Switched model predictive control for energy dispatching of a photovoltaic-diesel-battery hybrid power system

A new adaptive switched model predictive control (MPC) strategy is designed in this paper for energy dispatching of a photovoltaic-diesel-battery (PDB) hybrid power system, where the battery is unpermitted to charge and discharge simultaneously. The distinguishing feature of the proposed switchedMPC is that, new switched constraints are constructed to describe the different modes (charging and discharging) of the battery, such that the burden of using a switched multiple-input-multiple-output (MIMO) state-space model could be circumvented. Parameters of the battery are unknown constants, and are estimated online with an adaptive updating law. In the switched MPC algorithm, predictive horizon and control horizon vary according to the predefined switching schedule. Based on optimization with the switched constraints, receding horizon control is utilized to obtain the dispatching strategy for the hybrid power system. Performances of the closed-loop system with the proposed switched MPC are verified by simulation results.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=87hb201

Optimal design of isolated mini-grids with deterministic methods: matching predictive operating strategies with low computational requirements

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

Energy Production Analysis and Optimization of Mini-Grid in Remote Areas: The Case Study of Habaswein, Kenya

Rural electrification in remote areas of developing countries has several challenges which hinder energy access to the population. For instance, the extension of the national grid to provide electricity in these areas is largely not viable. The Kenyan Government has put a target to achieve universal energy access by the year 2020. To realize this objective, the focus of the program is being shifted to establishing off-grid power stations in rural areas. Among rural areas to be electrified is Habaswein, which is a settlement in Kenya’s northeastern region without connection to the national power grid, and where Kenya Power installed a stand-alone hybrid mini-grid. Based on field observations, power generation data analysis, evaluation of the potential energy resources and simulations, this research intends to evaluate the performance of the Habaswein mini-grid and optimize the existing hybrid generation system to enhance its reliability and reduce the operation costs. The result will be a suggestion of how Kenyan rural areas could be sustainably electrified by using renewable energy based off-grid power stations. It will contribute to bridge the current research gap in this area, and it will be a vital tool to researchers, implementers and the policy makers in energy sector

Optimal energy dispatch in a smart micro-grid system using economic model predictive control

The problem of energy dispatch in heterogeneous complex systems such as smart grids cannot be efficiently addressed using classical control or ad-hoc methods. This paper discusses the application of Economic Model Predictive Control (EMPC) to the management of a smart micro-grid system connected to an electrical power grid. The considered system is composed of several subsystems, namely some photovoltaic (PV) panels, a wind generator, a hydroelectric generator, a diesel generator, and some storage devices (batteries). The batteries are charged with the energy from the PV panels, wind and hydroelectric generators, and they are discharged whenever the generators produce less energy than needed. The subsystems are interconnected via a DC Bus, from which load demands are satisfied. Modeling smart grids components is based on the generalized flow-based networked systems paradigm, and assuming energy generators to be stable, load demands and energy prices are known. This study shows that EMPC is economically superior to a two-layer hierarchical MPC.Peer ReviewedPostprint (author's final draft

Techno-economic and environmental optimization of a household photovoltaic-battery hybrid power system within demand side management

This paper presents a power management system of a household photovoltaic-battery hybrid power system within demand side management under time of use electricity tariff. This system is easy to implement by employing cheap electrical switches, off-the-shelf chargers and inverters. Control system models combining both power dispatching level and home appliance scheduling level are proposed to minimize the residents’ energy cost and energy consumption from the grid with the practical constraints strictly satisfied. In addition, the resident comfort inconvenience level is considered in the control system models. The trade-off among operating cost, energy consumption and inconvenience is considered and a multi-objective optimization problem is formulated. The optimal control strategies are derived by solving a mixed-integer nonlinear programming problem. Simulation results show that the energy cost and energy consumption from the grid can be largely reduced with the proposed strategies. These results are important for customers to dispel their major uncertainty in determining whether to newly install or update to such photovoltaic-battery hybrid power systems.http://www.elsevier.com/locate/renene2018-08-31hb2017Electrical, Electronic and Computer Engineerin

