Scheduled Power Flows Research Articles

Joint Covering Congestion Rents in Multi-area Power Systems Considering Loop Flow Effects

We consider the problem of how multiple areas should jointly cover congestion rents of internal and tie-lines in an interconnected power system. A key issue of our concern is the loop flow problem, which represents discrepancies between scheduled and actual power flow distributions because electric power does not always flow along the most direct paths of transactions. We employ generalized coordinated transaction scheduling (GCTS) for interchange scheduling, which can eliminate dispatch errors caused by loop flow effects and asymptotically converge to the joint economic dispatch (JED) under ideal assumptions. Subsequently, distributed algorithms are proposed for each area to recover multipliers of the global GCTS model, as well as quantifying and pricing its contribution to line congestions. Thereby, all areas and interface bids can jointly cover congestion rents of internal and tie-lines with their merchandise surpluses and profits. Simulations demonstrate the effectiveness of the proposed approach of LMP recovery and joint covering congestion rents.

Distributed Automatic Load Frequency Control With Optimality in Power Systems

With the increasing penetration of renewable energy resources, power systems confront new challenges in maintaining power balance and the nominal frequency. This article studies load-side frequency control to handle these challenges. In particular, a fully distributed automatic load control (ALC) algorithm, which only needs local measurement and local communication, is proposed. We prove that the load control algorithm globally converges to an optimal operating point that minimizes the total disutility of users, restores the nominal frequency and the scheduled tie-line power flows, and respects the load capacity limits and the thermal constraints of transmission lines. Furthermore, the global exponential convergence of the reduced ALC algorithm without considering the capacity limits is proved and leveraged to study the dynamical tracking performance and robustness of the algorithm. Finally, the effectiveness, optimality, and robustness of the proposed ALC algorithm are demonstrated via numerical simulations.

Flexibility Services Management Under Uncertainties for Power Distribution Systems: Stochastic Scheduling and Predictive Real-Time Dispatch

Over the last years, the role of the distribution system operator (DSO) has largely expanded. This is necessitated by the increased penetration of intermittent energy resources at the distribution level, as well as the new, more complex interactions with the transmission system operator (TSO). As such, to properly manage its system and to have an effective joint cooperation with the TSO, the DSO is required to procure and carefully manage flexibility services from distributed energy resources (DER). This paper introduces a thorough framework on optimal operational planning (day-ahead scheduling) and operational management (real-time dispatch) of active distribution systems under uncertainties, to avoid line congestions and voltage limit violations, and efficiently balance the distribution system. A two-stage stochastic programming model based on weighted scenarios is proposed to optimize the multi-period optimal power flow day-ahead scheduling, i.e., scheduled power flows at the TSO-DSO interface and reserved DER flexibility services. Subsequently, the operational management, realized with a predictive real-time dispatch model based on a constantly updated rolling horizon, aims to efficiently activate the available flexibility services to minimize deviations from the committed schedule. Different sources of flexibility are considered, with their respective response times also taken into account at real-time dispatch. The proposed framework is applied on two distribution systems and investigates the DSO’s level of risk exposure while minimizing its total cost (reservation and activation expenses). The results indicate that a less conservative approach at planning stage, despite the potential risk exposure, can lead to significant reduction in total expenses.

The EV-olution of the power system: A spatio-temporal optimisation model to investigate the impact of electric vehicle deployment

Power system models have become an essential part of strategic planning and decision-making in the energy transition. While techniques are becoming increasingly sophisticated and manifold, the ability to incorporate high resolution in space and time with long-term planning is limited. We introduce ESONE, the Spatially granular Electricity Systems Optimisation model. ESONE is a mixed-integer linear program, determining investment in power system generation and transmission infrastructure while simultaneously optimising operational schedule and optimal power flow on an hourly basis. Unique data clustering combined with model decomposition and an iterative solution procedure enable computational tractability. We showcase the capabilities of the ESONE model by applying it to the power system of Great Britain under CO2 emissions reduction targets. We investigate the effects of a spatially distributed large-scale roll-out of electric vehicles (EVs). We find EV demand profiles correlate well with offshore and onshore wind power production, reducing curtailment and boosting generation. Time-of-use-tariffs for EV charging can further reduce power supply and transmission infrastructure requirements. In general, Great Britain’s electricity system absorbs additional demand from ambitious deployment of EVs without substantial changes to system design.

