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It is possible to launch undetectable load-redistribution (LR) attacks against power systems even in systems with protection schemes. Therefore, it is imperative to detect LR attacks in power systems and establish corrective actions to provide secure dispatch points. This paper develops a systematic real-time LR threat analysis (RTLRTA) tool to flag LR attacks and identify all affected transmission assets. Since attackers might introduce some forms of random strategies to create LR attacks, we introduce different optimization models to generate random LR attacks to determine accurate thresholds for our detection index and test the tool’s functionality. Additionally, based on an estimation for the actual loads in the post-attack stage, we design a set of physical line flow security constraints (PLFSCs) that can be added to the existing security-constrained economic dispatch (SCED) models. This leads to appropriate responses to the identified LR attacks and provides secure dispatch points. We generate multiple scenarios of LR attacks and random errors for different target lines in the 2383-bus Polish test system to validate our proposed methods’ accuracy and functionality in detecting LR attacks and responding to them. [ABSTRACT FROM AUTHOR]

In this paper, we continue to analyze optimal dispatch of generation and transmission topology to meet load as a mixed integer program (MIP) with binary variables representing the state of the transmission element (line or transformer). Previous research showed a 25% savings by dispatching the IEEE 118-bus test case. This paper is an extension of that work. It presents how changing the topology affects nodal prices, load payment, generation revenues, cost, and rents, congestion rents, and flowgate prices. Results indicate that changing the topology to cut costs typically results in lower load payments and higher generation rents for this network. Computational issues are also discussed. Index Terms--Mixed integer programming, power generation dispatch, power system economics, power transmission control, power transmission economics.

The flexibility in transmission networks is not fully utilized in existing energy management systems (EMSs). Corrective transmission switching (CTS) is proposed in this two-part paper to enable EMS to take advantage of the flexibility in transmission systems in a practical way. This paper proposes the following two EMS procedures: first, Procedure-A connects real-time security-constrained economic dispatch (RT SCED) with real-time contingency analysis (RTCA), which is consistent with industrial practice; and second, Procedure-B, an enhanced version of Procedure-A, includes CTS in EMS with the proposed concept of branch pseudo limit used in RT SCED. Part-I of this paper presents the methodology, whereas Part-II includes detailed results analysis. It is demonstrated that Procedure-A can effectively eliminate the base case overloads and the potential post-contingency overloads identified by RTCA, and Procedure-B can achieve significant congestion cost reduction with consideration of CTS in RT SCED. Numerical simulations also illustrate that integrating CTS into RT SCED would improve social welfare. [ABSTRACT FROM AUTHOR]

This paper presents a novel procedure for energy management system (EMS) that can utilize the flexibility in transmission networks in a practical way. With the proposed enhanced EMS procedure, the reliability benefits that are provided by corrective transmission switching (CTS) in real-time contingency analysis can be translated into significant cost savings in real-time security-constrained economic dispatch. Simulation results show that the congestion cost with consideration of CTS is largely reduced as CTS can relieve potential post-contingency network violations. The effects of integrating CTS in existing EMS procedure on markets are also analyzed. In conclusion, this two-part paper shows that CTS can achieve substantial reliability benefits, as well as significant cost savings. [ABSTRACT FROM AUTHOR]

This paper modifies the traditional security-constrained unit commitment (UC) model to include a reserve policy that aims to preemptively anticipate post-contingency congestion patterns and account for uncertainty, simultaneously. The policy uses post-contingency transmission constraints to predict the influence of recourse actions under critical generator contingencies and to cover a range of uncertain scenarios by defining reserve response factors, which are determined offline using a data-mining algorithm. The main motive is to address both the locational and the deliverability issues that are usually associated with reserve. The performance of the proposed data-driven reserve response set policy is compared against two sets of deterministic reserve policies and an extensive form stochastic UC model. All simulations are conducted on a modified 2383-bus Polish test system. Test results illustrate that the proposed model consistently outperforms the benchmark policies by improving the market efficiency and enhancing the reliability of the market solution while maintaining scalability and transparency. The proposed model can be employed by contemporary solvers with minimal disruption to existing market procedures. [ABSTRACT FROM AUTHOR]

