Towards reinforcement learning for vulnerability analysis in power-economic systems

Future smart grids can and will be subject of systematic attacks that can result in monetary costs and reduced system stability. These attacks are not necessarily malicious, but can be economically motivated as well. Emerging flexibility markets are of interest here, because they can incite attacks if market design is flawed. The dimension and danger potential of such strategies is still unknown. Automatic analysis tools are required to systematically search for unknown strategies and their respective countermeasures. We propose deep reinforcement learning to learn attack strategies autonomously to identify underlying systemic vulnerabilities this way. As a proof-of-concept, we apply our approach to a reactive power market setting in a distribution grid. In the case study, the attacker learned to exploit the reactive power market by using controllable loads. That was done by systematically inducing constraint violations into the system and then providing countermeasures on the flexibility market to generate profit, thus finding a hitherto unknown attack strategy. As a weak-point, we identified the optimal power flow that was used for market clearing. Our general approach is applicable to detect unknown attack vectors, to analyze a specific power system regarding vulnerabilities, and to systematically evaluate potential countermeasures.

Solving realistic reactive power market clearing problem of wind-thermal power system with system security

This paper proposes a security-constrained single and multi-objective optimization (MOO) based realistic security constrained-reactive power market clearing (SC-RPMC) mechanism in a hybrid power system by integrating the wind energy generators (WEGs) along with traditional thermal generating stations. Pre-contingency and post-contingency reactive power price clearing plans are developed. Different objective functions considered are the reactive power cost (RPC) minimization, voltage stability enhancement index (VSEI) minimization, system loss minimization (SLM), and the amount of load served maximization (LSM). These objectives of the SC-RPMC problem are solved in a single objective as well as multi-objective manner. The choice of objective functions for the MOO model depends on the load model and the operating condition of the system. For example, the SLM is an important objective function for the constant power load model, whereas the LSM is for the voltage-dependent/variable load model. The VSEI objective should be used only in near-critical loading conditions. The SLM/LSM objective is for all other operating conditions. The reason for using multiple objectives instead of a single objective and the rationale for the choice of the appropriate objectives for a given situation is explained. In this work, the teaching learning-based optimization (TLBO) algorithm is used for solving the proposed single objective-based SC-RPMC problem, and a non-dominated sorting-based TLBO technique is used for solving the multi-objective-based SC-RPMC problem. The fuzzy decision-making approach is applied for extracting the best-compromised solution. The validity and efficiency of the proposed market-clearing approach have been tested on IEEE 30 bus network.

Modern Features of Price Formation on the Reactive Power Market

This article discusses the specific features of such a product as reactive power. The degree of reactive power compensation both in the domestic electric power industry and in most industrialized countries is clearly insufficient. The possibilities available in electric grids, at power plants and at consumers of electricity for coordinated regulation of reactive power and voltage levels are not fully used. The main factors influencing the formation of the reactive power market in the electric power industry are revealed. The proposed market is based on the organization and implementation of qualified selection of reactive power suppliers. The scheme of the price bid of reactive power suppliers, developed on the fundament of the cost structure of various types of reactive power suppliers is proposed. Rational regulation of reactive power is currently not considered as an economic problem, but it is one of the main tools for managing the efficiency of EPS. The proposed organizational mechanism of pricing for reactive power and the qualified selection of its suppliers is aimed at determining the range of suppliers of reactive power capable of meeting the demand for it with the least costs, as well as to stimulate investments in the construction of new sources of reactive power.

Implementation of Reactive Power Markets to Enhance the Power System Network.

Reactive power is an important component which plays a critical role in maintaining grid reliability, especially voltage stability. The report presents an analysis of the current compensation strategies followed by different independent system operators (ISOs) in US and identifies the drawbacks in the present compensation schemes. The properties of reactive power which poses an impediment to setup a reactive power market has been compared with the need of a reactive power market. Finally, a possible spot market structure has been considered along with bid formulation and its different components as applicable to different reactive power producing equipment.