Reactive Power Market Research Articles

Reactive power management in distribution networks in the presence of distributed generation sources based on information gap decision theory

The presence of uncertain parameters in power systems has led to many challenges for the designers and operators of these systems. One of these challenges is reactive power management in the presence of distributed renewable generation sources.In this article, the management of reactive power in distribution networks in the electricity market and the presence of distributed renewable generation sources, including wind and solar power plants, is performed considering the uncertainties in the network load, power generation of distributed generation sources, and active and reactive power market prices. Furthermore, reactive power cost modeling of reactive power compensation equipment is carried out.A hybrid stochastic/robust optimization method is employed to model the uncertainties in the problem. Finally, the efficiency of the method is confirmed by numerical examinations using the IEEE 33-bus distribution network and the GAMS optimization software. Simulation results indicate that in the risk-averse strategy, for a certain increase in cost, the radius of uncertainty in the active and reactive power market prices increases. Also, in this strategy, as β increases, the total cost of network operating increases by 81.72 %, while in a risk-seeking strategy, with the increase of β, the total operating cost of the network decreases by 77.78 %.

A Multi-Objective Stochastic Framework for Coupled Reactive Power and Energy Market Settlement for Wind Energy Integrated System

A Multi-Objective Stochastic Framework for Coupled Reactive Power and Energy Market Settlement for Wind Energy Integrated System

An AC optimal power flow framework for active–reactive power scheduling considering generator capability curve

AbstractThis paper presents a simplified optimal power flow (OPF) framework to facilitate co‐optimised active and reactive power scheduling for synchronous generators and price‐sensitive demands. The proposed framework creates an opportunity for generators and loads to simultaneously participate in a combined market for active and reactive power. The co‐optimisation of active and reactive power generation is constrained by the interdependence of the active and reactive power capacities, which is represented by the generator capability curve. Thus, a detailed mathematical derivation of the opportunity costs across various regions of the generator capability curve is presented. This study considers a detailed generator capability curve that considers the armature, field, under‐excitation, and prime mover limits. The interdependence of active and reactive power consumption for demand is modelled using the concept of power‐factor. The OPF problem for generator and load scheduling is formulated as a non‐linear optimisation task, leveraging the inherent properties of the generator capability curve, that is, piecewise smoothness, continuity, and the monotonically increasing slope magnitudes. Furthermore, to simplify the OPF formulation, the non‐linear capability curve is represented as a combination of the linear curves. To demonstrate the effectiveness of the proposed OPF methodologies, suitable case studies are conducted using different test systems.

Reactive Power Market Design for Distribution Networks With High Photovoltaic Penetration

Voltage violation problems caused by high photovoltaic (PV) penetration in distribution systems can be mitigated if PVs are properly operated by the distribution system operator (DSO). However, PV resources are usually reluctant to provide reactive power support due to the absence of an incentive mechanism. Here, we design a reactive power market mechanism to unlock the potential of PV resources to provide reactive power support. We then develop an iterative algorithm to calculate the Nash equilibrium of the proposed market. The market concentration is further quantified to demonstrate its applicability in different power distribution systems. Case studies show that the proposed market can be applied to large power distribution systems with multiple PV resources.

A reactive power market for the future grid

As pressures to decarbonize the electricity grid increase, the grid edge is witnessing a rapid adoption of distributed and renewable generation. As a result, traditional methods for reactive power management and compensation may become ineffective. Current state-of-art for reactive power compensation, which rely primarily on capacity payments, exclude distributed generation (DG). We propose an alternative: a reactive power market at the distribution level designed to meet the needs of decentralized and decarbonized grids. The proposed market uses variable payments to compensate DGs equipped with smart inverters, at an increased spatial and temporal granularity, through a distribution-level Locational Marginal Price (d-LMP). We validate our proposed market with a case study of the US New England grid on a modified IEEE-123 bus, while varying DG penetration from 5% to 160%. Results show that our market can accommodate such a large penetration, with stable reactive power revenue streams. The market can leverage the considerable flexibility afforded by inverter-based resources to meet over 40% of reactive power load when operating in a power factor range of 0.6 to 1.0. DGs participating in the market can earn up to 11% of their total revenue from reactive power payments. Finally, the corresponding daily d-LMPs determined from the proposed market were observed to exhibit limited volatility.