The level of uncertainty, which the power system operators should account for, increases as more renewables are integrated in the system. Additional operating reserves needs to be scheduled within security constrained economic dispatch to ensure reliability. Existing practices rely on conventional generators for providing operational flexibility required to mitigate the uncertainty introduced by renewables. However, with the increased share of renewables in the generation mix, such intermittent resources would be expected to take part in the balancing tasks, too. Providing a reserve margin allows wind generators to hedge against uncertainty. This paper examines the market implications of wind reserve margin policies used to mitigate uncertainty from wind resources. The market implications of the recently proposed optimized reserve margin policy factors are studied. Analysis on the Reliability Test System 1996 shows that reserve margin policy factors along with the proposed compensation scheme help in allocating payments toward renewable resources that present a good quality of service. [ABSTRACT FROM AUTHOR]

The uncertainty and variability associated with stochastic resources coupled with the constantly changing system operating conditions introduce new challenges to power systems. Smart, well-designed reserve policies are needed to assist the operators in maintaining system reliability. This paper presents a reserve response set model, which improves upon existing deterministic models. The proposed model aims to address the allocation and deliverability issues associated with reserves by using reserve response set policies and by modeling the predicted post-contingency effects of nodal reserve deployment on critical transmission elements. The performance of the proposed reserve model is compared against contemporary deterministic programs and an extensive-form stochastic program. The results show that the proposed reserve model outperforms the contemporary models and improves the deliverability of reserves post-contingency at reduced costs. All numerical results are based on the IEEE 118-bus and the 2383-bus Polish test systems. [ABSTRACT FROM AUTHOR]

The rapid increase in the integration of renewable resources has given rise to challenges in power system operations. Due to the uncertainty and variability of renewable generation, additional reserves may be needed to maintain reliability. Uncertainty complicates the process of economic dispatch and renders the deterministic optimization approach less effective. Existing optimization solutions for handling uncertainty, such as scenario-based stochastic programming and robust programming, are also computationally expensive, especially when there are multiple wind farms. Such approaches are less practical for large-scale systems during real-time operations. This paper investigates offline stochastic algorithms to train deterministic operational policies. Such policies are then added to real-time operational models. Specifically, an offline policy generation technique is proposed to provide a stochastic reserve margin to hedge against the real-time uncertainty of (multiple) wind farm generation. The proposed policy generation structure uses a forecast-based framework that accounts for wind generation and system loading conditions. The proposed approach is tested on the Reliability Test System 1996. The proposed approach is compared against existing reserve rules to demonstrate the improvement in handling uncertainty and achieving a more secure solution. [ABSTRACT FROM PUBLISHER]

Transmission switching (TS) has gained significant attention recently. However, barriers still remain and must be overcome before the technology can be adopted by the industry. The state-of-the-art challenges include AC feasibility, computational complexity, the ability to handle large-scale real power systems, and dynamic stability. This paper investigates these challenges by developing an AC corrective TS (CTS) based real-time contingency analysis (RTCA) tool that can handle large-scale systems within a reasonable time. The tool quickly proposes multiple high-quality corrective switching actions for contingencies with potential violations. To reduce the computational complexity, three heuristic algorithms are proposed to generate a small set of candidate switching actions. Parallel computing is implemented to further speed up the solution time. Moreover, time-domain simulations are performed to check for dynamic stability of the proposed CTS solutions. The promising results, tested on the Tennessee Valley Authority (TVA) system and actual energy management system snapshots from the PJM Interconnection (PJM) and the Electric Reliability Council of Texas (ERCOT), show that the tool effectively reduces post-contingency violations. It is concluded that CTS is ripe for industry adoption for RTCA application. [ABSTRACT FROM AUTHOR]

Regional transmission organisations and independent system operators include different types of security requirements to approximate system security issues. Transmission line contingencies are well handled in state-of-art market models with line outage distribution factors and, at the same time, the impacts of transmission line contingencies are reflected in energy prices. However, there is a lack of efficient mechanisms to handle generator contingencies and reflect the impacts of generator contingencies on energy prices. In this study, a set of security constraints to withstand single-generator-failure contingencies are presented and the market implications are studied. A new component of locational marginal prices, a marginal security component, which is a weighted shadow price of the security constraints, is proposed to better represent energy prices. A 3-bus system example is given to illustrate the market implications. The results are confirmed on a 73-bus system test case. [ABSTRACT FROM AUTHOR]

