Active-reactive Optimal Power Flow Research Articles

Review of Battery Storage and Power Electronic Systems in Flexible A-R-OPF Frameworks

This paper provides an overview of power electronics and its applications in various fields, emphasizing power conditioning and minimizing losses for high energy efficiency. It discusses the distinction between unidirectional and bidirectional converters and their applications in power systems. The significance of unidirectional and bidirectional power flow in different scenarios is explored. The importance of battery storage systems (BSSs) for grid stabilization, frequency regulation, and renewable energy integration is highlighted. The paper focuses on flexible active-reactive optimal power flow (A-R-OPF) frameworks in battery storage and power electronic systems, reviewing existing research, identifying gaps, and offering new perspectives. It addresses the challenges and potential of grid-scale energy storage for reliable and cost-effective power systems with high renewable energy penetration. The need for energy curtailment, demand response, and smart grid implementation is discussed. The paper emphasizes comprehensive coordination, new power lines, European collaboration, and smart grid implementation to meet the dynamic needs of Europe’s power grids.

Real-Time Active-Reactive Optimal Power Flow with Flexible Operation of Battery Storage Systems

In this paper, a multi-phase multi-time-scale real-time dynamic active-reactive optimal power flow (RT-DAR-OPF) framework is developed to optimally deal with spontaneous changes in wind power in distribution networks (DNs) with battery storage systems (BSSs). The most challenging issue hereby is that a large-scale ‘dynamic’ (i.e., with differential/difference equations rather than only algebraic equations) mixed-integer nonlinear programming (MINLP) problem has to be solved in real time. Moreover, considering the active-reactive power capabilities of BSSs with flexible operation strategies, as well as minimizing the expended life costs of BSSs further increases the complexity of the problem. To solve this problem, in the first phase, we implement simultaneous optimization of a huge number of mixed-integer decision variables to compute optimal operations of BSSs on a day-to-day basis. In the second phase, based on the forecasted wind power values for short prediction horizons, wind power scenarios are generated to describe uncertain wind power with non-Gaussian distribution. Then, MINLP AR-OPF problems corresponding to the scenarios are solved and reconciled in advance of each prediction horizon. In the third phase, based on the measured actual values of wind power, one of the solutions is selected, modified, and realized to the network for very short intervals. The applicability of the proposed RT-DAR-OPF is demonstrated using a medium-voltage DN.

A VSC-Based BESS Model for Multi-Objective OPF Using Mixed Integer SOCP

This paper presents a new model of voltage source converter (VSC) based battery energy storage systems (BESSs) that interface with power grids. A VSC-based BESS is made up of a series connection of a VSC, its connecting transformer, and a BESS. The VSC allows a BESS to generate both active and reactive powers in all four quadrants. The proposed model captures the coupling between active power, reactive power, and the voltage of a BESS. In addition, the proposed model explicitly describes the relationship between the control configuration of pulsewidth modulation (PWM) VSC and the power output of the BESS. Therefore, the proposed model possesses unparalleled control capabilities in the operational parameters of both the ac and dc sides of the converter. By incorporating such a model into the active-reactive optimal power flow (A-R-OPF) formulation, we can not only optimize the active and reactive power output of the BESS in power systems, but also understand how the optimal powers are generated by setting the operational parameters of both the BESS and PWM-VSC. To solve the A-R-OPF problem with the proposed model, we propose a sequence of strong relaxations to transform the problem into a mixed-integer second-order cone programming problem. Such a formulation is amendable for efficient solutions using off-the-shelf solvers. Case studies on the IEEE benchmark systems show that more than 17.73% of power losses in transmission lines and more than 0.961% of interface losses can be reduced by using the proposed model in comparison to the traditional BESS model.

