy and feed-in-tariffs to be inferred from the operating conditions, depending on tolerance. The simulations assess and compare the techno-economic viability and efficiency of every renewable sources coupled with ESS. PV power is more efficient with daylight hours restricted services and higher power levels can be guaranteed for S1. Wind and wave power are more suitable than PV for services dedicated to full-day power delivery, as in the case of S2. For hourly smoothing the forecast accuracy influence is studied and yields a high impact on techno-economic sizing. (C) 2016 Elsevier Ltd. All rights reserved.

Dans cet article, un modele de type flux d'energie pour une batterie Li-Ion est presente. Le modele decrit permet de simuler une batterie Li-Ion d'un point de vue systemique. Le but de la modelisation presentee est de proposer une solution, avec un cout de calcul reduit, au probleme de simulation avec des grands horizons d'etude (plusieurs annees). L'approche proposee est basee sur l'elaboration de cartographies a partir du modele dynamique de la batterie Li-Ion. Cette modelisation inclut aussi un modele macroscopique du vieillissement de la cellule, en considerant la degradation de la capacite de la batterie au cours du temps. Le modele global presente permet d'obtenir un bon compromis entre la precision dans l'estimation de l'etat de charge de la batterie et la vitesse de calcul de la simulation. L'originalite de l'approche consiste a calculer d'une facon precise et en un temps tres reduit l'energie effectivement chargee ou dechargee de la batterie.

This paper presents a technico-economical analysis of a Pelamis wave power generator coupled with a proposed air compression storage system. Ocean wave measurements and forecasts are used from a site near the city of Saint-Pierre in Reunion island, France. The insular context requires both smoothing and forecast of the output power from the wave power system. The storage system is a solution to meet this requirement Several power network services are defined by the utility operator in order to meet different load needs. The goal is to analyze the role of the proposed storage device for each desired network service. An optimization procedure, from previous works, based on available wave energy forecast, is used to compute the optimal storage size for each service. An economical analysis shows the feasibility from the addition of the storage device, as the hybrid source power output may be economically profitable compared to a raw wave power production. (C) 2014 Elsevier Ltd. All rights reserved.

In this paper a two level hierarchical methodology is presented for the integral design of hybrid power generation systems based on alternative renewable energy (ARE) systems using the net energy concept and considering technical, economical, societal as well as environmental aspects. Results are presented for the design of a small-scale hybrid renewable energy system using the proposed methodology in Margarita Island, Venezuela. The proposed methodology applies the integrated analytical hierarchy process (AHP) methodology to the selection of the best hybrid renewable energy system using the concept of net energy and is divided in two phases: a classic optimization process using levelized costs minimization and an AHP implementation for decision making problems. Under this methodology technical–economical aspects are considered as quantitative parameters, while social–environmental aspects depend largely on the criteria of the system planning engineers and future users of the system. Technical–economical aspects are considered using specialized software, used to optimize and compute the best configuration of an ARE project. Social–economical aspects are defined as a series of parameters that should be considered by the planning team, a meeting of experts or a community consensus on the project site. Several diesel price scenarios (low, intermediate and high) are considered. The results show the importance of the proposed tools for decision making problems.

In this paper, the control of the air supply system of a fuel cell power generator is addressed. The management of the air dynamic entering the fuel cell is assured by the control of the air flow of a compressor. The air supply subsystem is controlled to keep a desired oxygen excess ratio, this allows to improve the fuel cell performance. Linear Matrix Inequalities (LMI) tools are extensively used in this paper as a solution to the multivariable robust control problem. Robust multivariable H∞ controllers are considered. A special interest is also given to reduced order controllers, specifically simple PI structures with desired H∞ performances. The models used for control implementation were identified from measures on a real test-bench set-up. Two control strategies are proposed, first a speed controller for the air compressor is designed; then the problem of a robust control of the system subject to some model uncertainties is solved using the Linear Parameter Varying (LPV) approach. The validation of the closed-loop control strategies is achieved using time-domain simulation analysis and the gain scheduled approach.