Regional transmission organisations and independent system operators include different types of security requirements to approximate system security issues. Transmission line contingencies are well handled in state‐of‐art market models with line outage distribution factors and, at the same time, the impacts of transmission line contingencies are reflected in energy prices. However, there is a lack of efficient mechanisms to handle generator contingencies and reflect the impacts of generator contingencies on energy prices. In this study, a set of security constraints to withstand single‐generator‐failure contingencies are presented and the market implications are studied. A new component of locational marginal prices, a marginal security component, which is a weighted shadow price of the security constraints, is proposed to better represent energy prices. A 3‐bus system example is given to illustrate the market implications. The results are confirmed on a 73‐bus system test case. [ABSTRACT FROM AUTHOR]

Enhanced utilization of the existing transmission network is a cheaper and paramount alternative to building new transmission lines. Flexible ac transmission system (FACTS) devices are advanced technologies that offer transfer capability improvements via power flow control. Although many FACTS devices exist in power systems, their set points are not frequently changed for power flow control purposes, which is mainly due to the computational complexity of incorporating FACTS flexibility within the market problem. This paper proposes a computationally efficient method for adjustment of variable impedance-based FACTS set points, which is also compatible with existing market solvers. Thus, the method can be employed by the existing solvers with minimal modification efforts. This paper models FACTS reactance control as injections to keep the initial shift factors unchanged. Next, the paper formulates a dc optimal power flow that co-optimizes FACTS set points alongside generation dispatch. The resulting problem, which is in a nonlinear program, is then reformulated to a mixed-integer linear program. Finally, an engineering insight is leveraged to further reduce the computational complexity to a linear program. Simulation studies on IEEE 118-bus and Polish 2383-bus test cases show that the method is extremely effective in finding quality solutions and being very fast. [ABSTRACT FROM AUTHOR]

While there are growing interests in using pumped hydro storage to facilitate the integration of renewable resources, the flexibility of storage is not being fully utilized by existing energy and market management systems. Today, one common approach to operate pumped hydro storage is to determine schedules for a future time horizon based on a look-ahead operational planning stage, with limited adjustment in real-time. However, as renewable penetration levels increase, such approaches do not fully utilize the flexibility of pumped hydro storage. In this paper, a policy function approach is proposed to enhance the utilization of pumped hydro storage in real-time operations. The performance of the approach is evaluated and compared with other benchmark approaches using the IEEE RTS 24-bus system. The result shows that the policy function approach is effective in utilizing the flexibility of pumped hydro storage and has minimal added computational complexity to the existing dispatch process. [ABSTRACT FROM AUTHOR]

Reserve requirements serve as a proxy for N-1 reliability in the security-constrained unit commitment (SCUC) problem. However, there is no guarantee that the reserve is deliverable for all scenarios (post-contingency states). One cheap way to improve reserve deliverability is to harness the flexibility of the transmission network. Flexible AC transmission system (FACTS) devices are able to significantly improve the transfer capability. However, FACTS utilization is limited today due to the complexities these devices introduce to the DC optimal power flow problem (DCOPF). With a linear objective, the traditional DCOPF is a linear program (LP); when variable impedance based FACTS devices are taken into consideration, the problem becomes a nonlinear program (NLP). A reformulation of the NLP to a mixed integer linear program, for day-ahead corrective operation of FACTS devices, is presented in this paper. Engineering insight is then introduced to further reduce the complexity to an LP. Although optimality is not guaranteed, the simulation studies on the IEEE 118-bus system show that the method finds the globally optimal solution in 98.8% of the cases. Even when the method did not find the optimal solution, it was able to converge to a near-optimal solution, which substantially improved the reliability, very quickly. [ABSTRACT FROM PUBLISHER]

