Review of energy storage system for wind power integration support

Advances and trends of energy storage technology in Microgrid

Congestion management in competitive power market : A bibliographical survey

Demand side management (DSM) can be defined as modifications in the demand side energy consumption pattern to foster better efficiency and operations in electrical energy systems. DSM activities, which are classified into “energy efficiency (EE)” and “demand response (DR)” are becoming more popular due to technological advances in smart grids and electricity market deregulation. However, it can be argued that ensuring DSM sustainability requires creating suitable business models. Business models are influenced by different factors such as electricity market regulation, mechanisms, power system characteristics and infrastructure. The proliferation of smart grid infrastructure, distributed generation, intermittent renewable energy resources and energy storage devices has affected DSM business models considerably. Therefore, in this paper, possible business models for EE and DR providers in different electricity market segments are analyzed and reviewed. The analysis covers three types of characteristics: DSM transaction characteristics, renewable energy correlation and DSM load control characteristics. In DSM transaction characteristics, the value proposition of DSM such as added value offered to the DSM purchaser and transaction triggers are discussed. In renewable energy correlation, the effect of increased renewable energy penetration on the business model is evaluated. In DSM load control characteristics, load control and aggregation aspects such as response speed, duration, advance notice, location sensitivity and actual usage frequency are analyzed.

A review of demand side management business models in the electricity market

A methodology on the design of a wind farm battery energy storage system to realize power dispatchability is described. Based on the statistical long-term wind speed data captured at the farm, a dispatch strategy is proposed which allows the battery capacity to be determined so as to maximize a defined service lifetime/unit cost index of the energy storage system. Also, the application of the dispatch strategy is shown to yield the short-term wind farm output power schedule which meets the specified confidence level of power delivery commitment.

On the Determination of Battery Energy Storage Capacity and Short-Term Power Dispatch of a Wind Farm

The liberalization of the electric energy market changes the tasks of power network planning as well as of network operation into multi-criteria optimization problems. In this paper two different Pareto-based optimization techniques are presented, which are suitable for this kind of problems.

Multi-criteria optimization methods for planning and operation of electrical energy systems

This paper presents a new approach of congestion management with network based measures, market based measures and generation management in wind farms for transmission system with large scale integration of wind energy. The congestion management problem is solved using a genetic algorithm based approach, that enables to combine network based measures, market based measures and generation management in order to avoid congestions. In doing so, the power system requirements are assessed with network security algorithms like the ACload flow calculations for the base case, the (n-1)-security calculations or the short circuit calculations. Additionally to the mentioned possibilities of congestion management, the paper presents an approach of energy management using energy storage systems to enhance the collaboration between wind farm operators and TSO in order avoid congestions on the grid.

Congestion management in transmission systems with large scale integration of wind energy

This paper presents a congestion management system (CMS) based on corrective measures. In an unbundled power system, the schedules of the generation units and of the demands are given to the transmission system operator who has to realize them. This may cause multiple congested conditions, which can be eliminated by the following corrective measures: adjustment of the network elements like transformer taps or shunt elements, corrective switching, corrective redispatch of generation. The aim of the CMS is to specify a state of the transmission system, which represents an undisturbed state and enables all schedules. The search for a state of the transmission system, which fulfills these requirements, represents a mixed-integer-nonlinear-problem, which cannot be described in an analytical way. Particularly the topology changes generate a problem of large dimension. The paper presents the mathematical model representing a CMS to formulate an optimization problem and gives exemplary study results. The described problem is solved by an evolution strategy.

Congestion management in a deregulated environment using corrective measures

Wind energy is one of the most popular sources for renewable energy. Worldwide, but especially in Germany, an extensive growth of installed wind energy plants can be traced. In Germany, the installed power of wind energy plants in 2007 was about 22 GW. The aim of the government is to raise this amount to 47 GW to the year 2020, what will be equal to 60 % of the total load of Germany. One problem is that some large conventional power plants have to shut down because of the priority feed in of wind energy, so problems concerning grid stability may appear. A contribution to the grid stability is control power, which is today supplied from conventional power plants or storage units. At the moment, wind energy plants have not the duty to support the grid stability, but it is unavoidable they have to do it already in near future. This work shows on the one side the technical possibility of wind energy plants to supply control power and on the other side the possible economical benefit. First it is demonstrated, that both types of today's wind generators (double-fed induction generator, synchronous generator) are able to supply positive and negative control power to the grid. To enhance the ability to support the grid with control power and also to increase the revenues of the wind park owner, an energy storage unit is combined with the wind farm. At the moment, the supplied wind energy is paid with a fix amount of money according to governmental directives, independent of day-time, grid load or conventional energy prices. In the future this system has to be rejected and an open competition of renewables energy sources to conventional power plants will take place. One option is to take part at the market of ancillary services and here especially at the control power market. In this work, the generated energy by the wind farm is sold to different sources depending on an optimization using mixed integer linear programming, which also takes into account the technical limitations of the modeled system. Various scenarios show the results of participating at the control power and also the difference between using a storage unit to support the system.

Wind farms with energy storages integrated at the control power market

This paper addresses the problem of optimal operation planning of industrial power systems (IPS) considering the enhanced opportunities due to the liberalized energy markets. Therefore, the IPS is considered as an independent power producer particularly taking into account: the economic and technical assessment of spot energy transactions, the operational restrictions of combined heat and power (CHP) plants which can frequently be found in IPS, and the application of methods of industrial load management. The mathematical model representing IPS to formulate the optimization problem is presented and exemplary case study results are given.

http://ieeexplore.ieee.org/iel5/6967/18766/00867350.pdf

J.F. Verstege

Papers

Multi-criteria optimization methods for planning and operation of electrical energy systems

Congestion management in transmission systems with large scale integration of wind energy

Congestion management in a deregulated environment using corrective measures

Wind farms with energy storages integrated at the control power market

Assessing industrial load management in liberalized energy markets