Balancing Power Market Research Articles

Demonstration of participation in the German balancing power market using a large‐capacity hybrid battery storage system

AbstractAs one of NEDO's international demonstration projects, a large‐capacity hybrid battery storage system which consists of two types of battery cells with different charge‐discharge characteristics was constructed in the state of Lower Saxony in the Federal Republic of Germany. By using the hybrid battery system has a lithium‐ion which has an advantage in short time and high rate, and a sodium‐sulfur battery (NAS) which has an advantage in long time and low rate, the tender participation in the balancing power market in Germany had been executed. The hybrid battery storage system could successfully drive and provided services for primary and secondary control reserves, elimination of power imbalance, and reactive power injection, as well as a combination of these services.

Demonstration of Participation in the German Balancing Power Market using a Large-capacity Hybrid Battery Storage System

Demonstration of Participation in the German Balancing Power Market using a Large-capacity Hybrid Battery Storage System

Flexibility-expansion planning of multi-energy systems by energy storage for participating in balancing-power markets

The growing need for balancing power combined with the shutdown of conventional power plants requires new balancing-power providers. In this context, industrial energy systems are particularly promising. However, the main task of industrial energy systems is to provide various energy forms. For this purpose, they operate interconnected units to maximize efficiency, but the interconnected operation also increases complexity, limiting flexibility due to the need to supply fixed demands. Energy storage can increase the flexibility of current and future industrial energy systems, thus enhancing the potential for sector coupling within the overall energy system at a low cost. To improve the flexibility of industrial energy systems, we propose a design optimization framework that accounts for investment in energy storage and for the provision of balancing power. Since the request of balancing power is uncertain, we present a stochastic program for the balancing-power market and propose two ways to model storage that both derive feasible storage operations while being computationally efficient. In a case study of a multi-energy system, cost savings between 6% and 17% can be achieved by increasing flexibility for participation in the balancing-power market with investment in heat storage. The sensitivity analysis identifies heat storage as particularly advantageous for heat-driven energy systems. Our method combines long-term investment decisions with short-term operational uncertainties to identify optimal investment decisions, which enhance the energy system’s flexibility for the provision of balancing power.

Analysing sector coupling technologies for Re‐purposing coal‐fired power plants–Case study for the ENTSO‐E grid

AbstractThe high emission intensity of coal‐fired power plants (CFPP) leads to the inevitable next step towards energy transition, the coal phase‐out. One challenge is the subsequent use of still‐functioning assets. Re‐purposing these assets avoids value loss and creates new opportunities for coal regions. Therefore, this study considers the sector coupling technologies Power‐to‐Gas (PtG) and Gas‐to‐Power (GtP) as re‐purposing options. First, a multi‐variable Mixed‐Integer Linear Programming optimisation model is established. This model includes the participation of the plant in the current (2020) and future (2030, 2040) electricity and natural gas spot‐markets and the balancing power market while fulfilling existing contracts, and allows for determining the re‐purposing technologies' operating profiles. By applying a techno‐economic analysis, investment recovery periods of the considered re‐purposing technologies are assessed, which range between two (GtP) and over ten (PtG) years. A sensitivity analysis accounting for current energy prices and technological advancements reveals capital expenditure has the highest impact on this Return‐On‐Investment period. Additionally, a case study considering the Austrian energy grids is performed to account for the grid impact of integrating these technologies at former CFPP sites. Thus, it is found that the investigated sector coupling technologies have the potential to compensate for grid congestions even in profit‐optimised operation.

Day-ahead market bidding taking the balancing power market into account

Generation companies with controllable units put considerable analysis into the process of bidding into the day-ahead markets for electricity. This article investigates the gain of coordinating price-taking bids to the day-ahead electricity market (DA) and sequentially cleared energy-only markets, such as the Nordic balancing market (BM). A technically detailed case study from the Nordic market is presented. We find that coordinated bidding is hardly worthwhile under current market conditions, but that only a modest increase in the demand for balancing energy will make coordination profitable. If the supply curve for balancing energy is convex, so that the cost of balancing energy is asymmetric, the gains will be even higher. Finally, we find that day-ahead market bid curves that result from coordinated instances provide extra supply at low prices, and lower supply at high prices, compared to sequential bids. This is rational given the anticipated opportunities that the balancing market offers; however, it makes day-ahead bidding appear to exploit market power.

