Transmission Congestion Relief Research Articles

Power Flow Optimization with Energy Storage - Sal Island Case Study

The correlation between energy costs and the country's economic competitiveness is an unquestionable reality also responsible for the improvement of the population's life conditions. In the past Cape Verdean electric power system (EPS), expansion was based on fossil-fuel power plants, nowadays it shifted to renewable energy (RE) which is abundant in the Cape Verde archipelago. However, no reduction in the electricity tariffs occurred, due to renewable curtailment and other pendent questions related to power transmission losses in the EPS. This paper presents an approach, that supports an implementation of a distributed electric energy storage system (ESS) on the Sal Island of Cape Verde archipelago, as a solution to increase the RE integration and power Transmission congestion relief. Thus, a power flow optimization is only achievable by storing excess RE as near as possible to consumption buses that can reduce overall transmission losses. The most advantageous allocation of ESSs along the EPS buses is combinational which faces a maximization of transmission loss reduction and minimization of ESS investment capital. The proposed tool to manage the “trade-off” between cost and avoided losses, is based on a genetic algorithm (GA) that is broadly applied to multi-objective problems like this.

Leveraging rail-based mobile energy storage to increase grid reliability in the face of climate uncertainty

Maintaining reliability is increasingly challenging for electric grids as they endure more frequent extreme weather events and utilize more intermittent generation. Exploration of alternative reliability approaches is needed to effectively address these emerging issues. Here we examine the potential to use the US rail system as a nationwide backup transmission grid over which containerized batteries, or rail-based mobile energy storage (RMES), are shared among regions to meet demand peaks, relieve transmission congestion and increase resilience. We find that RMES is a feasible reliability solution for low-frequency, high-impact events and quantify its cost effectiveness relative to reliability-driven investments in transmission infrastructure and stationary capacity. Compared to new transmission lines and stationary battery capacity, deploying RMES for such events could save the power sector upwards of US$300 per kW-year and US$85 per kW-year, respectively. While no known technical barriers exclude RMES from grid participation, addressing interconnection challenges and revising regulatory frameworks is necessary for deployment at scale.

The flexible roles of distributed energy storages in peer-to-peer transactive energy market: A state-of-the-art review

With the development of distributed energy resources, the peer-to-peer (P2P) transactive energy market has emerged as an effective method for consuming the excess renewable energy on the end-user side. In the current research on transactive markets, distributed energy storages (DESs) have been widely applied in energy trading for transaction flexibility and system management. These small-scale energy storages have achieved a considerable momentum that, if properly harnessed, may unleash their potential for prosumers’ utility maximization, reserves for renewable energy uncertainty, and transmission congestion relief. The present work reviews distributed energy storage in the transactive market, classifying and analyzing 120 papers according to their applications, algorithms, and adopted policies. This study first identifies DES functions in wholesale and transactive markets and then provides the mathematical models of DESs in various transactive market types in detail. This paper then focuses on the pricing mechanism for the DESs’ contributions in the P2P transactive energy market. A transactive energy market mechanism for accommodating DESs is proposed based on the Vickrey–Clarke–Groves framework to meet incentive compatibility. The energy policies related to the promotion of DESs in electricity markets are listed and compared. Furthermore, this review highlights the possible questions and future development opportunities according to the analyzed studies. With the roles and relationships among aggregators, DES owners, and power grid determined, the benefit of participating P2P transactive market can be further improved.

MACHINE LEARNING BASED ISLANDING DETECTION DURING BLACKOUT

In modern era, demand of electricity is increasing rapidly due to fast development in industrial sector, communication technologies, commercial and domestic usage. The need of the hour is to protect the power system from blackouts during abnormal conditions, like voltage collapse and frequency disturbance etc between the generation and consumption. The sudden change in weather conditions, loading of power system, and over ageing of transmission and distribution lines becomes the cause of blackouts. Islanding detection and protection is one of the best possible techniques to improve the power quality, reliability, system security, transmission congestion relief and efficient energy utilization. Distribution generators (DGs), if properly placed have many positive impacts on the operation of power system. The islanding can improve the reliability by counting the operation of electrical power to keep the balance between consumption and generation. The main problem is sustained islanding with fast timing. Plant should sustain its island mode condition when fault occurs in transmission lines. Most islanding detection algorithms suffer from large NDZ and Non detection zone must be minimized to protect system properly and avoid blackouts. This study presents a technique to develop a reliable system to prevent complete blackouts, while maintaining the stability of the power system with high variability and uncertainty under the abnormal conditions. It is also needed to present the period all the DGs need to connect and disconnect immediately when the island occurs. For this purpose, each DG must be equipped with islanding detection devices. In this research work the presented system is a two-step process, based on the collection of some of the key characteristics in the current and voltage signals to analyze second harmonic by the Fourier transform (FT).

