Hanane Dagdougui

A Dynamic Decision Model for the Real-Time Control of Hybrid Renewable Energy Production Systems

The use of renewable energy sources can reduce the greenhouse gas emissions and the dependence on fossil fuels. The main problem of the installations based on renewable energy is that electricity generation cannot be fully forecasted and may not follow the trend of the actual energy demand. Hybrid systems (including different subsystems such as renewable energy plants, energy storage systems based on hydrogen or dam water reservoirs) can help in improving the economic and environmental sustainability of renewable energy plants. In addition, hybrid systems may be used to satisfy other user demands (such as water supply or hydrogen for automotive use). However, their use should be optimized in order to fulfill the user demand in terms of energy or other needs. In this paper, a model representing an integrated hybrid system based on a mix of renewable energy generation/conversion technologies (e.g., electrolyzer, hydroelectric plant, pumping stations, wind turbines, fuel cell) is presented. The model includes an optimization problem for the control of the different ways to store energy. The goal is to satisfy the hourly variable electric, hydrogen, and water demands. A specific application area in Morocco is considered and the results obtained are discussed in detail.

Decentralized Control of the Power Flows in a Network of Smart Microgrids Modeled as a Team of Cooperative Agents

The focus of this paper is on the decentralized control of smart microgrids (SMGs), where each microgrid is modeled as an inventory system locally producing energy by wind/solar sources. The objective is to satisfy the internal demand, and to exchange power with its local energy storage technology, the main grid, and other similar microgrids of the region. The problem faced, within this context, is the optimization (minimization) of the costs of energy storage and power exchanged among SMGs. A decentralized control strategy is proposed, which allows the storage level in each microgrid to operate around a reference value by cooperatively sharing power between microgrids. A distributed control approach is presented where different agents, one for each microgrid and one for each power line, agree on a saddle point of a local function. The approach is based on the classical work of Arrow on convex optimization, which has seen renewed interest with its recent application to team theory and in its connection with the decomposition of feedback systems. An example is illustrated to show the practical use and the limitations of the method.

Coordinated Model Predictive-Based Power Flows Control in a Cooperative Network of Smart Microgrids

In this paper, a model predictive control (MPC) for the optimal power exchanges in a smart network of power microgrids (MGs) is presented. The main purpose is to present an innovative control strategy for a cluster of interconnected MGs to maximize the global benefits. A MPC-based algorithm is used to determine the scheduling of power exchanges among MGs, and the charge/discharge of each local storage system. The MPC algorithm requires information on power prices, power generation, and load forecasts. The MPC algorithm is tested through case studies with and without prediction errors on loads and renewable power production. The operation of single MGs is simulated to show the advantage of the proposed cooperative framework relative to the control of a single MG. The results demonstrate that the cooperation among MGs has significant advantages and benefits with respect to each single MG operation.

Optimal Control of Power Flows and Energy Local Storages in a Network of Microgrids Modeled as a System of Systems

In this paper, a centralized control model for optimal management and operation of a smart network of microgrids (SNMs) is designed. The proposed control strategy considers grid interconnections for additional power exchanges. This paper is based on an original Linear Quadratic Gaussian (LQG) problem definition for the optimal control of power flows in a SNMs. The control strategy incorporates storage devices, various distributed energy resources, and loads. The objective function aims to minimize the power exchanges among microgrids (MGs), and to make each local energy storage system in a MG works around a proper optimal value. The proposed model is evaluated through a case study in the Savona district, Italy, consisting of four MGs that cooperate together under an SNMs connected to a main grid. The case study shows that the proposed approach can effectively cope with the aim to decrease the intermittencies effects of renewable energy sources, and to manage real-time burst in the residential local demands.