In this paper, the control of the air supply system of a fuel cell power generator is addressed. The management of the air dynamic entering the fuel cell is assured by the control of the air flow of a compressor. The air supply subsystem is controlled to keep a desired oxygen excess ratio, this allows to improve the fuel cell performance. Linear Matrix Inequalities (LMI) tools are extensively used in this paper as a solution to the multivariable robust control problem. Robust multivariable H ∞ controllers are considered. A special interest is also given to reduced order controllers, specifically simple PI structures with desired H ∞ performances. The models used for control implementation were identified from measures on a real test-bench set-up. Two control strategies are proposed, first a speed controller for the air compressor is designed; then the problem of a robust control of the system subject to some model uncertainties is solved using the Linear Parameter Varying (LPV) approach. The validation of the closed-loop control strategies is achieved using time-domain simulation analysis and the gain scheduled approach.

In this paper a complete robustness analysis is per formed for a hybrid Fuel Cell/Supercapacitor genera tion system with power management, realized through the control of two identical boost power converters. Fo r the closed-loop control a previously proposed multi variable robust control is considered. The robust c ontrol strategy analyzed consists of a multivariable Propo rtional-Integral controller found using an algorith m with a Linear Matrix Inequalities (LMI) formulation prop osed by the authors in former works. The control actuators are the duty cycles of the boost power co nverters interfacing the Fuel Cell (FC) and the Supercapacitor (SC) with the system electrical load . The control effectively achieves stability and performance robustness for several considered parameter variations sets. Simulation results were obtai ned using µ-analysis theory and the experimental valida tion was achieved. The results obtained show the improvement of the system robustness with a strateg y that can be generalized as a robust control methodology.

In this paper a complete robust control synthesis is performed for a hybrid power generation structure composed by a Fuel Cell and a Supercapacitor. The control strategies are applied to the DC-DC boost power converters associated to each power source. Multivariable PI control with H∞ performance, H∞ full and reduced order controllers are designed and compared. The multivariable PI controller is designed through an optimization procedure based on solving some Linear Matrix Inequalities. A μ-analysis and frequency/time response performances results shows the advantages of the different proposed control strategies.

In this paper several optimal control strategies are proposed for the power management subsystem of a hybrid fuel cell/supercapacitor power generation system. The control strategies are based on different control configurations involving the power converters associated to the hybrid source. Given certain desired performances, Linear Matrix Inequalities methods are used to solve the controller design problem that is written as an optimization problem with inequalities constraints. The solution to the optimization problem yields a simple PID controller with H∞ desired performance. For the several control strategies proposed, robustness is a primary issue. Time simulations and robustness analysis shows the effectiveness of the proposed strategies when compared with the classic control strategies used for this type of hybrid power generation system.

In this article a robust control methodology is proposed for an hybrid power generation structure composed by a Fuel Cell and a Super-capacitor. The control strategy and the desired performances are written as inequality constraints so they can be solved using Linear Matrix Inequalities methods. Using this method a multivariable PI control with ℌ ∞ performance is computed, which is used to control the power converters associated with the Fuel Cell and the Super-capacitor respectively. The control performance in time and frequency domain is analyzed, with special interest in the control robust performance. The robust controller is implemented on a real-time test-bench with a Fuel Cell emulator. Results show the efficiency or the proposed methodology.

A novel robust control technique is proposed for the control of synchronous machines operating in electric power systems. The Sliding Mode Control technique belongs to the Variable Structure Systems Theory. The control law used is unique, non-linear and besides, it is discontinuous. Its discontinuous nature allows the controller to enhance the robustness of the system; which means that the control is insensitive to model uncertainties as well as to external disturbances. The sliding mode control approach is applied together with the Feedback Linearization technique, which is used here to obtain a decoupled-reduced form of the system in terms of the output controlled variables and the control input. Two different control schemes using sliding mode control are proposed and applied to synchronous machines. The response is obtained using a complete high order model for the machine, taking in consideration the model of the hydraulic turbine. The analysis of the obtained results show that in both cases the system response to small as well as to large disturbances, show a significant advantage of the proposed control techniques over conventional linear control systems for the Automatic Voltage Regulation (AVR) and the Power System Stabilizer (PSS). Moreover, the analysis of the system response to parameter variations demonstrates the robust characteristic of the non-linear discontinuous controller. The advantages obtained with sliding mode control appear directly in the operational behavior of the system as a substantial improvement in the stability characteristics of the electric power system.