Energy management means to optimize one of the most complex and important technical creations that we know: the energy system. While there is plenty of experience in optimizing energy generation and distribution, it is the demand side that receives increasing attention by research and industry. Demand Side Management (DSM) is a portfolio of measures to improve the energy system at the side of consumption. It ranges from improving energy efficiency by using better materials, over smart energy tariffs with incentives for certain consumption patterns, up to sophisticated real-time control of distributed energy resources. This paper gives an overview and a taxonomy for DSM, analyzes the various types of DSM, and gives an outlook on the latest demonstration projects in this domain.

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Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads

We explore in this chapter questions of existence and uniqueness for solutions to stochastic differential equations and offer a study of their properties. This endeavor is really a study of diffusion processes. Loosely speaking, the term diffusion is attributed to a Markov process which has continuous sample paths and can be characterized in terms of its infinitesimal generator.

Stochastic Differential Equations

(1990). ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY. Electric Machines & Power Systems: Vol. 18, No. 2, pp. 209-210.

Energy function analysis for power system stability

Doubly fed induction generators (DFIGs), often organized in wind parks, are the most important generators used for variable-speed wind energy generation. This paper reviews the control systems for the operation of DFIGs and brushless DFIGs in wind energy applications. Control systems for stand-alone operation, connection to balanced or unbalanced grids, sensorless control, and frequency support from DFIGs and low-voltage ride-through issues are discussed.

Overview of Control Systems for the Operation of DFIGs in Wind Energy Applications

This article provides a survey on state estimation (SE) in electric power grids and examines the impact on SE of the technological changes being proposed as a part of the smart grid development. Although SE at the transmission level has a long history, further research and development of innovative SE schemes, including those for distribution systems, are needed to meet the new challenges presented by the requirements of the future grid. This article also presents some example topics that signal processing (SP) research can contribute to help meet those challenges.

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State Estimation in Electric Power Grids: Meeting New Challenges Presented by the Requirements of the Future Grid

This paper presents a solution of optimal power flow (OPF) incorporating wind power. A paradigm for modeling the cost of wind-generated electricity from a wind farm is proposed. Based on the Weibull wind speed distribution and wind turbine model represented by function approximation, the frequency distribution of wind farm power output to be the basis for modeling wind generation cost is established via applying Monte Carlo simulation. The proposed wind generation cost model consists of the opportunity cost of wind power shortage and the opportunity cost of wind power surplus, which reflect the cost of dispatching additional reserve capacity and the cost of environmental benefit loss, respectively, and it is integrated into the conventional OPF program. Furthermore, the small signal stability constraints are considered simultaneously as well during optimization. A self-adaptive evolutionary programming method is employed to solve the OPF with wind power involved. A case study is conducted based on the IEEE New England test system (10-Generator-39-Bus) as a benchmark. The simulation results demonstrate the effectiveness and validity of the proposed model and method.

Optimal Power Flow Solution Incorporating Wind Power

Multi-terminal HVDC transmission system technology using voltage source converters is proposed for integrating large offshore wind farms. Various DC grid management strategies based on coordinated close-loop DC voltage control and DC droop characteristics are proposed, to ensure smooth system operation and proper power sharing among various onshore AC networks. PSCAD/EMTDC simulations for a four-terminal DC system for connecting two offshore wind farms to two different onshore AC networks are presented to demonstrate the robust performance of the proposed DC management modes during wind speed and power variations, and large disturbances caused by the trip of one of the wind farms.

DC grid management of a multi-terminal HVDC transmission system for large offshore wind farms

To describe the impact of uncertainties, such as fluctuation of bus loads and intermittent behavior of renewable generations, on the available load supply capability (ALSC) of distribution system accurately and comprehensively, this paper defines a series of meaningful indices for the probabilistic evaluation of ALSC. An efficient simulation method, Latin hypercube sampling-based Monte Carlo simulation (LHS-MCS), combined with step-varied repeated power flow method is proposed to compute the defined indices. Compared with simple random sampling-based Monte Carlo simulation (SRS-MCS), LHS-MCS is found to be more suitable for the probabilistic evaluation of ALSC. It can achieve more accurate and stable ALSC indices under relatively small sample sizes. The calculation speed of LHS-MCS is comparable with that of SRS-MCS under the same sample sizes, and the required CPU time of LHS-MCS is far less than SRS-MCS under the same calculation accuracy. Case studies carried out on the modified Baran & Wu 33-bus and the modified IEEE 123-bus distribution systems verify the feasibility of the defined indices and high performance of the proposed method.

Probabilistic Evaluation of Available Load Supply Capability for Distribution System

This paper proposes a novel integration of wind farm energy storage (ES) systems within microgrids. The main feature of the method is that the voltage and frequency control of the microgrid is shared by the wind generators through droop characteristics. Therefore, the control structure is suitable when the wind generators supply significant part of the load. The paper modifies the standard droop method in order to force the generators to share the load according to their available wind power and not just the generator rating. The paper focuses on islanded microgrid application; however, the method is applicable when there is a controlled connection to the main grid via a power converter, and also for HVDC connection. The proposed control methods are derived for doubly-fed induction generators (DFIGs) and validated using PSCAD/EMTDC simulations. The ride-through in case of a 3-phase fault on the local grid will also be simulated.

Novel Integration of Wind Generator-Energy Storage Systems Within Microgrids

The transient stability analysis incorporating wind power intermittency and volatility is studied in this study. The wind turbines with doubly fed induction generator (DFIG) and direct-driven permanent magnet synchronous generator (PMSG) are considered, respectively, during analysis. In modelling of DFIG and PMSG, the default GE wind turbine model and the Western Electricity Coordinating Council generic wind turbine model are employed, respectively. Based on the Jensen model, which is applied to describe the wake effect in a wind farm located on flat terrain, an equivalent simplified model of a wind farm is established regarding wind farm layout. On the basis of the built wind farm model, the Monte Carlo simulation technique combined with two evaluation indices, namely angle-based margin index and critical clearing time (CCT) is applied on the IEEE 10-generator-39-bus test system and a real-sized China-Jiangxi power grid as a benchmark to exploit and explore the effects of wind power intermittency and volatility on power system transient stability. The frequency distributions of transient stability evaluation index, CCT, probability of system transient instability and the range of wind speeds causing system transient instability are simulated. In addition, the influence of wake effect on transient stability is discussed as well.

Masoud Bazargan

Papers

Optimal Power Flow Solution Incorporating Wind Power

DC grid management of a multi-terminal HVDC transmission system for large offshore wind farms

Probabilistic Evaluation of Available Load Supply Capability for Distribution System

Novel Integration of Wind Generator-Energy Storage Systems Within Microgrids

Effects of wind generation intermittency and volatility on power system transient stability