Reliable and economic deployment of a generation fleet to satisfy demand is a complex problem. Independent system operators (ISOs) and regional transmission operators (RTOs) solve complex unit commitment and economic dispatch models to determine appropriate resources to deploy at various time stages. Due to the complexity of power systems, several approximations are made within optimization models, including approximations of the transmission network with a linearized formulation known as the direct current optimal power flow (DCOPF) instead of the more realistic formulation known as the alternating current optimal power flow (ACOPF). Furthermore, approximations occur in these models by relaxing specific constraints in the model, i.e., the constraint is allowed to be violated based on a predetermined penalty price. By doing so, the ISO/RTO receives several benefits, including the ability to manage prices, clear the market, as well as the potential to obtain gains in social welfare (market surplus). This paper describes the constraint relaxation practices of ISOs in their unit commitment models and analyzes the corresponding market implications based on these practices. [ABSTRACT FROM PUBLISHER]

In recent years, the penetration of renewable resources in electrical power systems has increased. These renewable resources add more complexities to power system operations, due to their intermittent nature. As a result, operators must acquire additional reserves in order to maintain reliability. However, one persistent challenge is to determine the optimal location of reserves and this challenge is exacerbated by the inability to predict key transmission bottlenecks due to this added uncertainty. This paper presents robust corrective topology control as a congestion management tool to manage power flows and the associated renewable uncertainty. The proposed day-ahead method determines the maximum uncertainty in renewable resources in terms of do-not-exceed limits combined with corrective topology control. The day-ahead topology control formulation is based on the direct current optimal power flow; therefore, topology control solutions obtained from these algorithms are tested for AC feasibility and system stability. The numerical results provided are based on the IEEE-118 bus test case and the Tennessee Valley Authority (TVA) test system. [ABSTRACT FROM AUTHOR]

Transmission systems are under stress and need to be upgraded. Better utilization of the existing grid provides a fast and cheap alternative to building new transmission. One way to improve the utilization of the transmission network is power flow control via flexible ac transmission system (FACTS) devices. While FACTS devices are used today, the utilization of these devices is limited; traditional dispatch models (e.g., security constrained economic dispatch) assume a fixed, static transmission grid even though it is rather flexible. The primary barrier is the complexity that is added to the power flow problem. The mathematical representation of the DC optimal power flow, with the added modeling of FACTS devices, is a nonlinear program (NLP). This paper presents a method to convert this NLP into a mixed-integer linear program (MILP). The MILP is reformulated as a two-stage linear program, which enforces the same sign for the voltage angle differences for the lines equipped with FACTS. While this approximation does not guarantee optimality, more than 98% of the presented empirical results, based on the IEEE 118-bus and Polish systems, achieved global optimality. In the case of suboptimal solutions, the savings were still significant and the solution time was dramatically reduced. [ABSTRACT FROM AUTHOR]

Transmission switching, as a power flow control mechanism that can reduce costs and improve reliability, has gained a lot of attention during the last decade. Despite its benefits, industry adoption has been very limited due to its computational complexity, stability and AC performance concerns. Pennsylvania New Jersey Maryland (PJM) has published a list of corrective switching solutions to relieve actual and post‐contingency network violations. The list is developed based on operators' prior knowledge and offline studies. This study employs a fast AC‐based real‐time contingency analysis (RTCA) tool with corrective transmission switching (CTS) functionality to analyse PJM's switching solutions with actual PJM data. The results show that the RTCA CTS tool is almost always able to find solutions that perform better than, or equally as well as, PJM's solutions. The results also show that PJM's list identifies solutions for only 3% of the problematic contingencies with post‐contingency violations over the course of one week. The RTCA CTS tool, however, is able to find corrective TS solutions for almost all the cases. The results suggest that CTS is ripe for industry adoption. The tool provides significant savings and would pave the road towards a smarter transmission network as an essential ingredient of the future smart grid. [ABSTRACT FROM AUTHOR]

The fast growing expansion of renewable energy increases the complexities in balancing generation and demand in the power system. The energy-shifting and fast-ramping capability of energy storage has led to increasing interests in batteries to facilitate the integration of renewable resources. In this paper, we present a two-step framework to evaluate the potential value of energy storage in power systems with renewable generation. First, we formulate a stochastic unit commitment approach with wind power forecast uncertainty and energy storage. Second, the solution from the stochastic unit commitment is used to derive a flexible schedule for energy storage in economic dispatch where the look-ahead horizon is limited. Analysis is conducted on the IEEE 24-bus system to demonstrate the benefits of battery storage in systems with renewable resources and the effectiveness of the proposed battery operation strategy. [ABSTRACT FROM PUBLISHER]

