计量经济分析 = Econometric analysis

Introduction to stochastic programming

Transition to a sustainable energy environment results in aggregated generator and load dynamics in the distribution network. State estimation is a key function in building adequate network models for online monitoring and analyzes. The requirements of distribution system state estimation (DSSE) is becoming stringent because of the needs of new system modeling and operation practices associated with integration of distributed energy resources and the adoption of advanced technologies in distribution network. This paper summarizes the state-of-the-art technology, major hurdles, and challenges in DSSE development. The opportunities, paradigm shift, and future research directions that could facilitate the need of DSSE are discussed.

A Review on Distribution System State Estimation

The increasing penetration of renewable energy sources (RES) in power systems intensifies the need of enhancing the flexibility in grid operations in order to accommodate the uncertain power output of the leading RES such as wind and solar generation. Utilities have been recently showing increasing interest in developing Demand Response (DR) programs in order to match generation and demand in a more efficient way. Incentive- and price-based DR programs aim at enabling the demand side in order to achieve a range of operational and economic advantages, towards developing a more sustainable power system structure. The contribution of the presented study is twofold. First, a complete and up-to-date overview of DR enabling technologies, programs and consumer response types is presented. Furthermore, the benefits and the drivers that have motivated the adoption of DR programs, as well as the barriers that may hinder their further development, are thoroughly discussed. Second, the international DR status quo is identified by extensively reviewing existing programs in different regions.

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An overview of Demand Response: Key-elements and international experience

Distribution System Modeling and Analysis

Phasor measurement units (PMUs) are rapidly being deployed in electric power networks across the globe. Wide-area measurement system (WAMS), which builds upon PMUs and fast communication links, is consequently emerging as an advanced monitoring and control infrastructure. Rapid adaptation of such devices and technologies has led the researchers to investigate multitude of challenges and pursue opportunities in synchrophasor measurement technology, PMU structural design, PMU placement, miscellaneous applications of PMU from local perspectives, and various WAMS functionalities from the system perspective. Relevant research articles appeared in the IEEE and IET publications from 1983 through 2014 are rigorously surveyed in this paper to represent a panorama of research progress lines. This bibliography will aid academic researchers and practicing engineers in adopting appropriate topics and will stimulate utilities toward development and implementation of software packages.

Synchrophasor Measurement Technology in Power Systems: Panorama and State-of-the-Art

Demand response enabled by time-varying prices can propel the power industry toward a greater efficiency. However, a noncoordinated response of customers may lead to severe peak rebounds at periods with lower prices. In this regard, a coordinated demand response scheme can mitigate concerns about the peak rebounds. This paper presents a system-wide demand response management model to coordinate demand response provided by residential customers. The objective of the model is to flatten the total load profile that is subject to minimum individual cost of customers. The model is first formulated as a bi-level optimization problem. It is then casted into equivalent single-level problems, which are solved via an iterative distributed algorithm. Home load management (HLM) modules embedded in customers' smart meters are autonomous agents associated with the algorithm. In the algorithm, at first, HLM modules, in response to prices announced by the utility, optimize the daily operation of household appliances and send back the scheduled load profiles. Then, the total load profile is calculated and released by the utility. Thereafter, the HLM modules asynchronously update their schedule such that, given their least energy expenses, the most evenly distributed total load profile is achieved. The mutual interaction between the utility and HLM modules is continued to the point in which no further improvement is obtained. Convergence and optimality of the algorithm are proved.

A Distributed Algorithm for Managing Residential Demand Response in Smart Grids

Proliferation of renewable energy resources in distribution networks has captured distribution companies' attention towards more active management tools. Thanks to the smart grid paradigm, hourly network reconfiguration, which is still among immature ideas, can bring the activeness required to handle fluctuating output of renewable resources. The aim of this study is to analyze the worthiness of the hourly reconfiguration in the presence of renewable energy resources. For doing so, a mathematical model is devised to minimize daily network losses via applying hourly reconfigurations. The model is a mixed integer second-order cone programming problem and is solved via MOSEK solver. The electrical demand variations as well as renewable power generation fluctuations during a day are taken into account. The proposed method is applied to the Baran 33-bus system and the results including a great deal of sensitivity analyses on key parameters are presented and discussed.

Value of Distribution Network Reconfiguration in Presence of Renewable Energy Resources

Despite of the great focus of attention dedicated to demand response (DR), the potential benefits of DR on distribution networks have not yet been quantitatively studied. This paper aims to assess DR potential impacts on major attributes of the operation of a residential distribution network. For doing so, grossly metered usage of more than 1600 residential consumers from Kainuu, Finland, is disaggregated to appliance-level load profiles. The flexibility of the load profiles is also estimated from the survey data and questionnaires. The individual profiles are then adjusted within their flexibility such that the most evenly distributed aggregated load profile is realized. Finally, the resulted load profile is applied to a Finnish distribution network, and the impacts of the DR on different aspects of the network operation such as the network losses, voltage profiles, and service reliability are studied. The observations certified significant benefits of the DR potentials for the network operation and reliability. It is also revealed that almost all of the benefits can be achieved by enabling the potential of responsive heating and ventilation systems.

Benefits of Demand Response on Operation of Distribution Networks: A Case Study

Severe peak rebounds are likely in absence of a system-wide coordination among customers participating in demand response programs. This paper aims to establish a decentralized system-wide framework to coordinate demand response of residential customers in a smart grid. The objective of the framework is to modify system load profile provided that customers’ payments are minimized, and their comfort and privacy are preserved. Home load management (HLM) modules, embedded in customers’ smart meters are autonomous agents of the framework. The energy service provider iteratively exchanges load information with HLM modules in the hope of achieving his desired load profile. In each iteration, the service provider announces system load profile to HLM modules. The modules, keeping in mind their own financial and comfort constraints, nonsequentially send back load reschedule proposals to modify system load profile. The received proposals are judged whether they improve system load profile or not. HLM modules with accepted proposals apply their proposed schedules. The modified system load profile is then released, and HLM modules’ new proposals are gathered and judged. This procedure is repeated to the point at which no further improvement in the system load profile can be experienced. Performance of the framework is shown by applying it to a system with 50 customers.

Amir Safdarian

Papers

Synchrophasor Measurement Technology in Power Systems: Panorama and State-of-the-Art

A Distributed Algorithm for Managing Residential Demand Response in Smart Grids

Value of Distribution Network Reconfiguration in Presence of Renewable Energy Resources

Benefits of Demand Response on Operation of Distribution Networks: A Case Study

Optimal Residential Load Management in Smart Grids: A Decentralized Framework