Day-Ahead Scheduling of Distribution Level Integrated Electricity and Natural Gas System Based on Fast-ADMM With Restart Algorithm
TL;DR: A day-ahead scheduling framework of integrated electricity and NG system (IENG) is proposed at a distribution level based on the fast alternating direction multiplier method with restart algorithm considering demand side response and uncertainties.
Abstract: Power generated by the natural gas (NG) is a promising option for solving the restrictions on the development of the power industry. Consequently, the high interdependence between NG network and electricity network should be considered in this integration. In this paper, a day-ahead scheduling framework of integrated electricity and NG system (IENG) is proposed at a distribution level based on the fast alternating direction multiplier method with restart algorithm considering demand side response and uncertainties. Within the proposed framework, the detailed model of the IENG system at a distribution level is established, where the NG flow equation is processed by incremental linearization method to improve the computational efficiency. The objective is to minimize the operation costs of the entire system. With consideration of the uncertainties of distributed generation and electricity load as well as the uncertainties from the NG load, a two-stage robust optimization model is introduced to obtain the worst case within the uncertainty set, which is solved by column and constraints generation algorithm. In addition, the demand-side response (DSR) model including the decentralized air conditioning (AC) load model and the centralized ice-storage AC load model is integrated into the scheduling framework. Finally, the proposed day-ahead scheduling framework is verified by numerical studies where the optimal scheduling schemes are obtained in different cases, both the effects of the uncertainties and the performance with introducing DSR to the system operation are analyzed.
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TL;DR: A detailed model for the IPGS is presented with the consideration of the power-to-gas devices and gas storages, and the gas storage life reliability model is considered to characterize the charging and discharging performance.
Abstract: The reliability evaluation of integrated power-gas systems (IPGS) becomes critical due to the high dependency of the two energy systems. Once a contingent incident happens in one system, the other system will accordingly be affected. In this paper, a detailed model for the IPGS is presented with the consideration of the power-to-gas devices and gas storages. Furthermore, a sequential Monte Carlo (SMC) simulation is utilized to evaluate the reliability of the IPGS. In particular, the gas storage life reliability model is considered to characterize the charging and discharging performance. Moreover, an optimal load shedding model is used to coordinate the load shedding of the IPGS. What's more, new reliability indices are given to display the reliability of the IPGS. Finally, the proposed model is tested on an integrated IEEE 24-bus power system and 20-node gas system and an integrated IEEE RTS 96 power system and 40-node gas system. The results show the effectiveness of the proposed model.
119 citations
Cites methods from "Day-Ahead Scheduling of Distributio..."
...Particularly, the piecewise linearization to a non-linear function requires the Special Ordered Set of type Two (SOS2) [36]....
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TL;DR: In this paper, the authors present a survey of the latest investigations into coordinated home energy management systems (HEMSs) and the required steps to implement these systems, accounting for coordination topologies and techniques, are thoroughly explored.
Abstract: High penetration of selfish Home Energy Management Systems (HEMSs) causes adverse effects such as rebound peaks, instabilities, and contingencies in different regions of distribution grid. To avoid these effects and relieve power grid stress, the concept of HEMSs coordination has been suggested. Particularly, this concept can be employed to fulfill important grid objectives in neighborhood areas such as flattening aggregated load profile, decreasing electricity bills, facilitating energy trading, diminishing reverse power flow, managing distributed energy resources, and modifying consumers’ consumption/generation patterns. This paper reviews the latest investigations into coordinated HEMSs. The required steps to implement these systems, accounting for coordination topologies and techniques, are thoroughly explored. This exploration is mainly reported through classifying coordination approaches according to their utilization of decomposition algorithms. Furthermore, major features, advantages, and disadvantages of the methods are examined. Specifically, coordination process characteristics, its mathematical issues and essential prerequisites, as well as players concerns are analyzed. Subsequently, specific applications of coordination designs are discussed and categorized. Through a comprehensive investigation, this work elaborates significant remarks on critical gaps in existing studies toward a useful coordination structure for practical HEMSs implementations. Unlike other reviews, the present survey focuses on effective frameworks to determine future opportunities that make the concept of coordinated HEMSs feasible. Indeed, providing effective studies on HEMSs coordination concept is beneficial to both consumers and service providers since as reported, these systems can lead to 5% to 30% reduction in electricity bills.
34 citations
TL;DR: Results show that the configuration generated by the two-level planning model can satisfy the daily reserve requirements for emergency failures, and the resilient scheduling strategy with storage reserve can improve the system resilience effectively.
