It has been shown that the heating, ventilation, and air conditioning (HVAC) systems of commercial buildings can offer ancillary services to power systems without loss of comfort. In this paper, we propose a new control framework for reliable scheduling and provision of frequency reserves by aggregations of commercial buildings. The framework incorporates energy-constrained frequency signals, which are adopted by several transmission system operators for loads and storage devices. We use a hierarchical approach with three levels: (i) reserve capacities are allocated among buildings (e.g., on a daily basis) using techniques from robust optimization, (ii) a robust model predictive controller optimizes the HVAC system consumption typically every 30 minutes, and (iii) a feedback controller adjusts the consumption to provide reserves in real time. We demonstrate how the framework can be used to estimate the reserve capacities in simulations with typical Swiss office buildings and different reserve product characteristics. Our results show that an aggregation of approximately 100 buildings suffices to meet the 5 MW minimum bid size of the Swiss reserve market.

No abstract

Load demand in small autonomous island systems is typically covered by Diesel Units (DU). Although a favourable renewable energy source (RES) potential might exist, the technical constraints introduced by the conventional generators result in relatively low RES penetration levels, typically up to 15%-20% of the annual energy demand. To overcome such limitations, introduction of energy storage is necessary. In the case of very small islands (less than 1 MW peak load), lead-acid battery energy storage systems (BESS) constitute a technically mature solution with considerable application potential. In this paper, the potential for achieving very high RES penetration levels with the introduction of BESS in an existing small island system is investigated. An operating policy is first introduced for the overall system, including conventional generators, RES (wind and photovoltaic) stations and storage system. Simulation results are then presented to quantify the expected energy benefits in terms of RES energy penetration and the impact on the economics of the island system. The sizing of the hybrid system components is then investigated by conducting a parametric analysis and then optimized by applying genetic algorithms.

In this paper, the Unit Commitment (UC) problem in a power network with low levels of rotational inertia is studied. Frequency-related constraints, namely the limitation on Rate-of-Change-of-Frequency (RoCoF), frequency nadir and steady-state frequency error, are derived from a uniform system frequency response model and included into a stochastic UC that accounts for wind power and equipment contingency uncertainties using a scenario-tree approach. In contrast to the linear RoCoF and steady-state frequency error constraints, the nadir constraint is highly nonlinear. To preserve the mixed-integer linear formulation of the stochastic UC model, we propose a computationally efficient approach that allows to recast the nadir constraint by introducing appropriate bounds on relevant decision variables of the UC model. For medium-sized networks, this method is shown to be computationally more efficient than a piece-wise linearization method adapted from the literature. Simulation results for a modified IEEE RTS-96 system revealed that the inclusion of inertia-related constraints significantly influences the UC decisions and increases total costs, as more synchronous machines are forced to be online to provide inertial response.

No abstract

A large-scale integration of renewable generation,usually interfaced to the network through power electronics,has led to an overall decrease in power system inertia. This paper presents novel insights on the fundamental stability properties of such systems. For that purpose, a uniform set of Differential-Algebraic Equations (DAEs) describing a generic,low-inertia power system has been developed. A full-order, state-of-the-art control scheme of both synchronous and converter-based generators are included, with the latter differentiating between the grid-forming and grid-following mode of operation. Furthermore, the dynamics of transmission lines and loads are captured in the model. Using modal analysis techniques such as participation factors and parameter sensitivity, we determine the most vulnerable segments of the system and investigate the adverse effects of the underlying control interference. Finally, the appropriate directions for improving the system stability margin under different generation portfolios have been proposed.

This paper is the first part of a two-part series in which we present results from an experimental demonstration of frequency regulation in a commercial building test facility.In Part I, we introduce the test facility and develop relevant building models. Furthermore, we design a hierarchical controller that consists of three levels: a reserve scheduler, a building climate controller, and a fan speed controller for frequency regulation. We formulate the reserve scheduler as a robust optimization problem and introduce several approximations to reduce its complexity. The building climate controller is comprised of a robust model predictive controller and a Kalman filter. The frequency regulation controller consists of a feedback and a feedforward loop, provides fast responses, and is stable.Part I presents building model identification and controller tuning results, whereas Part II reports results from the operation of the hierarchical controller under frequency regulation.

This paper is the second part of a two-part series presenting the results from an experimental demonstration of frequency regulation in a commercial building test facility. In Part I, we developed relevant building models and designed a hierarchical controller for reserve scheduling, building climate control and frequency regulation.In Part II, we introduce the communication architecture and experiment settings, and present extensive experimental results under frequency regulation. More specifically, we compute the day-ahead reserve capacity of the test facility under different assumptions and conditions. Furthermore, we demonstrate the ability of model predictive control to satisfy comfort constraints under frequency regulation, and show that fan speed control can track the fast-moving RegD signal of the Pennsylvania, Jersey, and Maryland Power Market (PJM) very accurately. In addition, we report the observed effects of frequency regulation on building control and provide suggestions for realworld implementation projects. Our results show that hierarchical control is appropriate for frequency regulation from commercial buildings.