The means for transporting more power through an existing transmission corridor have been given considerable attention in recent studies. Reconductoring a path with a conductor that has a higher thermal capacity, such as a high temperature low sag (HTLS) conductor, is one possible option with minimal structural modification and out-of-service time. Parallel line additions or HTLS parallel line additions are other options that can increase transfer capabilities and reduce operating costs. Thermal constraint relaxation is another option, which is an operational based method that allows the line flow to exceed the steady-state line rating for a certain penalty price. Since such operation may deteriorate the expected service time of the conductor, the penalty price should be determined properly. In this study, the above options are captured to create the proposed transmission expansion planning model. In addition, a conductor degradation model is introduced to capture the associated degradation costs due to operating conductors at elevated temperatures. Numerical simulations conducted on the IEEE-24 and IEEE-118 bus system indicate the effectiveness of the proposed approach to increase system capacity while preserving current right-of-ways (ROWs). [ABSTRACT FROM AUTHOR]

The means for transporting more power through an existing transmission corridor have been given considerable attention in recent studies. Reconductoring a path with a conductor that has a higher thermal capacity, such as a high temperature low sag (HTLS) conductor, is one possible option with minimal structural modification and out‐of‐service time. Parallel line additions or HTLS parallel line additions are other options that can increase transfer capabilities and reduce operating costs. Thermal constraint relaxation is another option, which is an operational based method that allows the line flow to exceed the steady‐state line rating for a certain penalty price. Since such operation may deteriorate the expected service time of the conductor, the penalty price should be determined properly. In this study, the above options are captured to create the proposed transmission expansion planning model. In addition, a conductor degradation model is introduced to capture the associated degradation costs due to operating conductors at elevated temperatures. Numerical simulations conducted on the IEEE‐24 and IEEE‐118 bus system indicate the effectiveness of the proposed approach to increase system capacity while preserving current right‐of‐ways (ROWs). [ABSTRACT FROM AUTHOR]

With the significant penetration of wind generation, the variability and uncertainty of wind energy poses new challenges to power system operations. In particular, more rapid reserve is required, which may result in the scarcity of balancing services. With the increasing penetration of renewable generation, it is envisaged that renewable resources will be required to partake in the system balancing tasks. In this paper, a combined flexible dispatch and reserve scheduling policy is proposed by determining a flexible wind dispatch margin. In order to provide a flexible dispatch margin, wind generators underschedule in the hour-ahead energy market, so as to hold some expected output for reserves. Additional wind energy is then available for mitigating forecast errors and other system uncertainties. This paper presents a framework to find the optimal policy to incorporate the flexible wind dispatch margin into the hour-ahead market. A finite-state Markov chain wind power forecast model, based on spatio-temporal analysis, is utilized. The presented framework is used to find the appropriate level of wind dispatch margin. The proposed approach is tested and the wind generation data are used to analyze the effectiveness of the presented model in coping with forecast errors and achieving a more secure system operation. [ABSTRACT FROM PUBLISHER]

This study focuses on developing an integrated transmission and distribution framework that couples the two sub‐systems together with due consideration to conventional demand flexibility. The proposed framework ensures accurate representation of the system resources and the network conditions when modelling the distribution system in the transmission optimal power flow and vice‐versa. It is further used to develop an accurate pricing mechanism (distribution‐based location marginal pricing), which is reflective of the moment‐to‐moment costs of generating and delivering electrical energy, for the distribution system. By accurately modelling the two sub‐systems, the authors can improve the economic efficiency and the system reliability, as the price sensitive resources can be controlled to behave in a way that benefits the power system as a whole. [ABSTRACT FROM AUTHOR]