Robust bidding strategy of battery energy storage system (BESS) in joint active and reactive power of day-ahead and real-time markets

The most important applications of an Energy Storage System (ESS) in power systems are energy arbitrage along with procurement of Ancillary Services (ASs). In addition to economic benefits, ESS also improves network reliability and stability. In this paper, a bidding strategy model of a Battery Energy Storage System (BESS) in a Joint Active and Reactive Power Market (JARPM) in the Day-Ahead-Market (DAM) and the Real-Time-Market (RTM) using a robust framework is presented. In this study, the BESS model is considered a price-taker, with the private owner trying to maximize its profit while facing price uncertainty. In the first stage of the proposed model, JARPM is cleared in a deterministic way without the presence of BESS to determine hourly prices of active and reactive power. In the second stage, by determining the prices uncertainty interval and the robust budget for DAM and RTM, the robust bidding model aims to maximize the BESS owner's profit, using the robust counterpart formation of the objective function and dual theory. The proposed robust formulation based on a Mixed Integer Non-Linear Programming Model (MINLP) is implemented in the GAMS software environment on the IEEE-24-RTS test system. The result shows that by the participation of BEES in the market, the average price of active and reactive power is reduced by 2 % & 3 % respectively. In addition, the overall cost of DAM execution is reduced markedly. On the other hand, the proposed framework in three case studies also guarantees a suitable profit level for the private owners of BESS (30–35 $/hour).

IGDT-Based Robust Operation of Thermal and Electricity Energy-Based Microgrid with Distributed Sources, Storages, and Responsive Loads

In this paper, the optimal operation of microgrids (MGs) with thermal blocks, distributed generations (DGs), storage systems, and responsive loads is presented to achieve optimal scheduling of active, reactive, and thermal power of the mentioned elements in the day-ahead (DA) reactive power and energy market environment. The thermal block has a combined heat and power (CHP) system, a boiler, and thermally responsive loads. This scheme minimizes the difference between the total operating costs of the MG and power sources and the total revenue gained from the sale of energy and reactive power of the mentioned elements in the markets located in the MG. It is constrained by the AC power flow equations, network operation constraints, and the operating model of these elements. Furthermore, this scheme is subject to the uncertainties of energy price, load, and renewable power. In this paper, to access the optimal resistant solution against the maximum prediction error associated with the mentioned uncertainties, a robust model based on information gap decision theory (IGDT) is used. Finally, by implementing the proposed scheme on a 119-bus radial MG, the obtained numerical results confirm the ability of the scheme to simultaneously improve the economic and operational situation of the MG. The proposed scheme succeeded in improving energy cost, energy loss, voltage drop, and power factor of the distribution substation by roughly 101%, 44%, 41%, and 16% compared to power flow studies, even in the worst-case scenario caused by uncertainties.

REACTIVE POWER MARKET MODEL BASED ON THE DIVISION OF THE ELECTRIC POWER SYSTEM INTO VOLTAGE ZONES AND ON THE TWOLEVEL OPTIMIZATION ALGORITHM

The article presents a reactive power evaluation methodology which in terms of time comprises the action of the reactive power market in the stage of short-term planning. The methodology is based on the division the electric power system (EPS) into voltage zones by using the electrical distance method, whereby local reactive power markets are established. Within each local market a separate TSO cost optimization is performed by means of the optimal power flow applying the criterion of minimal required payment for reactive power. The said optimization is the first step within a developed methodology, the purpose of which is to determine the share of each of the available control systems in reactive power generation within each of the established zones. Based on optimal reactive power generation, an auction procedure is conducted by which a uniform price of reactive power generation within a zone is defined. In the second optimization step the optimization of the whole network is carried out by the criterion of minimal energy procurement costs to cover the network losses and simultaneously by the criterion of minimal reactive energy procurement costs, using the optimal power flow. The methodology has been tested on the Croatian EPS model for the maximum network load scenario. The proposed approach is warranted by the results, whereas the detected problems can at once serve as guidelines for future development and potential improvements in the proposed methodology.