Optimal Control of a Network of Power Microgrids Using the Pontryagin's Minimum Principle

The optimal control of the power flows in a network of microgrids (MGs) is presented. The problem is solved using the mathematical formalization of the optimal control based on the Pontryagins minimum principle (PMP). The objective is to deliver an optimal control strategy for the minimization of the power flows among MGs, and to maintain the storage system operating around a given reference value. This study proposes an original formulation based on the PMP that may be viewed as a preliminary continuous time attempt to model and control the exchange of power in a network of MGs. Its main originality is the use and the exchange of information and forecast of energy production and consumption on the whole set of MGs, to improve the overall quality of the power management, and energy storage. A method based on the PMP is developed to solve the corresponding constrained optimal control problem in an almost exclusively analytical way and thus, to calculate the optimal control. To prove the viability of the proposed approach, an example has been solved for the case of four MGs collaborating in a network.

Optimal control of a regional power microgrid network driven by wind and solar energy

In this paper, a model to support optimal decisions in a network of microgrids is formalized as an original discrete and centralized problem defined here as cooperative network of smart power grids problem. The control variables are the instantaneous flows of power in the network of microgrids, which can be obtained from the solution of a linear quadratic Gaussian (LQG) problem on a fixed time horizon. The state is represented by the energy stored in each microgrid. The goal is to minimize the variations of the energy stored in each storage device from a reference value, as well as to minimize the exchange of power between the microgrids. An application of the model is proposed taking into account wind and solar data in three sites in Liguria region (Castellari, Capo Vado and Savona). It is assumed that each microgrid is composed by a renewable hybrid energy system, a cluster of 100 households and a storage device.

Hazard and risk evaluation in hydrogen pipelines

Purpose – The purpose of this paper is the definition and the implementation of a simplified mathematical model to estimate the hazard and the risk related to the use of high‐pressurized hydrogen pipeline.Design/methodology/approach – This study aims to investigate the effects of different hydrogen operations conditions and to tackle with different release or failure scenarios. Based on the combination of empirical relations and analytical models, this paper sets the basis for suitable models for consequence analysis in terms of estimating fire length and of predicting its thermal radiation. The results are compared either with experimental data available in the literature, thus by setting the same operations and failure conditions, or with other conventional gaseous fuel currently used.Findings – The findings show that the release rate increasingly varies according to the supply pressure. Regarding the effect of the hole diameter, it hugely affects the amount of hydrogen escaping from the leak, up to a v...

Optimal power exchanges in an interconnected power microgrids based on model predictive control

This paper presents a model predictive control (MPC) approach for the optimization of the energy produced by a microgrids (MGs) in a network. The objective is to present a control approach for interconnected cooperating MGs, where the main objective is to minimize the power purchased by each MG. Minimizing the energy purchased from other MGs and from the main grid is considered among main objectives to be achieved. In order to reach these objectives, a global central controller is responsible to find the best patterns for state of energy storage system and the power exchanges among MGs, where each MG can be modeled as an inventory system, locally producing energy by wind turbines. The MPC strategy is tested using an interconnected network of three MGs. Results provide a good reference on the economic benefits which can be obtained using MPC.

Distributed Robust Control of the Power Flows in a Team of Cooperating Microgrids

This brief paper presents a mathematical formulation for a team of cooperating microgrids (TCM) proposing a robust distributed control strategy based on partially nested information. This brief paper faces one of the main problems in a TCM, which is to react to the unpredictable production/demand processes, optimizing power flows, and energy storage in each microgrid (MG). This brief paper focuses on a high-level control of the TCM through properly coordinating power that is exchanged among MGs. The robust distributed control strategy operates in order to minimize the maximum divergence both from an agreed power exchange among MGs and from a technical reference value of the energy storage system of each MG. The proposed approach is based on some quite recent results on robust control for cooperative teams. The robust control approach is tested through a case study.

Modeling and optimal operation of a university campus microgrid

In this paper, we propose a system design for a university campus microgrid (UCM) to facilitate research needs in relation to the operation and control of microgrid. This paper proposes the design, modeling and optimal operation of a UCM. The optimal operation aims to minimize the operation costs of photovoltaic system and costs of exchange with the local electrical network. The UCM is aggregating different distributed energy resources with parts of local loads that are co-located in the campus setting. The mathematical modeling of different components of the UCM is proposed. However, the objective of the UCM is to achieve three objectives: 1) to satisfy part of the residential campus loads, 2) to charge employees electric vehicles and 3) to help the campus avoiding peak load in period of high demands.