Demand side management of photovoltaic-battery hybrid system

In the electricity market, customers have many choices to reduce electricity cost if they can economically schedule their power consumption. Renewable hybrid system, which can explore solar or wind sources at low cost, is a popular choice for this purpose nowadays. In this paper optimal energy management for a grid-connected photovoltaic-battery hybrid system is proposed to sufficiently explore solar energy and to benefit customers at demand side. The management of power flow aims to minimize electricity cost subject to a number of constraints, such as power balance, solar output and battery capacity. With respect to demand side management, an optimal control method (open loop) is developed to schedule the power flow of hybrid system over 24 h, and model predictive control is used as a closed-loop method to dispatch the power flow in real-time when uncertain disturbances occur. In these two kinds of applications, optimal energy management solutions can be obtained with great cost savings and robust control performance.http://www.elsevier.com/locate/apenergyhb201

Comparison of Two Energy Management System Strategies for Real-Time Operation of Isolated Hybrid Microgrids

The propagation of hybrid power systems (solar–diesel–battery) has led to the development of new energy management system (EMS) strategies for the effective management of all power generation technologies related to hybrid microgrids. This paper proposes two novel EMS strategies for isolated hybrid microgrids, highlighting their strengths and weaknesses using simulations. The proposed strategies are different from the EMS strategies reported thus far in the literature because the former enable the real-time operation of the hybrid microgrid, which always guarantees the correct operation of a microgrid. The priority EMS strategy works by assigning a priority order, while the optimal EMS strategy is based on an optimization criterion, which is set as the minimum marginal cost in this case. The results have been obtained using MATLAB/Simulink to verify and compare the effectiveness of the proposed strategies, through a dynamic microgrid model to simulate the conditions of a real-time operation. The differences in the EMS strategies as well as their individual strengths and weaknesses, are presented and discussed. The results show that the proposed EMS strategies can manage the system operation under different scenarios and help power system operator obtain the optimal operation schemes of the microgrid.This work was supported by the Autonomous Community of Madrid under the PROMINT-CM project (S2018/EMT-4366)

Smart power management of a hybrid photovoltaic/wind stand-alone system coupling battery storage and hydraulic network

An off-grid energy system based on renewable photovoltaics (PV) and wind turbines (WT) generators is coupled via converters to electric and hydraulic networks. The electric network is composed of consumers and of a battery bank for electrical storage,while the hydraulic part is made of motor-pumps and hydraulic tanks for water production and desalination. Both battery and water tanks are used to optimize the power management of both electric and hydraulic subsystems by ensuring electric load demand and by reducing at the same time water deficit following the operation of the renewable intermittent source. Thus, both electric and hydraulic subsystems are strongly coupled in terms of energy making necessary to manage the power flows provided by renewable sources to optimize the overall system performance. In this paper, two kinds of management strategies are then compared in the way they share the hybrid power sources between the storage devices (battery and tanks) and the electrical/hydraulic loads. The first approach deals with an “uncoupled power management” in which the operation of electrical and hydraulic loads does not depend on the state of the intermittent renewable sources: in particular, hydraulic pumps are operated only taking account of water demand and tank filling but without considering power sources. On the contrary, given the available power produced by the sources, the second class of strategy (i.e. the “coupled management strategy”) consists of a “smart” power sharing between the electrical and hydraulic networks with regard to the battery SOC and the tank L1 and L2. A dynamic simulator of the hybrid energy system has been developed and tested using a MATLAB environment. The system performance is shown under the two investigated approaches (uncoupled vs coupled). Several tests are carried out using real meteorological data of a remote area and a practical load demand profile. The simulation results show that the “coupled strategy” clearly outperforms the classical “uncoupled” management strategies

A Review of Active Management for Distribution Networks: Current Status and Future Development Trends

Driven by smart distribution technologies, by the widespread use of distributed generation sources, and by the injection of new loads, such as electric vehicles, distribution networks are evolving from passive to active. The integration of distributed generation, including renewable distributed generation changes the power flow of a distribution network from unidirectional to bi-directional. The adoption of electric vehicles makes the management of distribution networks even more challenging. As such, an active network management has to be fulfilled by taking advantage of the emerging techniques of control, monitoring, protection, and communication to assist distribution network operators in an optimal manner. This article presents a short review of recent advancements and identifies emerging technologies and future development trends to support active management of distribution networks