Day-ahead local flexibility market for active and reactive power with linearized network constraints

This paper presents a Day-Ahead Local Flexibility Market in the Distribution Network cleared using a novel Successive Linear Programming algorithm for Optimal Power Flow in the Distribution Network. The proposed algorithm is shown to be robust and produce high quality, AC feasible solutions with satisfactory solution speed. The efficiency of the proposed algorithm is validated via its application in various distribution networks and under different loading scenarios. The proposed Flexibility Market encompasses flexibility products for upward and downward active energy as well as service products for the provision of reactive power. The efficiency of the proposed Flexibility Market in solving operational issues of the distribution network is demonstrated via a case-study.

Design and evaluation of a multi-level reactive power market

The shift from conventional power plants on transmission level to distributed energy resources in the distribution grids requires procedures to enable efficient and economic reactive power exchange across different voltage levels. In this paper, we propose a multi-level reactive power market that enables reactive power provision from distributed energy resources to higher voltage levels. Each grid operator operates a local reactive power market and offers local reactive power potential, as an intermediary, to superordinate grid operators by passing on its aggregated cost curve and flexibility range. As a result, there is a low requirement of communication between the market participants and each grid operator is free to choose its local market rules as well as the optimization algorithm used. First results from a case study show that our decentralized market approach can realize an economically efficient multi-level reactive power provision that is close to a centrally computed optimal solution, without violating local grid constraints.

A new stochastic multi-objective framework for the reactive power market considering plug-in electric vehicles using a novel metaheuristic approach

A new stochastic multi-objective framework for the reactive power market considering plug-in electric vehicles using a novel metaheuristic approach

Probabilistic clearing of the reactive power market in the presence of solar power plants and considering the solar irradiance variations

With the advent of renewable energy plants, new sources have been created to provide reactive power. This paper first explores the importance of renewable energy sources growth, especially solar power plants, then it examined the participation of solar power plants in the reactive power market. Various cost components of the solar power plant have been investigated and a general cost function model has been proposed for all reactive power suppliers that help the independent system operator (ISO) to better manage the system. Considering the probabilistic nature of energy generation from solar power plants, solar irradiance variations are considered in the reactive market and a probabilistic structure is proposed. To simulate and to consider the probabilistic nature of solar irradiance, the Monte Carlo method is used in simulations. The proposed method has been tested on the IEEE 24 buses system and two definitive and probabilistic markets are compared. As stated in the results, the proposed algorithm has satisfactory results.

Reactive Power Markets: A Review

Liberalization of the energy system sets the way towards market-based solutions for ancillary service provision. Local reactive power markets are envisioned to achieve more economically and technically efficient reactive power provision to solve voltage control problems in future distribution and transmission grids. However, market-based reactive power procurement is a difficult and yet unsolved problem. This survey provides a comprehensive overview of the characteristics and hardships of reactive power markets. That is followed by a literature overview of reactive power market design, including local markets and markets on system operator level. Further, methods how to analyse reactive power markets are discussed, focusing on market power, game theoretical approaches, Reinforcement Learning, and manipulation of reactive power markets. From this overview, trends and current research gaps are derived and some general research recommendations are given to serve as a guideline for future research in the field of reactive power markets.

Spatial-economic framework to estimate small biomass plant remuneration in reactive power markets

With growing shares of renewable power generation, ancillary services such as reactive power become increasingly important to balance power systems. In this work, we provide a framework to assess the suitability of small biomass power plants, i.e., less than 5 MW, for reactive power markets. The proposed methodology consists of two-stages and considers the spatial relationship between the biomass plants’ location and the regional transmission system and tests different plant remuneration scenarios. In the first step, the reactive energy potentials available from biomass plants are quantified and located through spatial analysis, considering locational factors that influence the economic value that these plants bring to the ancillary services markets. Second, a financial analysis is performed to determine how each biomass plant’s electricity bill can be reduced through participation in ancillary services markets. Resulting layers of geographic information provide system operators and policymakers with the available reactive power potential and required financial compensation of biomass plant owners close to the electricity transmission system. The methodology is applied to a case study in São Paulo, Brazil, using data from sugar and alcohol plants installed near the regional transmission system’s 138 kV lines to assess the implementation of a seasonal reactive power market.

