Probabilistic Spinning Reserve Provision Model in Multi-Control Zone Power System

Inter-zonal trading in multi-area power system (MAPS) improves the market efficiency and the system reliability by sharing the resources (energy and reserve services) across zonal boundaries. Actually, each area can operate with less reserve resources than would normally be required for isolated operation. The aim of this work is to propose a model that includes the problem of optimal spinning reserve (SR) provision into the security constraint unit commitment (SCUC) formulation based on the reliability criteria for a MAPS. The loss of load probability (LOLP) and the expected load not served (ELNS) are evaluated as probabilistic metrics in the case of a multi-control zone power system. Moreover, we demonstrate how these criteria can be explicitly incorporated into the market-clearing formulation. The non-coincidental nature of spinning reserve requirement across the zonal boundary is effectively modeled. Two system cases including a small-scale (six-bus) test system and the IEEE reliability test system (IEEE-RTS) are used to demonstrate the effectiveness of the presented model

Multi-Area Energy and Reserve Dispatch Under Wind Uncertainty and Equipment Failures

The cross-border trading among electricity markets in an interconnected multi-area system (e.g., in central Europe) and the integration of renewable resources (e.g., wind energy) have remarkably increased in recent years. To efficiently operate such system, a proper coordination among different areas is required. Within this context, a decentralized algorithm for market clearing is proposed in this paper to dispatch simultaneously energy and reserve under wind generation uncertainty and equipment failures. The proposed technique does not require a central operator but just a moderate interchange of information among neighboring areas. Additionally, the benefit of cross-border trading is studied

Multi-Area Unit Scheduling and Reserve Allocation Under Wind Power Uncertainty

This paper proposes a decentralized methodology to optimally schedule generating units while simultaneously determining the geographical allocation of the required reserve.We consider an interconnected multi-area power systemwith cross-border trading in the presence of wind power uncertainty. The multi-area market-clearingmodel is represented as a two-stage stochastic programming model. The proposed decentralized procedure relies on an augmented Lagrangian algorithm that requires no central operator intervention but just moderate interchanges of information among neighboring regions. The methodology proposed is illustrated using an example and a realistic case study

Economic Advantages of Office Buildings Providing Ancillary Services with Intraday Participation

Controlling the consumption profile of office buildings can be used to provide balancing services to the power grid at a financial benefit without violating its thermal comfort constraints. The economic advantage of such a service is a reduction in the total operating cost, but also an increase in average occupants’ comfort when using our control scheme. We study these effects for the case of participating in the secondary frequency control market of Switzerland. Moreover, we examine the advantages of engaging in the intraday energy market. We propose a method for solving the flexibility bidding problem for a building in order to partake in the ancillary services market. The proposed solution is based on the combination of a new intraday control policy and two-stage stochastic programming. We also study the sensitivity of this economic benefit to electricity pricing. Our findings are based on extensive simulations with real data for energy prices, ancillary service bids, meteorological records and the frequency control signals for the year 2014 as transmitted by Swissgrid

Providing ancillary service with commercial buildings: the Swiss perspective

Ancillary services constitute the cornerstone of the power grid. They allow for an efficient system operation, provide resilience to uncertainties and establish safeguards against unprecedented events. Their importance is growing due to the rise of grid decentralisation and integration of intermittent, renewable power sources, which lead to more variability and uncertainty in the system. Today, the vast share of ancillary services is provided by large generating units. An ongoing effort by research and business entities focuses on using variation of loads connected to the power grid in order to increase significantly the provision of such services, hopefully at a reduced cost. We examine here, from an economic perspective, the use of commercial buildings as ancillary service providers based on real prices from the Swiss electricity market. We calculate the effect of retail electrical prices on the economic performance of a building and find that for the rates charged in the least expensive cantons a single building can reduce its overall energy costs, when participating in the ancillary services market. For the high end of prices this gradually becomes prohibitive but can be alleviated for a building that has a need for electricity during nighttime hours, as well as daytime. Finally, we show, the counter-intuitive result that providing ancillary services can increase the comfort levels of a building at a decreased cost