Evaluating Options to Integrate Energy Storage Systems in Albania

The focus of the paper is to identify for the first time the most adequate energy storage systems (ESS) applicable in the central or bulk generation of the electricity sector in Albania. The application and integration of ESS is a smart way to overcome the problems of timely power supply volatility and minimizing energy losses, transmission congestion relief and upgrade deferral (top 10%), energy time shift (arbitrage), and many other services that reduce the cost of electricity and gain the security of energy supply. The presence of high-level rates of water discharges into the Hydropower Power Plants (HPP) and the problems of congestion in the transmission grid are the two main problems that require new methods for addressing and solving them. To select the right form and type of ESS that should be applied in our national energy system, E-select, a very flexible and internationally approved model is chosen. The results of this study are necessary for achieving a flexible, cheaper, and environmentally friendly energy system in Albania.

Temporal complementarity of marine renewables with wind and solar generation: Implications for GB system benefits

Wave and tidal energy have the potential to provide benefits to power systems with high proportions of stochastic renewable generation. This is particularly applicable in combination with wind and solar photovoltaics, as the offsetting of these renewable resources results in more reliable renewable generation. This study utilises ten metrics to quantify the temporal complementarity and supply-demand balancing requirements of the energy mix in Great Britain, to investigate the potential magnitude of these system benefits. Wave and tidal generation profiles are created using historical resource data and hydrodynamic models. The results show that the inclusion of wave and tidal generation creates a renewable energy mix which is more available under multiple conditions: throughout a year of operation; at times of peak demand; for multiple consecutive hourly time periods; and at times when wind and solar generation are not available. Three regional case studies also show that the inclusion of marine energy allows for improved regional supply-demand matching, reducing instances of energy shortage and excess and potentially relieving transmission congestion at particularly constrained locations within GB. Finally, the implications of these findings are discussed in terms of GB wholesale market operation, system balancing and system security.

Energy Storage as a Service: Optimal sizing for Transmission Congestion Relief

In this paper, we propose a risk-based optimal sizing model for Storage as Transmission Alternative (SATA) intended for Transmission Congestion Relief (TCR) services. The storage system is sized from the perspective of the regulator/network operator with the ultimate goal of minimizing the cost of TCR to the ratepayers. The concept of Energy Storage as a Service (ESaaS) is considered when developing the models assuming that SATA’s idle capacity is rented out for a fee to third parties who would participate in energy and ancillary services markets. The fees collected through market participation services are assumed to be credited back to the ratepayers to offset the overall costs of removing network congestion. The presented simulation results provide insights into the financial benefits and risks associated with allowing SATA to share its excess capacity for additional revenues.

Driving to the future of energy storage: Techno-economic analysis of a novel method to recondition second life electric vehicle batteries

The transportation sector is trending towards electrification which means a dramatic change to the availability of used Lithium-ion (Li-ion) batteries which can be reused for grid energy storage systems (ESS). However, second life battery modules can have an imbalanced state of health (SOH) between cells which can reduce battery safety, life, and depth of discharge. This work evaluates the economics of a novel Heterogeneous Unifying Battery (HUB) reconditioning system that cycles battery modules to unify cells’ SOH to improve their second life battery performance. The HUB reconditioning cycles can be performed in one of two ways: recondition with grid services or recondition through energy shuffle. The results from this work demonstrate that a simple repurposing process will likely have a lower second life resale price (56 $/kWh) than the HUB system (62 $/kWh) in our baseline scenario; however, in our target scenario the HUB system (34 $/kWh) has a lower resale price than the repurposing system (38 $/kWh). This work also includes an economic analysis for using reconditioned batteries in a grid ESS that was compared to an ESS that is assembled with new Li-ion batteries. Results show that HUB reconditioned ESS require less grid revenue (194 $/kW-year) than new Li-ion ESS (253 $/kW-year). Finally, the HUB reconditioned ESS is shown to be economically feasible in 63% of frequency regulation, 18% of transmission congestion relief, and 16% of demand charge reduction markets but not economically feasible in spin/non-spin reserve, voltage support, and energy arbitrage markets.