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

Abstract 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.

Hybrid stochastic risk-based approach for a microgrid participating in coupled active and reactive power market

In recent years, simultaneous participation in energy and ancillary services (AS) markets has been very profitable for microgrids (MG). High penetration of renewable energy sources (RES) in energy supply, due to the uncertainties of these products, increases the need for AS. Also, active and reactive powers are completely related, so in this paper the microgrid simultaneous participation in the active and reactive power and ancillary services (regulation up and regulation down, spinning reserve and non-spinning reserve) markets is modeled considering uncertainty of wind and solar generations. The relation between active and reactive power generation of each generator is calculated based on capability diagrams and mathematical equations. Conditional value at risk (CVaR) is used for risk management, and probability of calling ancillary services is calculated. Uncertainties of wind and solar generations are modeled using their probability distribution functions (PDFs). The ERCOT market simulation is discussed to calculate the participation of each unit in all the mentioned markets based on real-world data.

Clariant's MegaMax 800 catalyst set production record at Baofeng Energy's methanol plant

The probabilistic and intermittent output power of Wind Turbines (WT) is one major inconsistency of these Renewable Energy Sources (RES). Battery Energy Storage Systems (BESS) are a suitable solution to mitigate this intermittency by smoothening WT's output power. Although the main benefit of BESSs mentions as peak shaving and load-shifting, but in this research, it will verify that optimal placement and sizing them jointly with WTs can lead to more benefits like compensating the required system's reactive power support from WTs. The reactive power size of WTs and BESSs will be derived from the result of the joint sizing and placement in this study, as well as their active power output to meet the load demand. This can facilitate WTs and BESSs contribution to cover the system's required reactive power and their participation in the reactive power market and ancillary services. This paper also proposes new cost functions for both WTs and BESSs and minimizes their cost while ensuring minimal total loss (active and reactive) in the power distribution system. This can benefit both WTs' and BESSs' owners as well as system operators. Suitable placement and sizing of the WTs and BESSs can also improve the load bus voltage profiles, which can benefit the end-users, and will verify using the proposed optimization by different case studies on the 33 bus distribution system. The results of case studies ascertain the consistency of the proposed formulation for placement and sizing BESSs and WTs jointly, as well as other benefits to the power system, the power plant owners, and system operators.

Joint sizing and placement of battery energy storage systems and wind turbines considering reactive power support of the system

The probabilistic and intermittent output power of Wind Turbines (WT) is one major inconsistency of these Renewable Energy Sources (RES). Battery Energy Storage Systems (BESS) are a suitable solution to mitigate this intermittency by smoothening WT's output power. Although the main benefit of BESSs mentions as peak shaving and load-shifting, but in this research, it will verify that optimal placement and sizing them jointly with WTs can lead to more benefits like compensating the required system's reactive power support from WTs. The reactive power size of WTs and BESSs will be derived from the result of the joint sizing and placement in this study, as well as their active power output to meet the load demand. This can facilitate WTs and BESSs contribution to cover the system's required reactive power and their participation in the reactive power market and ancillary services. This paper also proposes new cost functions for both WTs and BESSs and minimizes their cost while ensuring minimal total loss (active and reactive) in the power distribution system. This can benefit both WTs' and BESSs' owners as well as system operators. Suitable placement and sizing of the WTs and BESSs can also improve the load bus voltage profiles, which can benefit the end-users, and will verify using the proposed optimization by different case studies on the 33 bus distribution system. The results of case studies ascertain the consistency of the proposed formulation for placement and sizing BESSs and WTs jointly, as well as other benefits to the power system, the power plant owners, and system operators.

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.