Design of the Pacific DC Intertie Wide Area Damping Controller

This paper describes the design and implementation of a proof-of-concept Pacific dc Intertie (PDCI) wide area damping controller and includes system test results on the North American Western Interconnection (WI). To damp inter-area oscillations, the controller modulates the power transfer of the PDCI, a ±500 kV dc transmission line in the WI. The control system utilizes real-time phasor measurement unit (PMU) feedback to construct a commanded power signal which is added to the scheduled power flow for the PDCI. After years of design, simulations, and development, this controller has been implemented in hardware and successfully tested in both open and closed-loop operation. The most important design specifications were safe, reliable performance, no degradation of any system modes in any circumstances, and improve damping to the controllable modes in the WI. The main finding is that the controller adds significant damping to the modes of the WI and does not adversely affect the system response in any of the test cases. The primary contribution of this paper, to the state of the art research, is the design methods and test results of the first North American real-time control system that uses wide area PMU feedback.

A Schedule Power Flow Generating Method Based on State Estimation

Generating schedule power flow rapidly and accurately is an important step in security checking. In consideration of poor convergency property and calculating speed of conventional methods based on power flow calculations, this paper proposes a schedule power flow generating method based on state estimation to calculate schedule power flow. Pattern recognition is used to select similar section by comparing planned data and historical power flow to take the power flow of similar section as redundant measurements of state estimation. In state estimation calculation with transmission power constraints based on maximum correntropy criterion, measurements corresponding to generation schedule, load forecasting and maintenance schedule are assigned large weights. The schedule power flow calculated by the method could satisfy planned data conditions and transmission power constraints. Cases of IEEE 9-bus system and a practical power grid vertify the effectiveness and calculating accuracy of the method.

Distributed Optimal Tie-Line Power Flow Control for Multiple Interconnected AC Microgrids

In a multi-microgrid system (MMG), the microgrids (MGs) are normally managed by independent operators. Distributed energy trading/scheduling schemes via interactions of these MG operators have been extensively investigated. How to coordinate these MGs to implement the acquired optimal schedule in the real time under constant load fluctuation while guaranteeing operational stability is seldom reported. Due to the intrinsic advantages of scalability, robustness, and fast response in comparison to the centralized scheme, a multi-agent based distributed optimal tie-line power flow control strategy is proposed to achieve this objective, which is facilitated by a regional communication network overlapping each MG and distributed sensors monitoring the tie-line power flows. When the MMG is operated in the grid-connected mode, the proposed scheme can maintain the scheduled tie-line power flows among the MGs in the presence of any disturbance by adjusting the real-time power outputs of the distributed energy resources proportionally. When the MMG is islanded, frequency recovery can be further achieved via a local frequency feedback mechanism. Convergence of the proposed approach is analytically proved. Simulation results in a four-MG system modified from the IEEE 34-bus test feeder system validate the effectiveness and efficiency of the proposed approach in both grid-connected and islanded modes.

Active Distribution System Management: A Dual-Horizon Scheduling Framework for DSO/TSO Interface Under Uncertainty

Active distribution system management (ADSM) aims at optimally operating distribution network assets with a high penetration of distributed energy resources (DERs) while taking into account operational uncertainties, market constraints, and scheduled power flows at the interface with the transmission system. A novel framework for ADSM, which incorporates a dual-horizon rolling scheduling model based on dynamic ac optimal power flow, is proposed in this paper. In the first stage (planning), energy import/export is committed for given times ahead at the grid supply point considering local variable generation and load forecasts. At the second stage (operation) deviations from the schedules are minimised by controlling various assets and DER, including electrical energy storage (EES). We demonstrate how crucial it is to properly consider uncertainties (for instance, associated with forecasts) over different time scales. Case study results on a real U.K. distribution network show that the proposed ADSM approach can provide credible operational strategies to maximise renewable penetration, minimize deviations from time-ahead schedules, and estimate the required level of local reserves from dispatchable generation and EES while realistically accounting for uncertainty. The framework and model formulation proposed can thus be seen as a key tool to facilitate the transition from distribution network operators to distribution system operators and their interaction with transmission system operators.