Congestion Management in Power System Using Locational Marginal Price in Balancing Power Market

Congestion Management in Power System Using Locational Marginal Price in Balancing Power Market

Wind power intermittency and the balancing power market: Evidence from Denmark

Generated amounts of wind power fluctuate considerably over time due to weather patterns. Yet majority of wind power is sold in the day-ahead market, where producers are required to commit to a physical delivery 12–36h in advance. If the wind suddenly dies down, producers can cover their deficit either by purchasing from the intraday market or, as a last resort, from the balancing power market. This paper studies the pricing in the balancing power market during times of lower-than-expected wind power generation. Using data to construct ”wind power surplus”, defined as the difference between wind power prognosis and actual wind power production, this paper uses nonlinear regression methods to estimate the effect of wind surplus on the price of balancing power. The main finding is that the balancing power prices are consistently higher during times of lower-than-expected wind power production even after controlling for other factors. If we fix other covariates at their means and compute the predicted balancing power prices at the 5th and 95th percentile of wind power surplus, the difference is 26.8 DKK/MWH. For down-regulation, the corresponding figure is 21.9 DKK/MWH.

Investigating the Electrical Demand-Side Management Potential of Industrial Steam Supply Systems Using Dynamic Simulation

The increasing share of volatile, renewable energies, such as wind and solar power, leads to challenges in the stabilization of power grids and requires more flexibility in future energy systems. This article addresses the flexibilization of the consumer side and presents a simulation-based method for the technical and economic investigation of energy flexibility measures in industrial steam supply systems. The marketing of three different energy-flexibility measures—bivalence, inherent energy storage and adjusting process parameters—both at the spot market and at the balancing power market, are investigated from a technical as well as an economic point of view. Furthermore, the simulation-based methodology also considers pressure and temperature fluctuation induced by energy-flexibility measures. First, different energy-flexibility measures for industrial steam supply systems are introduced. Then, the physical modeling of the steam generation, distribution, and consumption as well as measure-specific control strategies will be discussed. Finally, the methodology is applied to a steam supply system of a chemical company. It is shown that the investigated industrial steam supply system shows energy-flexibility potentials up to 10 MW at peak and an annual average of 5.6 MW, which highly depend on consumer behavior and flexibility requirements.

Investigating the Electrical Demand-Side Management Potential of Industrial Steam Supply Systems Using Dynamic Simulation

The increasing share of volatile, renewable energies, such as wind and solar power, leads to challenges in the stabilization of power grids and requires more flexibility in future energy systems. This article addresses the flexibilization of the consumer side and presents a simulation-based method for the technical and economic investigation of energy flexibility measures in industrial steam supply systems. The marketing of three different energy-flexibility measures—bivalence, inherent energy storage and adjusting process parameters—both at the spot market and at the balancing power market, are investigated from a technical as well as an economic point of view. Furthermore, the simulation-based methodology also considers pressure and temperature fluctuation induced by energy-flexibility measures. First, different energy-flexibility measures for industrial steam supply systems are introduced. Then, the physical modeling of the steam generation, distribution, and consumption as well as measure-specific control strategies will be discussed. Finally, the methodology is applied to a steam supply system of a chemical company. It is shown that the investigated industrial steam supply system shows energy-flexibility potentials up to 10 MW at peak and an annual average of 5.6 MW, which highly depend on consumer behavior and flexibility requirements.

Electricity Day-Ahead Market Price Forecasting by Using Artificial Neural Networks: An Application for Turkey