Abstract: The coupling in integrated electricity and gas community energy system (IEGS) provides alternative operation modes when unpredictable outages occur at energy-supply sides. Reasonable operation strategies and system configuration can effectively improve the system's resilience, making reliable and continuous operation feasible. Based on the complementary characteristics and reserve capabilities of IEGS, this paper proposes a multi-stage scheduling strategy for resilience enhancement in which thermal storage serves as emergency response resources. The resilient scheduling framework consists of rolling reserve optimization stage, day-ahead economic dispatch stage and fault restoration stage. With the reserve capacity of energy storage generated by rolling optimization and day-ahead dispatch, multiple forms' critical loads will be satisfied in priority when outage occurs on energy-supply sides. Furthermore, a two-level planning model integrating the resilient operation strategy is formulated to better adapt to the source emergency. The proposed planning method is applied to an IEGS with practical demands as a case study. The results show that the configuration generated by the two-level planning model can satisfy the daily reserve requirements for emergency failures, and the resilient scheduling strategy with storage reserve can improve the system resilience effectively.
31 citations
Cites background from "Day-Ahead Scheduling of Distributio..."
...Integrated electricity and gas community energy system (IEGS), whose energy sources are electricity and natural gas, can utilize the complementary characteristics of electricity and gas [5]; furthermore, it can realize high-efficiency operation through the coordination of energy conversion, storage and consumption [6], and has been widely developed....
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TL;DR: A three-stage state estimation model for the ac–dc hybrid distribution network integrating supervisory control and data acquisition system and phasor measurement unit is established, which ensures the convergence of distributed state estimation while improving computational efficiency.
Abstract: The ac–dc hybrid distribution network is a credible path for the future evolution of distribution network. State estimation is a paramount foundation for the safe and stable operation of the complex distribution network. The application of the centralized state estimation method in an ac–dc distribution network has some obstacles, such as low computational efficiency, large communication capacity, and privacy protection problem. Based on the three-stage state estimation theory, this paper established a three-stage state estimation model for the ac–dc hybrid distribution network integrating supervisory control and data acquisition system and phasor measurement unit. The proposed three-stage estimation model achieves linearization of the nonlinear state estimation for the ac–dc hybrid distribution network. That is, the first and third stages simply solve the linear state estimation problem, and the second stage is a one-step nonlinear transform. Moreover, the alternating direction method of multipliers (ADMM) is applied to solving the distributed problem. Thus, an accurate and efficient three-stage distributed state estimation method for the ac–dc hybrid distribution network is proposed. In this method, ac subsystems and dc subsystems execute state estimation tasks based on local information and eventually achieve the overall consistency of the system state estimation through the transfer iteration of the boundary information, respectively. The combination of bilinear theory and ADMM ensures the convergence of distributed state estimation while improving computational efficiency. The simulation results verified the advantage of the proposal over the existing methods in many aspects.
30 citations
Cites methods from "Day-Ahead Scheduling of Distributio..."
...As a decentralized optimization algorithm, alternating direction multiplier method (ADMM) is to make ‘‘hard constraint’’ relaxed into the objective function, so that the original problem is decomposed into multiple sub-problems for parallel solution [26]–[28]....
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TL;DR: In this article, a novel integrated electricity-gas system (IEGS) architecture with collaborative operation of power-to-gas (P2G), carbon capture system (CCS) and electric vehicles (EVs) is constructed.
Abstract: As the global warming crisis becomes increasingly serious, decarbonized integrated electricity-gas system (IEGS) which can reduce CO2 emissions are gradually developed. However, with high proportion of renewable energy access, the inherent randomness and volatility bring great difficulties to energy scheduling optimization of decarbonized IEGS. In this article, for reducing CO2 emissions, meanwhile improving the utilization efficiency of wind power, a novel IEGS architecture with collaborative operation of power-to-gas (P2G), carbon capture system (CCS) and electric vehicles (EVs) is constructed. P2G is operated in a refined model combined with H2 storage and captured CO2 by CCS can be further consumed in reaction of P2G. Besides, EVs are innovatively adopted in IEGS as flexible energy resource to reduce the impact of wind power fluctuations. Additionally, a multi-step day ahead-intraday collaborative optimization framework is proposed to handle with the uncertainty of wind power, more accurate predicted wind power can be adopted under this framework. The objective function of constructed IEGS is minimize the total operating costs, which takes the CO2 processing costs and penalty costs of wind power deviations into consideration. Numerical studies are conducted with different cases, with the constructed structure and proposed multi-step optimization framework, the emissions of CO2 can be efficiently reduced and wind power utilization can be significantly improved, the total operating costs of IEGS can be reduced more than 20% compared with other cases, which demonstrates that the research of this article has better economic benefits and environmental friendliness.
