Matthias A. Bucher

A framework for and assessment of demand response and energy storage in power systems

The shift in the electricity industry from regulated monopolies to competitive markets as well as the widespread introduction of fluctuating renewable energy sources bring new challenges to power systems. Some of these challenges can be mitigated by using demand response (DR) and energy storage to provide power system services. The aim of this paper is to provide a unified framework that allows us to assess different types of DR and energy storage resources and determine which resources are best suited to which services. We focus on four resources: batteries, plug-in electric vehicles, commercial buildings, and thermostatically controlled loads. We define generic power system services in order to assess the resources. The contribution of the paper is threefold: (i) the development of a framework for assessing DR and energy storage resources; (ii) a detailed analysis of the four resources in terms of ability for providing power system services, and (iii) a comparison of the resources, including an example case for Switzerland. We find that the ability of resources to provide power system services varies largely and also depends on the implementation scenario. Generally, there is large potential to use DR and energy storage for providing power system services, but there are also challenges to be addressed, for example, adequate compensation, privacy, guaranteeing costumer service, etc.

Managing Flexibility in Multi-Area Power Systems

In this paper we present a framework to efficiently characterize the available operational flexibility in a multi-area power system. We focus on the available reserves and the tie-line flows. The proposed approach is an alternative to the current calculation of the available transfer capacity (ATC), as it considers location and availability of reserves, transmission constraints, and interdependencies of tie-line flows between different areas, while it takes into account the N-1 security criterion. The method is based on computational geometry using polytopic projections. It requires only a limited amount of information exchange and does not need central coordination. The method has two versions: a passive approach, and an active approach where neighboring areas can share reserves. In that respect we also introduce the term “exportable flexibility”. Case studies demonstrate the improved tie-line utilization, especially if reserves are shared, and the visualization benefits.

Robust Corrective Control Measures in Power Systems With Dynamic Line Rating

The increasing injections of energy from renewable energy sources far away from load centers have resulted in a more congested transmission grid. As the construction of new lines is costly, other options should be exploited as well. One possible solution is dynamic thermal line rating (DLR), which, instead of static thermal line rating, adapts the transmission capacity based on the expected weather conditions. This results, on average, in higher transmission capacities. First pilot projects have proven its efficiency. This paper analyzes the potential of DLR and demonstrates how DLR can be integrated in a dispatch optimization while managing possible errors in the forecasts of the line ratings with two different approaches. Both approaches result in robust optimization problems and guarantee that there is a suitable remedial action for all realizations of forecast errors given by uncertainty sets. The first approach relies on corrective control actions that are calculated centrally, once the actual line rating is known. The second approach relies on affine policies, which directly relate the current line rating to corrective control measures. This approach can be deployed in a decentralized manner. In case studies, the two approaches are applied and the reduction of overall operational costs is investigated exemplarily as a function of the forecast accuracy.

Probabilistic N−1 security assessment incorporating dynamic line ratings

As power systems are operated closer to their technical limits, dynamic thermal line rating (DLR) can be used to enable additional dispatching flexibility. DLR is used to dynamically adapt the ampacity of the conductors, i.e. the maximum allowed amount of current a conductor can carry without overheating, according to the meteorological conditions. This paper proposes a probabilistic N-1 security assessment method that incorporates DLR in a probabilistic constraint. To model the probability distributions of certain meteorological values we use a copula approach. We calculate the distribution of the ampacity based on the distributions of the meteorological quantities using a model of the thermal behaviour of the line and given weather forecasts. From the resulting distribution, uncertainty realizations are sampled which are needed for a scenario based methodology which is used to deal with the developed chance constraint program.

Risk-averse medium-term hydro optimization considering provision of spinning reserves

This paper presents two algorithms for solving a medium-term hydro optimization. Considered are risk-averse operation, provision of spinning reserves as well as short-term production flexibility. Proposed is a variant of stochastic dual dynamic programming (SDDP) and stochastic dynamic programming as a benchmark. A risk measure is introduced in both methods. To deal with short-term production flexibility a decomposition of the problem into inter- and intrastage subproblems is performed. The provision of spinning reserves leads to non-convex value functions. To deal with it in SDDP a method based on Lagrangian relaxation was used which was further enhanced by locally valid cuts in order to find realistic water values.