The reference price is the most important signal for market participant to have position of selling or buying in the trade of electricity. The electricity price has a dynamic structure and is directly and/or indirectly affected by many factors. All of the market participants’ transaction is carried out in a contract based on forecasting. These transactions are for day-ahead market (DAM) and balancing power market 1 day before, intraday market 60 min before and short, mid, long term for derivatives market. The price is forecasted that is determined as far as cost. The price forecasting has benefits which are maximizing profit, protecting from all of the crisis and constrictions and mitigation of loses. All of the market participants highly affected from the price. For this reason, such an important topic should be conducted scientifically. This study aims to develop a price forecasting tool for short term which is calculated day by day in DAM at Turkish electricity market. This forecasting tool is developed based on artificial neural networks. All of the market participants take the price, which is calculated in DAM, as reference. There are many direct and/or indirect factors affecting the reference price used by market players. In this study, a short-term price forecasting model was formed by analyzing historical data and all of the data, which are affecting the price most correctly, are correlated by using artificial neural network method. The basis of the forecasting model used is supply and demand curves. All the factors affecting different points on supply and demand curves by artificial neural network model provide the most correct reference price. In the study, January, April, July and October 2017 values were taken and estimated for randomly selected days of the months. The randomly selected supply and demand curves of April 19 is affected from renewable energy production, natural gas and coal production. In this scope of conclusion, the forecasted price is below 5% deviation on average per day compared to the actual price. As for hourly error deviation, it was seen that deviation is below 10% for 13 h. The suggested artificial neural network model scientifically supports market participant to make short-term transaction.

Utilizing the flexibility of distributed thermal storage in solar power forecast error cost minimization

Intermittent renewable energy generation, which is determined by weather conditions, is increasing in power markets. The efficient integration of these energy sources calls for flexible participants in smart power grids. It has been acknowledged that a large, underutilized, flexible resource lies on the consumer side of electricity generation. Despite the recently increasing interest in demand flexibility, there is a gap in the literature concerning the incentives for consumers to offer their flexible energy to power markets. In this paper, we examine a virtual power plant concept, which simultaneously optimizes the response of controllable electric hot water heaters to solar power forecast error imbalances. Uncertainty is included in the optimization in terms of solar power day-ahead forecast errors and balancing power market conditions. We show that including solar power imbalance minimization in the target function changes the optimal hot water heating profile such that more electricity is used during the daytime. The virtual power plant operation decreases solar power imbalances by 5–10% and benefits the participating households by 4.0–7.5 € in extra savings annually. The results of this study indicate that with the number of participating households, while total profits increase, marginal revenues decrease.

Performance Bounds for Continuous Trading on Balancing Power Markets

Abstract In power systems the system frequency is a good indicator of the networks resilience to major disturbances. In many deregulated markets, e.g. the Nordic power market, the system operator controls the system frequency manually by calling off bids handed in to a market, called the balancing power market. In this paper we consider the problem of optimal bid call-off on the balancing market, that the system operator is faced with each operating period. We formulate the problem as a stochastic optimal control problem of impulse type. When searching for numerical solutions a complicating factor is the structure of the balancing power market, where the overall marginal price applies to all bids. To retain numerical tractability we propose computationally efficient upper and lower bounds for the value function in the dynamic programming algorithm.

Bidding strategy for a battery storage in the German secondary balancing power market

Abstract This paper develops strategies for operating Battery Energy Storage Systems (BESS) on the Secondary Balancing Power (SBP) market in Germany. Various control reserve market scenarios with participating BESS were simulated for the years 2016 and 2017. Within the simulation, the submitted bids of the SBP auction as a well as the BESS operation strategy have been optimized with regard to maximizing the economic revenues. The simulation makes use of an SBP power price prediction based on a SARIMA model and implements a battery model for lithium-ion batteries providing the aging status and an incremental cost breakdown for a specific operation strategy. With current battery and electricity market prices, the simulation reveals that it is not economically beneficial to provide SBP with a standalone battery. This is mainly due to the high requirements for SBP with respect to the power-to-energy ratio and operation strategy. The simulation further implies that a BESS operating in a pool is possibly economically viable as the restrictions for the power-to-energy ratio do not apply. The value of BESS in a pool is subject to the pool’s precise configuration which prohibits a general statement regarding financial viability.