Enhancing the power grid flexibility with battery energy storage transportation and transmission switching

The penetration of large-scale renewable energy puts an urgent demand on increasing power grid flexibility. From the power grid perspective, transmission congestion has become one of the bottle-neck factors limiting renewable energy integration. In the tradition, transmission topology is regarded to be unadjustable, and energy storage only plays an important role in the local area where it locates. To enhance the transmission system flexibility and relieve transmission congestion, this paper proposes a network-constraint unit commitment (NCUC) model considering battery energy storage transportation (BEST) and transmission switching (TS). This model is integrated with a novel indicator based BEST model and a TS model to minimize the overall operating cost. The benefits of BEST mobility and TS flexibility are quantitatively evaluated through compared with the traditional NCUC model. Based on the difference between the overall operating cost of unit commitment (UC) and NCUC, we quantitatively evaluated the flexibility provided by BEST and TS by the overall operating cost reduction. A case study on a modified IEEE RTS-79 system is provided to validate the effectiveness of the proposed model. The results show that the BEST and TS have a synergistic effect on enhancing power grid flexibility, which reflects in this study as the power grid operating economics improvement and renewable energy curtailment reduction. Besides, though the BEST and TS bring transmission system more losses, applying them into the system could relieve transmission congestion, which makes them valuable technologies to improve power system security.

Utilization of energy storage systems in congestion management of transmission networks with incentive-based approach for investors

Electricity demand growth and other factors in the power system have increased the probability of congestion occurrence in power transmission lines. In recent years, there is more tendency for energy storage systems (ESSs) due to their high applications in the power system. One of these applications is the capability to relieve congestion. One of the main challenges of using ESSs is the high investment cost. In this paper, for expansion planning problem, a multi-objective optimization framework to relieve transmission congestion is proposed, combined with the use of new lines and ESSs. In the proposed framework, the viewpoint of the system operator and ESSs owner are simultaneously considered. Furthermore, an incentive-based approach for the investment of ESSs is suggested. The proposed method is implemented on the IEEE-RTS 24-bus system using pumped-storage hydro power plant (PSHP) and compressed-air energy storage (CAES) systems. The simulation results include a set of non-dominated optimal solutions that are obtained using the multi-objective genetic algorithm NSGA-II. The results provide optimal locations for new lines and ESSs and demonstrate the effectiveness of the incentive-based approach for selecting the best solution.

Transmission congestion management considering EV parking lots and demand response programmes

ABSTRACT Transmission congestion is one of the key elements affecting spike price and local market power. Reducing the demand and increasing the generation in distribution network may lead to relive the congestion of a transmission line. Plug-in hybrid electrical vehicle (PHEVs) parking lots and emergency demand response programmes (EDRP) are considered as two main options to manage the demand of a transmission bus. In this paper, a novel approach is proposed to determine the optimal capacity of EDRP and PHEV parking lots in order to relieve transmission congestion in a least-cost manner. The behaviour of EDRP participants and available capacity of the parking lot are mathematically modelled. Genetic algorithm (GA) with binary variables is employed to solve the optimisation problem. Simulation is carried out on a 14-bus transmission network. Results demonstrate the optimal contribution of parking lots and EDRP has a significant effect on mitigating congestion and decreasing the cost of the system.

Energy Storage as a Service: Optimal Pricing for Transmission Congestion Relief

This paper focuses on pricing Energy Storage as a Service (ESaaS) for Transmission congestion relief (TCR). We consider a merchant storage facility that competes in an electricity market to trade energy and ancillary services on a day-to-day basis. The facility also has the opportunity to provide a firm TCR service to a regional network operator under a long-term contract. Providing the additional TCR service would impose limitations on the facility's ability to fully harvest daily market trade opportunities. Thus, we model the opportunity costs associated with the TCR service and use it in a hybrid cost-value customized pricing technique to determine the risk-constrained optimal price of ESaaS for TCR. Given the long-term nature of the commitment to provide the TCR service, we use the Conditional Value at Risk (CVaR) metric to mitigate the long-term financial risks faced by the facility. The proposed pricing strategy enables the storage owner to estimate the additional financial gains and the associated risks that would likely result from adding the new service to its operation. Numerical simulations are provided to support the proposed methodology.