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

Abstract Abstract—It is extremely difficult to realize real-time active-reactive optimal power flow (RT-AR-OPF) in distribution networks (DNs) with wind stations (WSs) due to the conflict between the fast changes in wind power and the slow response from the optimization computation. To address this problem, a new lookup-table-based RT-AR-OPF framework is developed in this paper. According to the forecasted wind power for a prediction horizon, scenarios are generated based on its stochastic distribution. The corresponding mixed-integer nonlinear programming (MINLP) problems are solved online which simultaneously optimize the active and reactive power dispatch of WSs, active-reactive reverse power flow, and discrete slack bus voltage, resulting in a lookup table. Based on the actual wind power available in a sampling time, one of the solutions will be selected and realized to the DN. A new reconciliation algorithm is proposed to ensure both the feasibility and optimality of the realized operation strategy. The applicability of the proposed framework is shown using a medium-voltage DN.

On Variable Reverse Power Flow-Part II: An Electricity Market Model Considering Wind Station Size and Location

This is the second part of a companion paper on variable reverse power flow (VRPF) in active distribution networks (ADNs) with wind stations (WSs). Here, we propose an electricity market model considering agreements between the operator of a medium-voltage active distribution network (MV-ADN) and the operator of a high-voltage transmission network (HV-TN) under different scenarios. The proposed model takes, simultaneously, active and reactive energy prices into consideration. The results from applying this model on a real MV-ADN reveal many interesting facts. 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 the costs of active energy losses, 15% of the costs of reactive energy losses, and 100% of the costs of reactive energy imported from the HV-TN, respectively, can be reduced if WSs are operated as capacitor banks with no limits on PFs. It is also found that allocating WSs near possible exporting points at the HV-TN can significantly reduce wind power curtailments if the operator of the HV-TN accepts unlimited amount of reverse energy from the MV-ADN. Furthermore, the relationships between the size of WSs, VRPF and demand level are also uncovered based on active-reactive optimal power flow (A-R-OPF).

On Variable Reverse Power Flow-Part I: Active-Reactive Optimal Power Flow with Reactive Power of Wind Stations

It has recently been shown that using battery storage systems (BSSs) to provide reactive power provision in a medium-voltage (MV) active distribution network (ADN) with embedded wind stations (WSs) can lead to a huge amount of reverse power to an upstream transmission network (TN). However, unity power factors (PFs) of WSs were assumed in those studies to analyze the potential of BSSs. Therefore, in this paper (Part-I), we aim to further explore the pure reactive power potential of WSs (i.e., without BSSs) by investigating the issue of variable reverse power flow under different limits on PFs in an electricity market model. The main contributions of this work are summarized as follows: (1) Introducing the reactive power capability of WSs in the optimization model of the active-reactive optimal power flow (A-R-OPF) and highlighting the benefits/impacts under different limits on PFs. (2) Investigating the impacts of different agreements for variable reverse power flow on the operation of an ADN under different demand scenarios. (3) Derivation of the function of reactive energy losses in the grid with an equivalent-π circuit and comparing its value with active energy losses. (4) Balancing the energy curtailment of wind generation, active-reactive energy losses in the grid and active-reactive energy import-export by a meter-based method. In Part-II, the potential of the developed model is studied through analyzing an electricity market model and a 41-bus network with different locations of WSs.

An unequivocal normalization-based paradigm to solve dynamic economic and emission active-reactive OPF (optimal power flow)

This paper presents a straightforward compromising methodology of dynamic economic and emission AROPF (active-reactive optimal power flow). AROPF considering environmental effects is a highly nonlinear problem, and the dynamic consideration of such problems makes it even more complicated and extra-high nonlinear; find an appropriate compromising solution for such problems is considered as a complicated task. In one hand the traditional compromising methodologies cannot find an acceptable compromise point for large-scale systems, and on the other hand metaheuristic methods are time consuming. In this paper an UNBP (unequivocal normalization-based paradigm) is proposed, while instead of maximum output-based pollution control cost, an adaptive pollution control cost is used to consider the system topology in dynamic scheduling and under various system conditions such as normal, outage, and critical conditions. By using a normalization process and adaptive pollution control cost, a uniform compromising procedure is obtained. Three case studies such as 14-bus, 30-bus, and 118-bus IEEE test systems are conducted and results are compared to those reported in literature. Results confirm the potential, effectiveness, and superiority of the proposed UNBP compared to traditional and heuristic-based multi-objective optimization techniques.

Flexible Optimal Operation of Battery Storage Systems for Energy Supply Networks

<?Pub Dtl=""?> 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.

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.