Andreas Ulbig

Reducing peak electricity demand in building climate control using real-time pricing and model predictive control

A method to reduce peak electricity demand in building climate control by using real-time electricity pricing and applying model predictive control (MPC) is investigated. We propose to use a newly developed time-varying, hourly-based electricity tariff for end-consumers, that has been designed to truly reflect marginal costs of electricity provision, based on spot market prices as well as on electricity grid load levels, which is directly incorporated into the MPC cost function. Since this electricity tariff is only available for a limited time window into the future we use least-squares support vector machines for electricity tariff price forecasting and thus provide the MPC controller with the necessary estimated time-varying costs for the whole prediction horizon. In the given context, the hourly pricing provides an economic incentive for a building controller to react sensitively with respect to high spot market electricity prices and high grid loading, respectively. Within the proposed tariff regime, grid-friendly behaviour is rewarded. It can be shown that peak electricity demand of buildings can be significantly reduced. The here presented study is an example for the successful implementation of demand response (DR) in the field of building climate control.

Unified System-Level Modeling of Intermittent Renewable Energy Sources and Energy Storage for Power System Operation

The system-level consideration of intermittent renewable energy sources (RES) and small-scale energy storage in power systems remains a challenge as either type is incompatible with traditional operation concepts. Noncontrollability and energy constraints are still considered contingent cases in market-based operation. The design of operation strategies for up to 100% RES power systems requires an explicit consideration of nondispatchable generation and storage capacities, as well as the evaluation of operational performance in terms of energy efficiency, reliability, environmental impact, and cost. By abstracting from technology-dependent and physical unit properties, the power nodes modeling framework presented here allows the representation of a technologically diverse unit portfolio with a unified approach, while establishing the feasibility of energy-storage consideration in power system operation. After introducing the modeling approach, a case study is presented for illustration.

Impact of Low Rotational Inertia on Power System Stability and Operation

Abstract Large-scale deployment of Renewable Energy Sources (RES) has led to significant generation shares of variable RES in power systems worldwide. RES units, notably inverter-connected wind turbines and photovoltaics (PV) that as such do not provide rotational inertia, are effectively displacing conventional generators and their rotating machinery. The traditional assumption that grid inertia is sufficiently high with only small variations over time is thus not valid for power systems with high RES shares. This has implications for frequency dynamics and power system stability and operation. Frequency dynamics are faster in power systems with low rotational inertia, making frequency control and power system operation more challenging. This paper investigates the impact of low rotational inertia on power system stability and operation, contributes new analysis insights and offers impact mitigation options.

Energy storage in power system operation: The power nodes modeling framework

A novel concept for system-level consideration of energy storage in power grids with dispatchable and non-dispatchable generators and loads is presented. Grid-relevant aspects such as power ratings, ramp-rate constraints, efficiencies, and storage capacities of the interconnected units are modeled, while technology-dependent and physical unit properties are abstracted from. This allows the modeling of a technologically diverse unit portfolio with a unified approach. The concept can be used for designing operation strategies for power systems, especially in the presence of non-dispatchable generation and significant storage capacities, as well as for the evaluation of operational performance in terms of energy efficiency, reliability, environmental impact, and cost. After introducing the modeling approach and a taxonomy of unit types, a simulation example is presented for illustration.

On operational flexibility in power systems

Operational flexibility is an important property of electric power systems. The term flexibility is widely used in the context of power systems although at times without a proper definition. The role of operational flexibility for the transition of existing power systems, many of them based on fossil fuels, towards power systems effectively accommodating high shares of variable Renewable Energy Sources (RES) has been widely recognized. Availability of sufficient operational flexibility is a necessary precondition for the grid integration of large shares of power in-feed from variable RES, for example wind power and photovoltaics (PV). The paper analyzes the role of operational flexibility in power systems. Necessary flexibility metrics for categorizing different types of operational flexibility are discussed. A new methodology for assessing the technically available operational flexibility is presented. Qualitative insights are derived, notably regarding the limits of RES integration for a given power system with its specific flexibility properties. An extensive simulation study is performed, assessing the role that operational flexibility has for the mitigation of challenges, namely curtailment, arising from high shares of variable RES in-feed.