25 citations
References
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23 May 2011TL;DR: It is argued that the alternating direction method of multipliers is well suited to distributed convex optimization, and in particular to large-scale problems arising in statistics, machine learning, and related areas.
Abstract: Many problems of recent interest in statistics and machine learning can be posed in the framework of convex optimization. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be able to solve problems with a very large number of features or training examples. As a result, both the decentralized collection or storage of these datasets as well as accompanying distributed solution methods are either necessary or at least highly desirable. In this review, we argue that the alternating direction method of multipliers is well suited to distributed convex optimization, and in particular to large-scale problems arising in statistics, machine learning, and related areas. The method was developed in the 1970s, with roots in the 1950s, and is equivalent or closely related to many other algorithms, such as dual decomposition, the method of multipliers, Douglas–Rachford splitting, Spingarn's method of partial inverses, Dykstra's alternating projections, Bregman iterative algorithms for l1 problems, proximal methods, and others. After briefly surveying the theory and history of the algorithm, we discuss applications to a wide variety of statistical and machine learning problems of recent interest, including the lasso, sparse logistic regression, basis pursuit, covariance selection, support vector machines, and many others. We also discuss general distributed optimization, extensions to the nonconvex setting, and efficient implementation, including some details on distributed MPI and Hadoop MapReduce implementations.
17,433 citations
TL;DR: Accuracy analysis and the test results show that estimation methods can be used in searches to reconfigure a given system even if the system is not well compensated and reconfiguring involves load transfer between different substations.
Abstract: A general formulation of the feeder reconfiguration problem for loss reduction and load balancing is given, and a novel solution method is presented. The solution uses a search over different radial configurations created by considering switchings of the branch exchange type. To guide the search, two different power flow approximation methods with varying degrees of accuracy have been developed and tested. The methods are used to calculate the new power flow in the system after a branch exchange and they make use of the power flow equations developed for radial distribution systems. Both accuracy analysis and the test results show that estimation methods can be used in searches to reconfigure a given system even if the system is not well compensated and reconfiguring involves load transfer between different substations. For load balancing, a load balance index is defined and it is shown that the search and power flow estimation methods developed for power loss reduction can also be used for load balancing since the two problems are similar. >
3,985 citations
TL;DR: A computational study on a two-stage robust location-transportation problem shows that the column-and-constraint generation algorithm performs an order of magnitude faster than existing Benders-style cutting plane methods.
1,010 citations
"Day-Ahead Scheduling of Distributio..." refers methods in this paper
...Therefore, big-M method is used to handle this bilinear problem [42]....
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TL;DR: This paper considers accelerated variants of two common alternating direction methods: the alternating direction method of multipliers (ADMM) and the alternating minimization algorithm (AMA), of the form first proposed by Nesterov for gradient descent methods.
Abstract: Alternating direction methods are a common tool for general mathematical programming and optimization. These methods have become particularly important in the field of variational image processing, which frequently requires the minimization of nondifferentiable objectives. This paper considers accelerated (i.e., fast) variants of two common alternating direction methods: the alternating direction method of multipliers (ADMM) and the alternating minimization algorithm (AMA). The proposed acceleration is of the form first proposed by Nesterov for gradient descent methods. In the case that the objective function is strongly convex, global convergence bounds are provided for both classical and accelerated variants of the methods. Numerical examples are presented to demonstrate the superior performance of the fast methods for a wide variety of problems.
772 citations
"Day-Ahead Scheduling of Distributio..." refers methods in this paper
...And the fast-ADMM with restart algorithm use a restart rule can improve the stability of convergence rate [44]....
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TL;DR: A novel control strategy for coordinated operation of networked microgrids (MGs) in a distribution system considered as a stochastic bi-level problem with the DNO in the upper level and MGs in the lower level to achieve the equilibrium among all entities.
Abstract: This paper proposes a novel control strategy for coordinated operation of networked microgrids (MGs) in a distribution system. The distribution network operator (DNO) and each MG are considered as distinct entities with individual objectives to minimize the operation costs. It is assumed that both the dispatchable and nondispatchable distributed generators (DGs) exist in the networked MGs. In order to achieve the equilibrium among all entities and take into account the uncertainties of DG outputs, we formulate the problem as a stochastic bi-level problem with the DNO in the upper level and MGs in the lower level. Each level consists of two stages. The first stage is to determine base generation setpoints based on the load and nondispatchable DG output forecasts and the second stage is to adjust the generation outputs based on the realized scenarios. A scenario reduction method is applied to enhance a tradeoff between the accuracy of the solution and the computational burden. Case studies of a distribution system with multiple MGs of different types demonstrate the effectiveness of the proposed methodology. The centralized control, deterministic formulation, and stochastic formulation are also compared.
495 citations