High penetration levels of renewable resources impose increasing uncertainty and variability on power system operations. Traditionally, power systems rely on conventional generators (CGs) to balance the uncertainty in renewable generation. However, as renewable penetration levels increase, CGs may suffer from higher operating costs while receiving lower profits. In contrast, since bulk energy storage can store and shift clean energy and have fast ramping capability, they may become more competitive under high renewable penetration levels. In this paper, a stochastic unit commitment model with energy storage will be presented to evaluate the short-term profitability of CGs and energy storage under different levels of renewable penetrations. The short-term profitability of CGs and energy storage units will be compared to identify the impact of increasing renewable penetration on the attractiveness of bulk energy storage in comparison to CGs. [ABSTRACT FROM PUBLISHER]

In order to ensure a reliable and continuous supply of electric energy, operators must manage hundreds to thousands of generators with complex operating requirements, maintain synchronism, and manage thousands of transmission assets. Further complications arise due to stringent reliability standards, resource uncertainty, and limited economical energy storage. With advances in algorithmic performance and hardware, such optimization problems still require an engineered and simplified market structure. Market operators must therefore adjust the proposed market solution in order to obtain a valid solution. An overview of existing industry practices related to such market adjustments, referred to as out-of-market corrections, is presented. This paper also analyzes the market implications and required out-of-market corrections for the day-ahead scheduling process. Multiple out-of-market correction algorithms are created and used to analyze the potential impacts on market solutions and settlements. Finally, such solutions are compared against an extensive form stochastic unit commitment solution. [ABSTRACT FROM PUBLISHER]

Static reserve policies are used within security-constrained unit commitment (SCUC) and security constrained economic dispatch (SCED) to ensure reliability. A common policy is that 10-min reserve must exceed the largest contingency. However, this condition does not guarantee reliability because voltage and thermal limits can hinder reserve deliverability. Many operators use zonal reserve markets to ensure reserves are dispersed across the grid. Such zonal models attempt to anticipate transmission bottlenecks, which is a difficult task when the future system state is uncertain. This paper examines the market implications of dynamic reserve policies used to mitigate uncertainty from renewable resources and contingencies. We study the market implications of policies recently proposed in the literature, such as hourly zones within day-ahead SCUC and an algorithm that formally disqualifies reserves that are expected to be undeliverable. A locational reserve pricing scheme is also proposed in connection with scenario-based reserve disqualification. Analysis on the RTS-96 test case shows that dynamic zones and reserve disqualification, along with the proposed compensation scheme, help direct reserve payments toward resources that more effectively respond to contingencies. [ABSTRACT FROM PUBLISHER]

As more non-dispatchable renewable resources are integrated into the grid, it will become increasingly difficult to predict the transfer capabilities and the network congestion. At the same time, renewable resources require operators to acquire more operating reserves. With today's deterministic reserve requirements unable to ensure optimal reserve locations, improvements to reserve policies are needed to ensure reserve deliverability while maintaining a reliable system at least cost. This paper proposes a daily reserve zone determination procedure, which is able to reflect system operating conditions by utilizing probabilistic power flows. A statistical clustering algorithm is used to cluster buses together to produce the zones; the algorithm uses a centrality measurement, which is based on weighted power transfer distribution factors. The proposed method is validated by testing it on a modified IEEE 118-bus system for multiple days; the proposed method is compared against existing reserve zone partitioning procedures. While the proposed reserve zone determination method is a heuristic, it is shown to be effective and it is a computationally tractable method. The proposed method can be used on its own and can be used along with stochastic programming techniques that implicitly determine reserves. [ABSTRACT FROM PUBLISHER]

Reserve requirements promote reliability by ensuring resources are available to rebalance the power system following random disturbances. However, reliability is not guaranteed when dispatch is limited by transmission constraints. In this work, we propose a modified form of reserve requirement that identifies response sets for distinct contingency scenarios. The approach disqualifies reserve from counting towards a particular scenario if transmission constraints are likely to render that reserve undeliverable. A decomposition algorithm for security-constrained unit commitment dynamically updates the response sets to address changing conditions. Testing on the RTS 96 test case demonstrates the approach applied in tandem with existing reserve policies to avoid situations where reserve is not deliverable due to transmission constraints. Operational implications of the proposed method are discussed. [ABSTRACT FROM PUBLISHER]