This paper presents the mathematical formulation of the microgrid's energy management problem and its implementation in a centralized Energy Management System (EMS) for isolated microgrids Using the model predictive control technique, the optimal operation of the microgrid is determined using an extended horizon of evaluation and recourse, which allows a proper dispatch of the energy storage units The energy management problem is decomposed into Unit Commitment (UC) and Optimal Power Flow (OPF) problems in order to avoid a mixed-integer non-linear formulation The microgrid is modeled as a three-phase unbalanced system with presence of both dispatchable and non-dispatchable distributed generation The proposed EMS is tested in an isolated microgrid based on a CIGRE medium-voltage benchmark system Results justify the need for detailed three-phase models of the microgrid in order to properly account for voltage limits and procure reactive power support

A Centralized Energy Management System for Isolated Microgrids

Review of energy storage technologies for sustainable power networks

Grid-scale energy storage applications in renewable energy integration: A survey

The deployment of energy storage systems (ESSs) is a significant avenue for maximising the energy efficiency of a distribution network, and overall network performance can be enhanced by their optimal placement, sizing, and operation. An optimally sized and placed ESS can facilitate peak energy demand fulfilment, enhance the benefits from the integration of renewables and distributed energy sources, aid power quality management, and reduce distribution network expansion costs. This paper provides an overview of optimal ESS placement, sizing, and operation. It considers a range of grid scenarios, targeted performance objectives, applied strategies, ESS types, and advantages and limitations of the proposed systems and approaches. While batteries are widely used as ESSs in various applications, the detailed comparative analysis of ESS technical characteristics suggests that flywheel energy storage (FES) also warrants consideration in some distribution network scenarios. This research provides recommendations for related requirements or procedures, appropriate ESS selection, smart ESS charging and discharging, ESS sizing, placement and operation, and power quality issues. Furthermore, this study identifies future research opportunities in relation to challenges for optimal ESS placement planning, development and implementation issues, optimisation techniques, social impacts, and energy security.

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Overview of energy storage systems in distribution networks: Placement, sizing, operation, and power quality

The penetration of renewable distributed generation (DG) sources has been increased in active distribution networks due to their unique advantages. However, non-dispatchable DGs such as wind turbines raise the risk of distribution networks. Such a problem could be eliminated using the proper application of energy storage units. In this paper, optimal planning of batteries in the distribution grid is presented. The optimal planning determines the location, capacity and power rating of batteries while minimizing the cost objective function subject to technical constraints. The optimal long-term planning is based on the short-term optimal power flow considering the uncertainties. The point estimate method (PEM) is employed for probabilistic optimal power flow. The batteries are scheduled optimally for several purposes to maximize the benefits. A hybrid Tabu search/particle swarm optimization (TS/PSO) algorithm is used to solve the problem. The numerical studies on a 21-node distribution system show the advantages of the proposed methodology. The proposed approach can also be applied to the realistic sized networks when some sensitive nodes are considered as candidate locations for installing the storage units.

Optimal Storage Planning in Active Distribution Network Considering Uncertainty of Wind Power Distributed Generation

Due to environmental and fuel cost concerns more and more wind- and solar-based generation units are embedded in distribution networks (DNs). However, a part of such an embedded generation would be curtailed due to system constraints and variations of the energy penetration. This part of energy can be recovered by introducing energy storage systems (ESSs) and an optimal dispatch of both active and reactive powers. Therefore, we propose a combined problem formulation for active-reactive optimal power flow (A-R-OPF) in DNs with embedded wind generation and battery storage. The solution provides an optimal operation strategy which ensures the feasibility and enhances the profit significantly. Results of a 41-bus distribution network are presented. It can be demonstrated that more than 12% of energy losses and a large amount of reactive energy to be imported from the transmission network (TN) can be reduced using the proposed approach in comparison to the operation strategy where only active OPF is considered.

Active-Reactive Optimal Power Flow in Distribution Networks With Embedded Generation and Battery Storage

Active-reactive optimal power flow (A-R-OPF) in distribution networks (DNs) with embedded wind generation and battery storage systems (BSSs) was proposed recently. The solution was based on a fixed length in the charge and discharge cycle for daily operations of BSSs. This can lead to a low profit when the profiles of renewable generators, demand and prices vary from day to day. In this paper, we extend the A-R-OPF method by developing a flexible battery management system (FBMS). This is accomplished by optimizing the lengths (hours) of charge and discharge periods of BSSs for each day, leading to a complex mixed-integer nonlinear program (MINLP). An iterative two-stage framework is proposed to address this problem. In the upper stage, the integer variables (i.e., hours of charge and discharge periods) are optimized and delivered to the lower stage. In the lower stage the A-R-OPF problem is solved by a NLP solver and the resulting objective function value is brought to the upper stage for the next iteration. It can be shown through a case study that a flexible operation strategy will achieve a considerably higher profit than by a fixed operation strategy of BSSs.

Flexible Optimal Operation of Battery Storage Systems for Energy Supply Networks

Optimal operation of hybrid PV-battery system considering grid scheduled blackouts and battery lifetime

Real-time optimal power flow with reactive power dispatch of wind stations using a reconciliation algorithm

Developing a suitable framework for real-time optimal power flow (RT-OPF) is of utmost importance for ensuring both optimality and feasibility in the operation of energy distribution networks (DNs) under intermittent wind energy penetration. The most challenging issue thereby is that a large-scale complex optimization problem has to be solved in real-time. Online simultaneous optimization of the wind power curtailments of wind stations and the discrete reference values of the slack bus voltage which leads to a mixed-integer nonlinear programming (MINLP) problem, in addition to considering variable reverse power flow, make the optimization problem even much more complicated. To address these difficulties, a two-phase solution approach to RT-OPF is proposed in this paper. In the prediction phase, a number of MINLP OPF problems corresponding to the most probable scenarios of the wind energy penetration in the prediction horizon, by taking its forecasted value and stochastic distribution into account, are solved in parallel. The solution provides a lookup table for optional control strategies for the current prediction horizon which is further divided into a certain number of short time intervals. In the realization phase, one of the control strategies is selected from the lookup table based on the actual wind power and realized to the grid in the current time interval, which will proceed from one interval to the next, till the end of the current prediction horizon. Then, the prediction phase for the next prediction horizon will be activated. A 41-bus medium-voltage DN is taken as a case study to demonstrate the proposed RT-OPF approach.

Aouss Gabash

Papers

Active-Reactive Optimal Power Flow in Distribution Networks With Embedded Generation and Battery Storage

Flexible Optimal Operation of Battery Storage Systems for Energy Supply Networks

Optimal operation of hybrid PV-battery system considering grid scheduled blackouts and battery lifetime

Real-time optimal power flow with reactive power dispatch of wind stations using a reconciliation algorithm

A Framework for Real-Time Optimal Power Flow under Wind Energy Penetration