Day-Ahead Market Bidding Taking the Balancing Power Market Into Account

Day-Ahead Market Bidding Taking the Balancing Power Market Into Account

Virtual Power Plant Operation with Solar Power Forecast Errors and Demand Response

Intermittent renewable energy production, determined by weather conditions, is increasing in power markets. Their efficient integration calls for flexible participants in smart power grids. It has been acknowledged that a huge underutilized flexibility resource lies on the electricity consumer-side. The activation of this demand flexibility is, however, a big challenge. Despite the recently risen interest towards demand flexibility, there is a gap in the literature investigating the incentives for consumers to offer their flexibility to power markets. It has been proposed that there needs to be a third-party operator aggregating and controlling this flexibility. In this paper we examine a concept of virtual power plant, which simultaneously optimizes the response of controllable electric hot water heaters to solar power forecast error imbalances. Uncertainty is included in the optimization in terms of solar power day-ahead forecast errors and balancing power market conditions. We show that the virtual power plant can add value from optimizing the combination of these resources. The results indicate that while the total profits are increasing, the marginal revenues are diminishing with the number of participating households. From a policy perspective, our results imply that market efficiency can be increased by allowing the aggregated resources to participate more freely in the markets.

Agent-Based Simulations for Electricity Market Regulation Advice: Procedures and an Example

This paper discusses the use of agent-based simulation models for regulatory advice in electricity market regulation. It briefly introduces the necessary procedures and the state-of-the-art of the methodology, and outlines its possible range of application. In a second part, the paper presents an agent-based simulation model developed by the authors. The model can be applied for analyzing different market designs and market structures in order to derive evidence for regulatory advice. This is exemplified through the analysis of two settlement rules in the balancing power market and of several divestiture scenarios of the German electricity sector.

Derivatives of the nodal prices in market power screening

This paper proposes a novel method for market power screening. This method is developed for horizontally and vertically consolidated power markets, and is based on the optimal power flow (OPF) model properties. It undertakes the calculation and analysis of a matrix of derivatives of the nodal prices with respect to generating unit offer prices. The analysis takes into consideration the influence of particular partakers and energy groups on the nodal prices. This paper presents a theoretical analysis of the partakers' and groups' profits as well as a method for the market power screening. Moreover, the issue wherein the LMP model generates prices above the highest bidding price is discussed. Illustrative case studies and case studies based on the Polish wholesale balancing power market model are also presented.

Increasing the Benefit from Cost-Minimizing Loads via Centralized Adjustments

Several demand response (DR) strategies rely on real-time pricing and selfish local optimization, which may not result in optimal electricity consumption patterns from the viewpoint of an energy supplier or a power system. Thus, this paper proposes a strategy enabling centralized adjustments to cost-minimize consumers’ load. By employing the strategy, an aggregator is able to alter electricity consumption in order to remove power imbalances and to participate in the balancing power market (BPM). In this paper, we focus on direct electric space heating (DESH) loads that aim to minimize their heating cost locally. The consumers and an aggregator agree about an indoor temperature band, within which the aggregator is allowed to alter the temperature, and thus the electricity consumption. Centrally, the aggregator procures its electricity demand from a day-ahead (DA) market by utilizing the allowed temperature band and employs the band later in real-time (RT) operation for the balancing of its own imbalances or regulating power in the BPM.

A market-oriented hierarchical framework for residential demand response

The integration of a great deal of uncertain renewable sources in future grids will require more operational flexibility. Demand response (DR) can provide the load shaping potentials thereby assuaging the need for operational flexibility. To this end, this paper intends to develop a framework focusing on realization of domestic storage space heating DR capability in balancing market. The developed framework consists of two hierarchical stages named energy market stage and balancing power market stage. The first stage deals with customers’ day-ahead decisions in energy market. In this stage, the system operator releases day-ahead energy prices in response to which customers optimize their electricity usage to minimize their energy expenses. The second stage optimizes customers’ intra hour load scheduling decisions in balancing power market. In the second stage, up/down power regulation incentives are offered to customers who, in the hope of achieving monetary gains, modify their promised day-ahead decisions. Performance of the framework is verified through simulations on Finnish case studies. According to the obtained results, the framework allows the customers to make savings in energy expenses as well as the system operator to benefit from DR.

Economics and design of balancing power markets in Germany

This article analyzes the economic fundamentals that govern market design and behavior in German balancing power markets. Then, partly based on theoretical work by Chao and Wilson [3], we illustrate the role of the scoring and the settlement rule as key elements of the market design. With sufficiently competitive markets, a settlement rule based on uniform pricing ensures efficient energy call in the balancing power market. A scoring rule based on capacity prices only ensures an efficient production schedule. Thus, both rules together with rational bidding ensure simultaneous efficiency on the balancing power market and the wholesale electricity market.