Game Theoretical Approach to Novel Reactive Power Ancillary Service Market Mechanism

State-of-the-art short-term electricity market operation with solar generation: A review

Abstract: With the accelerating penetration of solar energy in energy systems, market operations concerning the solar-associated intermittency are widely discussed. How to correctly model the solar generation in the market and solve the uncertainty-based operation problems call for solutions. Unlike other renewable resources, solar power can be more easily applied to the demand side through behind-the-meter installations in a distributed manner with significant future extensibility. The corresponding operational rules in the markets are largely being revised. Over the past two decades, with the development of deregulated power markets, numerous studies related to uncertainty-based market operations tend to transform the market from a deterministic and centralized framework to a stochastic and decentralized one. As the relevant literature is most recent, this paper reviews their contributions to electricity market operations with solar integration and underlines the research directions of this topic and ongoing industry practices. A thorough review of the electricity markets worldwide with solar energy is provided. A variety of proposed mathematical solutions to the problem are also discussed.

Day-ahead optimal reactive power ancillary service procurement under dynamic multi-objective framework in wind integrated deregulated power system

Abstract: This paper deals with the investigation of a day-ahead reactive power ancillary service procurement problem to minimize cost and voltage deviation under wind power generation uncertainties in a pool-based deregulated system. This reactive power procurement problem is formulated as a dynamic bi-objective optimization problem and is solved using a developed Pareto-based multi-objective artificial electric field algorithm (MO-AEFA). The developed MO-AEFA utilizes nondominated sorting principle and an external archive to store Pareto optimal solutions. Sign and reorder mutation operators are used to avoid trapping in local optima and enhance population diversity. The numerical results obtained from MO-AEFA are compared with other algorithms to validate the efficacy of proposed approach. The optimization algorithm utilizes a fast Newton power flow employing sparse matrix techniques to diminish computational burden. The capacitor switching is decided with consideration of marginal prices. The proposed methodology has been tested on modified IEEE 30-bus and IEEE 118-bus test systems. The performance of both test systems is analyzed for two studies namely, VAr dispatch without wind integration, and VAr dispatch under wind integration. The analysis with wind integration is further investigated for different wind penetration levels. The convergence characteristic of Pareto solutions is measured through statistical distance and diversity metrics.

Neural Fitted Q Iteration based Optimal Bidding Strategy in Real Time Reactive Power Market_1.

Abstract: In real time electricity markets, the objective of generation companies while bidding is to maximize their profit. The strategies for learning optimal bidding have been formulated through game theoretical approaches and stochastic optimization problems. Similar studies in reactive power markets have not been reported so far because the network voltage operating conditions have an increased impact on reactive power markets than on active power markets. Contrary to active power markets, the bids of rivals are not directly related to fuel costs in reactive power markets. Hence, the assumption of a suitable probability distribution function is unrealistic, making the strategies adopted in active power markets unsuitable for learning optimal bids in reactive power market mechanisms. Therefore, a bidding strategy is to be learnt from market observations and experience in imperfect oligopolistic competition-based markets. In this paper, a pioneer work on learning optimal bidding strategies from observation and experience in a three-stage reactive power market is reported.

Development of a Smart Meter for Power Quality-Based Tariff Implementation in a Smart Grid

Abstract: Regarding the modern power smart grid, distribution consumers and prosumers are highly concerned about power quality (PQ). In fact, they would prefer to pay higher prices for a reliable and good quality power supply. Unfortunately, utility operators still aim for reliability alone, ignoring the quality of supply voltage and current. There are no clear guidelines for monitoring, penalizing, or implementing PQ-based tariff schemes in LV distribution systems. In addition, the implementation of a PQ-based tariff requires a real-time measuring mechanism at the user end, which is very expensive and difficult to understand for a domestic consumer. This paper presents a novel, low-cost, efficient, and user-friendly smart PQ meter to overcome these issues and limitations. It is essentially a PQ analyzer with energy metering functionality, which implements a novel PQ-based tariff scheme that penalizes consumers violating the PQ limits and provides incentives for a good PQ profile. It measures as many as 28 parameters and keeps track of the PQ for both the consumer and the grid in real-time. This paper demonstrates the specifications, design, and testing of the meter and proves the validity of the concept by practical implementation. The meter is practical, feasible, and economical for implementing PQ-based tariff schemes in LV distribution systems or smart grids.

MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education

Abstract: MATPOWER is an open-source Matlab-based power system simulation package that provides a high-level set of power flow, optimal power flow (OPF), and other tools targeted toward researchers, educators, and students. The OPF architecture is designed to be extensible, making it easy to add user-defined variables, costs, and constraints to the standard OPF problem. This paper presents the details of the network modeling and problem formulations used by MATPOWER, including its extensible OPF architecture. This structure is used internally to implement several extensions to the standard OPF problem, including piece-wise linear cost functions, dispatchable loads, generator capability curves, and branch angle difference limits. Simulation results are presented for a number of test cases comparing the performance of several available OPF solvers and demonstrating MATPOWER's ability to solve large-scale AC and DC OPF problems.

Towards a Competitive Market for Reactive Power

Abstract: This paper presents the design of a competitive market for reactive power ancillary services. Generator reactive power capability characteristics are used to analyze the reactive power costs and subsequently to construct a bidding framework. The reactive power market is settled on uniform price auction, using a compromise programming approach based on a modified optimal power flow model. The paper examines market power issues in these markets and identifies locations where strategic market power advantages are present that need to be removed through investments in reactive power devices.

Localized reactive power markets using the concept of voltage control areas

Abstract: In this paper, we present the design of a localized competitive market for reactive power ancillary services at the level of individual voltage-control areas. The concept of electrical distance has been used to identify the different voltage-control areas within a power system. The proposed reactive power market is settled on uniform price auction, using a modified optimal power-flow model. Uniform prices for various components of reactive power service are obtained for each voltage-control area. In the study cases described in the paper, we examine whether such a localized reactive power market is more desirable than a common system-wide reactive power market.

Solving multi-leader-common-follower games

Abstract: Multi-leader-common-follower games arise when modelling two or more competitive firms, the leaders, that commit to their decisions prior to another group of competitive firms, the followers, that react to the decisions made by the leaders. These problems lead in a natural way to equilibrium problems with equilibrium constraints (EPECs). We develop a characterization of the solution sets for these problems and examine a variety of nonlinear optimization and nonlinear complementarity formulations of EPECs. We distinguish two broad cases: problems where the leaders can cost-differentiate and problems with price-consistent followers. We demonstrate the practical viability of our approach by solving a range of medium-sized test problems.