Reserve services management in multi-area power system under uncertainty

The reserve is a service traded in the market to counteract unpredictable changes in system conditions. The efficient market-clearing procedure relies on economic criteria while maintaining the system security by means of a proper reserve management program. In this respect, there are several issues related to reserves that need to be assessed: (i) scheduling and allocation of reserves (ii) deployment or usage of reserves. In this dissertation, we formulate a market-clearing procedure that is in- tended to determine the reserve services required in an interconnected multi- area power system. First, the required reserves are determined implicitly using probabilistic criteria in an uncertain multi-area power system which is operated by a central system operator. Up to second order outages of generating units in a given area, double outages of generating units in different areas, and tie-line outages between interconnected areas are accounted for as possible uncertainties in the proposed model. Next, we provide a market-clearing procedure so that it is capable of de- termining the required reserves explicitly. Under this approach, the need for specifying any a priori reserve requirement is removed. Such proposed model is formulated as a two-stage stochastic programming problem. We use Bender’s decomposition approach to tackle the computational burden of the stochastic programming approach in the case with many scenarios. We then extend the model of electricity market-clearing, operated centrally, by proposing a decentralized market-clearing formulation capable of accounting for the system uncertainties, in particular wind production and equipment failures. The proposed decentralized algorithm relies on the decoupling of the first-order KKT optimality conditions of the original problem in such a way that the combination of the KKT conditions of all area sub-problems are identical to the KKT conditions of the original problem. The proposed model allows optimally dispatching the energy and reserve of each area of a multi-area system in a decentralized manner. Such model is relevant to the operation of the interconnected European electricity markets. Finally, we provide a decentralized procedure for clearing multi-regional electricity markets like electricity markets in U.S. where the unit commit- ment problem is solved for pool clearing. The aim of this methodology is to optimally schedule generating units while simultaneously determining the geographical allocation of the required reserve in the presence of wind power uncertainty. The proposed decentralized procedure relies on an augmented Lagrangian algorithm that require no central operator intervention but just moderate interchanges of information among neighboring regions. Numerical simulations and realistic case studies illustrate the performance of proposed market-clearing models

Probabilistic spinning reserve provision model in multi-control zone power system

Inter-zonal trading in multi-area power system (MAPS) improves the market efficiency and the system reliability by sharing the resources (energy and reserve services) across zonal boundaries. Actually, each area can operate with less reserve resources than would normally be required for isolated operation. The aim of this work is to propose a model that includes the problem of optimal spinning reserve (SR) provision into the security constraint unit commitment (SCUC) formulation based on the reliability criteria for a MAPS. The loss of load probability (LOLP) and the expected load not served (ELNS) are evaluated as probabilistic metrics in the case of a multi-control zone power system. Moreover, we demonstrate how these criteria can be explicitly incorporated into the market-clearing formulation. The non-coincidental nature of spinning reserve requirement across the zonal boundary is effectively modeled. Two system cases including a small-scale (six-bus) test system and the IEEE reliability test system (IEEE-RTS) are used to demonstrate the effectiveness of the presented model

Developing Offer Curves for an Electric Railway Company in Reserve Markets Based on Robust Energy and Reserve Scheduling

This paper proposes an appropriate offering strategy method for an electric railway company (ERC) to participate in reserve markets. In this respect, first the problem of energy and reserve scheduling for the ERC is modeled in a deterministic way. Next, a robust optimization technique is used to solve the problem taking into account the uncertain energy and reserve prices as well as the uncertain hourly energy demand of the electric railway substations. Afterward, a reserve offering curve construction algorithm based on the solution of robust energy and reserve scheduling is proposed. This algorithm takes into account the correlation between upward and downward reserve prices. Finally, to show the effectiveness of the proposed method, a realistic case study based on the characteristic of an ERC in Switzerland is presented

Developing offer curves for an electric railway company in reserve markets based on robust energy and reserve scheduling

This paper proposes an appropriate offering strategy method for an electric railway company (ERC) to participate in reserve markets. In this respect, first the problem of energy and reserve scheduling for the ERC is modeled in a deterministic way. Next, a robust optimization technique is used to solve the problem taking into account the uncertain energy and reserve prices as well as the uncertain hourly energy demand of the electric railway substations. Afterward, a reserve offering curve construction algorithm based on the solution of robust energy and reserve scheduling is proposed. This algorithm takes into account the correlation between upward and downward reserve prices. Finally, to show the effectiveness of the proposed method, a realistic case study based on the characteristic of an ERC in Switzerland is presented