Transmission-Scale Battery Energy Storage Systems: A Systematic Literature Review

When the transmission capacity of an electrical system is insufficient to adequately serve customer demand, the transmission system is said to be experiencing congestion. More transmission lines can be built to increase capacity. However, transmission congestion typically only occurs during periods of peak demand, which occur just a few times per year; capitol-intensive investments in new transmission capacity address problems that occur infrequently. Alternative solutions to alleviated transmission congestion have been devised, including generation curtailment, demand response programs, and various remedial action schema. Though not currently a common solution, battery energy storage systems can also provide transmission congestion relief. Technological and market trends indicate the growing production capacity of battery energy storage systems and decreasing prices, which indicate the technology may soon become a viable option for providing congestion relief. Batteries can provide multiple ancillary services, and so can concurrently provide value through multiple revenue streams. In this manuscript, the authors present a systematic review of literature, technology, regulations, and projects related to the use of battery energy storage systems to provide transmission congestion relief.

Robust Co-Planning of Energy Storage and Transmission Line With Mixed Integer Recourse

Energy storage is a potential planning option to relieve transmission congestion caused by increasing penetration of renewable energy. This paper presents a robust formulation for energy storage and transmission line co-planning, considering binary variables that represent energy storage statuses in the recourse problem. In order to solve this model, an improved nested column and constraint generation algorithm is used to cope with numerical issues caused by new binary variables, big-M constraints, and the enormous size of the problem. Case studies of a modified Garver's 6-bus system and a practical Chinese 196-bus system were used to assess the effectiveness of the proposed approach. The numerical results indicate that energy storage is more economical for relieving the transmission line congestion when the transmission distance is relatively long.

전력경제] 우리나라 전력시장에서 수도권 열병합발전기의 송전혼잡완화 편익 산정 연구

전력경제] 우리나라 전력시장에서 수도권 열병합발전기의 송전혼잡완화 편익 산정 연구

Modeling of demand response programs based on market elasticity concept

Demand response programs (DRPs) are appropriate tools to improve power system operation. Applying these programs results in a reduction in reliability cost and electricity price, transmission congestion and pollution relief, and also can determine postponements in network expansion. Therefore, developing a comprehensive model for DRPs is necessary for accurate planning and encouragement of consumers to increase their participation. In this paper, by using the market elasticity concept, a comprehensive model for DRPs is developed. Market elasticity is defined as sensitivity of electricity price on the network load. The proposed model is able to increase the consumers’ participation by providing a higher awareness about their participations’ effects on their electricity cost reduction. This additional awareness is provided by creating the information about the impact of consumers’ participation on the price of the electricity market in addition to the direct impact of their participations on their cost reduction. Information about the impact of consumers’ participation on the price of the electricity market is provided by the market elasticity concept. The effectiveness of the proposed $${\rho _0}(i)$$ model is demonstrated by simulation results.

An HPC based real-time path rating calculation tool for congestion management with high penetration of renewable energy

Every year, transmission congestion costs billions of dollars for electricity customers. This clearly identifies the critical need for more transmission capacity and also poses big challenges for power grid reliability in stressed conditions due to heavy loading and in uncertain situations due to variable renewable resources and responsive smart loads. However, it becomes increasingly difficult to build new transmission lines, which typically involve both economic and environmental constraints. In this paper, advanced computing techniques are developed to enable a non-wire solution that realizes unused transfer capabilities of existing transmission facilities. An integrated software prototype powered by high-performance computing (HPC) is developed to calculate ratings of key transmission paths in real time for relieving transmission congestion and facilitating renewable integration, while complying with the North American Electric Reliability Corporation (NERC) standards on assessing total transfer capabilities. The innovative algorithms include: (1) massive contingency analysis enabled by dynamic load balancing, (2) parallel transient simulation to speed up single dynamic simulation, (3) a non-iterative method for calculating voltage security boundary and (4) an integrated package considering all NERC required limits. This tool has been tested on realistic power system models in the Western Interconnection of North America and demonstrates satisfactory computational speed using parallel computers. Various benefits of real-time path rating are investigated at Bonneville Power Administration using realtime EMS snapshots, demonstrating a significant increase in path limits. These technologies would change the traditional goals of path rating studies, fundamentally transforming how the grid is operated, and maximizing the utilization of national transmission assets, as well as facilitating integration of renewable energy and smart loads.