Power and energy capacity requirements of storages providing frequency control reserves

Due to their fast response time and high ramp rates, storage systems are capable of providing frequency control reserves. However, the limit in energy capacity poses difficulties as frequency control signals are not unbiased. We describe a scheme to recharge or discharge the storage without impeding the quality of the provided service, and formulate an analyzing method to investigate the resulting size of the storage. We show that even small storage sizes are sufficient to provide continuous and reliable primary and secondary frequency control reserves to the grid.

Defining a degradation cost function for optimal control of a battery energy storage system

Optimal control of Battery Energy Storage Systems (BESSs) is challenging because it needs to consider benefits arising in power system operation as well as cost induced from BESS commitment. The presented approach relies on the methodology of Model Predictive Control (MPC) for optimal BESS operation. Variable and strongly usage dependent battery degradation costs constitute the bulk of the marginal costs for BESS operation. Battery degradation is usually modeled with nonlinear functional dependencies or an implicit cycle counting approach unsuited for an MPC implementation. In this paper an explicit cost function considering battery degradation is developed, which sufficiently captures the nonlinearities and is applicable for arbitrary battery load patterns. The resulting piece-wise affine cost function leads to a mixed-integer quadratic programming problem allowing a standard hybrid MPC formulation. As proof-of-concept, a peak shaving algorithm relying on the proposed cost function and on adaptive soft limits is developed and implemented on the Zurich 1MW BESS demonstration project, owned and operated by the utility of the Canton of Zurich (EKZ).

Modeling of Lithium-Ion Battery Degradation for Cell Life Assessment

Rechargeable lithium-ion batteries are promising candidates for building grid-level storage systems because of their high energy and power density, low discharge rate, and decreasing cost. A vital aspect in energy storage planning and operations is to accurately model the aging cost of battery cells, especially in irregular cycling operations. This paper proposes a semi-empirical lithium-ion battery degradation model that assesses battery cell life loss from operating profiles. We formulate the model by combining fundamental theories of battery degradation and our observations in battery aging test results. The model is adaptable to different types of lithium-ion batteries, and methods for tuning the model coefficients based on manufacturer’s data are presented. A cycle-counting method is incorporated to identify stress cycles from irregular operations, allowing the degradation model to be applied to any battery energy storage (BES) applications. The usefulness of this model is demonstrated through an assessment of the degradation that a BES would incur by providing frequency control in the PJM regulation market.

General frequency control with aggregated control reserve capacity from time-varying sources: The case of PHEVs

Herein, the concept of an ancillary service manager is developed for the provision of additional control reserve capacity. The aggregating entity clusters time-varying, aggregated battery capacity from plug-in hybrid electric vehicle (PHEV) fleets and power reserves from conventional generators. It is shown that providing additional control reserve capacity from time-varying sources such as PHEVs is possible and beneficial for power system control. An MPC framework is used as the algorithm of choice for the ancillary service manager. It is able to manage and allocate control reserve power efficiently from its sources, taking into account their constraints on available power, energy and ramping capabilities. The proposed method is applied to the IEEE 14 bus system featuring conventional generation units and several PHEV fleets with different charging patterns and availability profiles. Emergency situations, resulting in frequency deviations on different time-scales, are simulated. The MPC scheme proves to stabilise the grid frequency at all times taking into account the various parameter constraints of the different control sources.

BESS Control Strategies for Participating in Grid Frequency Regulation

Abstract Battery Energy Storage Systems (BESS) are very effective means of supporting system frequency by providing fast response to power imbalances in the grid. However, BESS are costly, and careful system design and operation strategies are needed in order to generate revenue for the system owner. We propose control strategies which will help to maintain BESSs State of Charge (SoC) in the optimal range and slow down battery aging significantly. A validation of these strategies using data from ENTSO-E (for the German regulation market) in Continental Europe and the PJM interconnection in the USA is presented in the results section.