Aouss Gabash

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

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.

Flexible Optimal Operation of Battery Storage Systems for Energy Supply Networks

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.

Chance constrained optimal power flow with non-Gaussian distributed uncertain wind power generation

Chance constrained optimization (CCOPT) turns out to be a valuable approach to optimal power flow under uncertainty. The aim of this study is to develop a novel computation framework to solve CCOPT problems with non-Gaussian distributed uncertain variables and apply it to optimal power flow (OPF) under uncertain wind power penetration with Beta distribution. Results of OPF of a real distribution system with embedded wind power generation show the effectiveness of the proposed approach.

On the control of main substations between transmission and distribution systems

A new method called flexible active-reactive optimal power flow (A-R-OPF) has been recently developed to deal with power systems including entities such as distributed generation (DG) units and battery storage systems (BSSs). It was shown that bidirectional flows of active and reactive power/energy will be more and more exchanged in the case of connected power systems. This brings additional challenges in terms of optimal control and safe operations. The purpose of this paper is twofold. First, we introduce a new sensitivity analysis method incorporating the original flexible A-R-OPF method with an on-load-tap-changer (OLTC) transformer control system. Second, we study the impacts of reverse A-R-OPF and different disturbances on the feasibility of the whole system. Analyses are carried out by considering a real distribution system with wind DG units and BSSs. It is demonstrated that allowing and/or restricting reverse A-R-OPF can violate the feasibility of traditional control systems. This fact needs to be considered in connected power systems for optimal and reliable operations.

Reverse active-reactive optimal power flow in ADNs: Technical and economical aspects

Since 1880s unidirectional power flows in electrical distribution networks (DNs) have been known as the usual case. But after 1990s due to the installation of new entities such as distributed generation (DG) units and battery storage systems (BSSs) bidirectional power flows would be the future case. Recently, a combined problem formulation for active-reactive optimal power flow (A-R-OPF) has been developed to utilize the economical benefits of operating both low- and medium-voltage active DNs (ADNs). In this paper, some technical and economical aspects of allowing reverse A-R-OPF in ADNs are highlighted. This is achieved by considering a real medium voltage ADN with a high penetration of wind and battery stations. The results show that considering a price for reactive energy in ADNs will lead to a huge amount of reverse reactive energy. This new phenomenon needs to be considered in operating and planning future ADNs.

Real-time optimal power flow under wind energy penetration-Part I: Approach

Real-time optimal power flow (RT-OPF) under wind energy penetration is highly desired but extremely difficult to realize. This is basically due to the conflict between the fast changes in wind power generation and the slow response from the optimization computation. This paper (Part I) presents a prediction-updating approach to address this challenge. We consider essential scenarios around forecasted data of wind power that would probably happen during the computation time required for solving a large-scale complex optimal power flow problem. Parallel computing is used to solve the individual OPF problems corresponding to these scenarios. This provides for the forecasted time horizon probable reference operations in the form of a lookup-table. One of these operations will be selected based on the actual wind power and realized to the grid for the current time interval, thus leading to a RT-OPF framework. The proposed approach is implemented in Part II of this paper using a 41-bus medium-voltage distribution network as a case study.

Variable reverse power flow-Part II: Electricity market model and results

This is the second part (Part-II) of the companion paper (Part-I) on variable reverse power flow in active distribution networks with wind stations (WSs). In Part-I, the original model of active-reactive optimal power flow was further developed to explore the pure potential of the reactive power capability of WSs in the absence of battery storage systems. Here, we answer the questions raised in Part-I by investigating an electricity market model. The most interesting results from applying the extended model on a real medium-voltage network are presented. For instance, we demonstrate that the reactive power capability of WSs will be never utilized during days with zero wind power and varying limits on power factors (PFs). In contrast, more than 10% of active and 15% of reactive energy losses costs, respectively, and 100% of the cost of reactive energy to be imported from a transmission network can be saved if WSs are operated like capacitor banks with no limits on PFs.

A Study of Uncertain Wind Power in Active-Reactive Optimal Power Flow

Wind power fluctuates with time and it is reasonable to regard it as a random variable. Recently, an active-reactive optimal power flow (A-R-OPF) method in active distribution networks with wind stations has been developed to handle the problem of wind power curtailment (WPC). Since the mentioned method is deterministic, it may fail to handle uncertain wind power (UWP). Therefore, our study in this paper will firstly discuss the issue of UWP and secondly develop a new strategy which can improve the A-R-OPF by considering UWP. The new strategy can be distinguished from the original so that: 1) it considers shorter time intervals, i.e., 15 minutes instead of one hour and 2) it can handle both UWP and WPC simultaneously. The effectiveness of the new strategy is shown by using a real case medium-voltage distribution network. Keywords-active-reactive optimal power flow (A-R-OPF); medium-voltage; uncertain wind power (UWP); wind power curtailment (WPC).

Variable reverse power flow-Part I: A-R-OPF with reactive power of wind stations

It has been recently shown that using battery storage systems (BSSs) to provide reactive power provision in a medium-voltage active distribution network with embedded wind stations (WSs) can lead to a huge amount of reverse power to an upstream transmission network. However, unity power factors (PFs) of WSs were assumed in those studies to analyze the potential of BSSs. Therefore, it is aimed in this paper (Part-I) with a companion paper (Part-II) to further explore the pure potential (i.e., without BSSs) of WSs considering variable reverse power flow and varying limits on PFs. We introduce a new version of the active-reactive optimal power flow (A-R-OPF) model with two distinguished features. First, the revenues of wind power are maximized considering both active and reactive power capabilities of WSs. Second, the total costs of both active and reactive energy losses in the grid are minimized. In Part-II, the potential of the model is studied through analyzing an electricity market model.

Real-time optimal power flow under wind energy penetration-Part II: Implementation

In this paper (Part II) we implement the prediction-updating approach developed in Part I to address fast changes in wind power generation when solving a complex realtime optimal power flow (RT-OPF) problem. The approach considers essential scenarios around forecasted wind power values in a moving prediction horizon (120 seconds). The individual optimal power flow problems corresponding to these scenarios are solved in parallel using a multi-processor server. Then the operation strategy is updated in a short sampling time (every 20 seconds) considering real wind power values. The RT-OPF problem is formulated considering both technical and economic aspects simultaneously. The RT-OPF is implemented on a 41-bus medium-voltage distribution network with two wind stations. The results show the benefits of the proposed approach and highlight further challenges of RT-OPF.