A Lagrangian Decomposition Approach to Energy Storage Transportation Scheduling in Power Systems

In this paper, we propose a security-constrained unit commitment (SCUC) model which considers the impact of mobility of Battery-based Energy Storage Transportation (BEST) system. The BEST technology considers the transmission of electricity via rails (in the form of storage) rather than utilizing transmission lines, which allows transmission grid operators to focus on certain geographical regions of the grid and provides the grid with more flexibility to relieve the congestion. To solve the resulting large-scale MILP model, a Lagrangian decomposition-based technology is presented, which uses a modified sub-gradient method to accelerate the convergence of the BEST algorithm. The IEEE 118-bus system integrated with a railway network composed of 8 railway stations and 10 rail lines is used to illustrate the applicability of the BEST model and the performance of the algorithm. The results show that the BEST solution can reduce the overall cost of power delivery by transporting the electricity from low locational marginal price (LMP) areas to high LMP areas, relieve transmission congestion, reduce the need for acquiring additional transmission right-of-ways, and optimize the use of existing space on freight trains which is already vacated by the closure of coal power plants throughout the country.

Rescheduling of real power for congestion management with integration of pumped storage hydro unit using firefly algorithm

Post-deregulation era of power system operation produces more pressure on Independent System Operator (ISO) to ensure congestion free transmission network without destroying system security. In order to relieve transmission congestion, ISO initiates correct methods by maintaining system reliability and security. This paper considers a novel efficient technique for congestion management like generator real power rescheduling by integrating a pumped storage hydro unit (PSHU) in the system. This paper presents an optimization model for congestion management by incorporating the calculation of two factors like generator sensitivity factor (GSF) and bus sensitivity factor (BSF). Optimal location of PSHU is identified using the value of BSF’s and the numbers of participated generators for congestion management by rescheduling their outputs are determined using the value of GSF’s. The impact of PSHU has been investigated to manage transmission congestion which further reduces the congestion cost and improves security of the system. The proposed method for congestion management considering PSHU is tested on modified IEEE-39 bus New England test system and the validity is obtained by considering the same problem without the presence of PSHU. The result of proposed work with proper utilization of PSHU illustrates the impact of PSHU towards the congestion management and also exploration of firefly algorithm for minimizing the transmission congestion cost.

Transmission Congestion Relief Using Privately Owned Large-Scale Energy Storage Systems in a Competitive Electricity Market

The trend of integrating more nondispatchable renewable sources into the electric grid and phasing out dispatchable fossil-fueled power plants in the near future reduces the operational flexibility, increases the chance of transmission congestion, and endangers the stability of electric system. Utilities are investigating the application of large-scale energy storage systems (ESSs) to address some of these imminent challenges to their power systems. In this paper, the application of privately owned large-scale ESSs for the purpose of congestion relief in transmission systems as an ancillary service is investigated. It is demonstrated that in conventional optimal dispatch algorithms for an ESS, the storage system cannot effectively contribute to congestion relief since the dispatch algorithm has not prepared the ESS in advance. Hence, a new real-time optimal dispatch (RTOD) algorithm is proposed that aims to generate revenue primarily by exploiting electricity price arbitrage opportunities in the day-ahead electricity market while optimally preparing the ESS to maximize its contribution to congestion relief as an ancillary service. A compressed-air ESS is sized and employed for evaluations of the proposed RTOD algorithm. The efficacy and feasibility of the proposed algorithm are validated using real-world price data from Ontario's wholesale electricity market. An analysis is presented regarding the appropriate amount of financial compensation for the ESS owner due to this contribution to congestion relief in the studied electricity market.