Optimal scheduled power flow for distributed photovoltaic/wind/diesel generators with battery storage system

In this study, two control strategies involving ‘continuous’ and ‘ON/OFF’ operation of the diesel generator in the solar photovoltaic (PV)-wind-diesel-battery hybrid systems are modelled. The main purpose of these developed models is to minimise the hybrid system's operation cost while finding the optimal power flow considering the intermittent solar and wind resources, the battery state of charge and the fluctuating load demand . The non-linearity of the load demand, the non-linearity of the diesel generator fuel consumption curve as well as the battery operation limits have been considered in the development of the models. The simulations have been performed using ‘fmincon’ for the continuous operation and ‘intlinprog’ for the ON/OFF operation strategy implemented in Matlab. These models have been applied to two test examples; the simulation results are analysed and compared with the case where the diesel generator is used alone to supply the given load demand. The results show that using the developed PV-diesel-battery optimal operation control models, significant fuel saving can be achieved compared with the case where the diesel is used alone to supply the same load requirements.

Congestion management of power system with interline power flow controller using disparity line utilization factor and multi-objective differential evolution

The restructuring of the electric power market has led to complex power transmission congestion problems. Additionally, scheduled power flows in the transmission line, as well as spontaneous power exchanges have also risen sharply in recent years. The proper placement of IPFC can improve the transmission line congestion problem to a great extent. This paper proposes a disparity line utilization factor (DLUF) for the optimal placement of IPFC to control the congestion in transmission lines. DLUF determines the difference between the percentages of Mega Volt Ampere utilization of each line connected to the same bus. The IPFC is placed in the lines with maximum DLUF. A multiobjective function consisting of reduction of active power loss, minimization of total voltage deviations, minimization of security margin and minimization of installed IPFC capacity is considered for the optimal tuning of IPFC using differential evolution algorithm. The proposed method is implemented for IEEE-30 bus test system under different loading conditions and the results are presented and analyzed to establish the effectiveness on the reduction of congestion.

The Selection of Online Power Flow Calculation’s Known Quantities

The difference between schedule power flow and online power flow is that the former has no corresponding physical power flow, while the latter is the reappearance of existing physical power flow. Owing to the different premise, the selection of power flow calculation’s known quantities can be different. A schedule power flow schedules physical power flow for power system, so the selection of known quantities has strict requirements, such as active power and reactive power regulation capability. Since the physical power flow exists, the selection of online power flow calculation’s known quantities can be more flexible. For example, we can choose load bus as slack bus or replace PQ bus with PV bus. The example demonstrated that we could locate the stealing electricity buses by choosing load bus as slack bus. Considering that voltage amplitude measurement accuracy is higher than reactive power measurement accuracy, we can replace PQ bus with PV bus and make the power flow calculation results more consistent with the physical power flow. Finally, the examples show that online power flow calculation’s known quantities can be selected flexibly according to the actual situation rather than strictly following the classical power flow calculation requirements.

An Estimation Technique to Assign Contribution Factors for Loop Flows in an Interconnected Power System

This article describes the significance of loop flows in an interconnected electric power system. Loop flows (unscheduled flows) are the difference between scheduled and actual power flows. A brief discussion of the consequences of loop flow is given. The article illustrates a new method of identifying the contributions of the loop flows occurring in a system to the participating utilities by means of a contribution factor matrix. A method to estimate the loop flows in the system using a type of Lp estimation is described, and the estimation technique is further employed in designing the contribution factor matrix. The potential application is in transmission pricing.