On quantification of flexibility in power systems

Large scale integration of fluctuating and non-dispatchable generation and variable transmission patterns induce high uncertainty in power system operation. In turn, transmission system operators (TSOs) need explicit information about available flexibility to maintain a desired reliability level at a reasonable cost. In this paper, locational flexibility is defined and a unified framework to compare it against forecast uncertainty is introduced. Both metrics are expressed in terms of ramping rate, power and energy and consider the network constraints. This framework is integrated into the operational practice of the TSO using a robust reserve procurement strategy which guarantees optimal system response in the worst-case realization of the uncertainty. The proposed procurement model is applied on an illustrative three-node system and a case study focuses on the available locational flexibility in a larger power system.

Assessment of capacity factor and dispatch flexibility of concentrated solar power units

One of the key challenges for an effective grid integration of renewable energy sources (RES) is their fluctuating power infeed. With thermal energy storage (TES) a concentrated solar power (CSP) plant has the possibility to shift the production to times when energy is needed or level out the infeed. To evaluate these dispatch possibilities, a CSP plant model is needed. In this paper, a non-linear model and a linearised model of a CSP plant with parabolic through technology are introduced. Both models are linked and used for sensitivity analyses of the sizes of the solar field and TES. The Power Nodes framework, which has been developed to model generic power system devices, will be used. A Power Node representation of a CSP plant is introduced, enabling the Power Nodes framework to use not only electrical, but also thermal Power Nodes. Using this CSP Power Node model in combination with a predictive dispatch procedure, capacity factors and normalized load covering are calculated for numerous CSP plant configurations via full-year simulations. CSP plant capacity factors between 45% and 72% were achieved. Constant load profiles could be covered by up to 95%. A residual load profile, scaled to the maximum generation capacity of the CSP plant, was covered up to 80% of the plant generation.

Modeling and economic evaluation of Power2Gas technology using energy hub concept

A major challenge in power system operation is the integration of renewable energy in-feed in large scale. Due to the fluctuating nature and seasonal dependency of these energy carriers, excess energy might be curtailed and shortfalls are covered by conventional generation units, since it is possible that sufficient storage capacities are not always available. In this paper we focus on the Power-to-Gas technology as an additional source for enhancing power system operability. Power-to-Gas converts electrical energy into hydrogen or methane, which can be stored or transported via the existing natural gas infrastructure. A major concern is whether this technology is economically valid. In order to address this issue, we propose a model based on the energy hub concept and apply it to historic data. In a simulation study we show, that currently a power-to-gas plant is not economically viable.

On wind farm operation with third-party storage

A major challenge in power system operation is the integration of renewable energy in-feed in large scale. Currently, the responsibility to cope with uncertainty in power injection is transferred to a central authority, i.e. the system operator, while renewable energy in-feed is supported via a tariff system. In this paper we propose market participation of wind farms in combination with a third-party energy storage. A novel concept of storage capacity reservation is presented, where the wind power producer hedges unfavorable wind power realizations with a third-party storage. In a day-ahead scheduling stage, profit maximizing bids for the day-ahead market are stated incorporating costs of storage reservation. During an intra-day stage, the storage device backs up the wind power producer by tracking its day-ahead market bids. In a simulation study we show that after the consideration of the costs of storage reservations and storage operation, the proposed model can lead to profitable operation of wind power plants while reducing the profit variability.

Balancing reserve procurement and operation in the presence of uncertainty and transmission limits

With the ongoing changes in the European electricity production portfolio towards more renewable energy sources, the dispatch flexibility has decreased and operational uncertainty, due to intermittent generation has increased. At the same time, the grid infrastructure is operated at its limits. This leads to an increased risk of contingencies. As investments in new grid infrastructure is often a tedious process, methods to improve the usage of the existing infrastructure are of importance. In this paper we present an approach for the procurement and operation of manually activated control reserves, such as tertiary control reserves, also considering HVDC interconnections. We formulate probabilistic power flows based on PTDF and correlated distributions of intermittent infeeds and quantify the operational flexibility needs for every transmission line. The proposed methods consider these flexibility needs and procure and operate the reserves and HVDC connections accordingly. The efficacy of the methodology is demonstrated in case studies and it is shown, that the risk of contingencies is reduced.