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This paper addresses the transmission network expansion planning problem under uncertain demand and generation capacity. A two-stage adaptive robust optimization framework is adopted whereby the worst-case operating cost is accounted for under a given user-defined uncertainty set. This paper differs from previously reported robust solutions in two respects. First, the typically disregarded correlation of uncertainty sources is explicitly considered through an ellipsoidal uncertainty set relying on their variance-covariance matrix. In addition, we describe the analogy between the corresponding second-stage problem and a certain class of mathematical programs arising in structural reliability. This analogy gives rise to a relevant probabilistic interpretation of the second stage, thereby revealing an undisclosed feature of the worst-case setting characterizing robust optimization with ellipsoidal uncertainty sets. More importantly, a novel nested decomposition approach based on results from structural reliability is devised to solve the proposed robust counterpart, which is cast as an instance of mixed-integer trilevel programming. Numerical results from several case studies demonstrate that the effect of correlated uncertainty can be captured by the proposed robust approach. [ABSTRACT FROM AUTHOR]

This paper proposes a dynamic valuation framework to determine the opportunity value of battery capacity degradation in grid applications based on the internal degradation mechanism and utilization scenarios. The proposed framework follows a dynamic programming approach and includes a piecewise linear value function approximation solution that solves the optimization problem over a long planning horizon. The paper provides two case studies on price arbitrage and frequency regulation using real market and system data to demonstrate the broad applicability of the proposed framework. Results show that the battery lifetime value is critically dependent on both the external market environment and its internal state of health. On the grid service side, results show that second-life batteries can provide more than 50% of the value compared to new batteries, and frequency regulation provides two times more revenue than price arbitrage throughout the battery lifetime. [ABSTRACT FROM AUTHOR]

Long-term contracting is the traditional governance mechanism to deal with the transaction costs associated with the specificity of gas industry assets. Long-term contracts have been often used to allocate risks among players, and to that end, they often include take-or-pay provisions. These clauses specify that buyers take the volume risk, as they are obliged to pay for a minimum amount of gas consumption. In exchange, buyers pay a predefined price, supposedly lower than the risk-neutral expectation of short-term gas prices. In that view, if the buyer is able to resell that gas in the short term, the contract is an effective hedge against short-term volatility. Otherwise, the contract does not act as a hedge but it becomes a sunk cost. The corresponding power producers' behavior involves not only output decisions but also financial decisions. To analyze that situation, this paper develops a new quantitative methodology that allows comparing risk-neutral valuations of gas and power markets decisions. We test the model in a real-size system, and show the additional cost of the power system associated with a possible illiquidity of the short-term gas market. [ABSTRACT FROM PUBLISHER]

Imbalance settlement markets are managed by the system operators and provide a mechanism for settling the inevitable discrepancies between contractual agreements and physical delivery. In European power markets, settlements schemes are mainly based on heuristic penalties. These arrangements have disadvantages: First, they do not provide transparency about the cost of the reserve capacity that the system operator may have obtained ahead of time, nor about the cost of the balancing energy that is actually deployed. Second, they can be gamed if market participants use the imbalance settlement as an opportunity for market arbitrage, for example if market participants use balancing energy to avoid higher costs through regular trade on illiquid energy markets. Third, current practice hinders the market-based integration of renewable energy and the provision of financial incentives for demand response through rigid penalty rules. In this paper we try to remedy these disadvantages by proposing an imbalance settlement procedure with an incentive compatible cost allocation scheme for reserve capacity and deployed energy. Incentive compatible means that market participants voluntarily and truthfully state their valuation of ancillary services. We show that this approach guarantees revenue sufficiency for the system operator and provides financial incentives for balance responsible parties to keep imbalances close to zero. [ABSTRACT FROM PUBLISHER]

Currently, demand response resources can sell load reductions in wholesale energy markets. However, paying for load reductions ultimately results in an unbalanced market, where the amount of resources sold (megawatts) is less than the amount of resources bought (megawatts and “negawatts”). To resolve this imbalance, the ISO must allocate the cost of compensating demand response to those buyers who benefit from reduced LMPs. Current cost allocation methods are quite broad and based on each energy buyer's share of the total load. In an uncongested network, this results in a “fair” allocation of costs, i.e., an allocation proportional to the benefits that each party accrues. However, in a congested network, this is no longer the case, as price separation occurs between nodes. In this paper, we therefore propose a cost allocation method based on LMP sensitivity that accounts for the effect of congestion on the distribution of benefits between nodes with different LMPs. Since this sensitivity-based method only takes into account the cost allocation per node, we also propose a means of allocating costs between individual load serving entities (LSEs) at a single node. Due to this refinement, LSEs are rewarded according to their individual contribution to demand response. Finally, we define a fairness index to evaluate the performance of the proposed method as compared to a load-based allocation. We find that when load reductions are small (1%–3% total load), the fairness index of the proposed method is very close to zero, indicating almost identical benefit to cost ratios for all market participants. Although the fairness index increases with increasing load reductions, results show that even for larger load reductions, the fairness index is still lower for the proposed method than for the load-based allocation method. [ABSTRACT FROM PUBLISHER]

Significant uncertainty surrounds the future development of electricity systems, primarily in terms of size, location and type of new renewable generation to be connected. In this paper we assess the potential for flexible network technologies, such as phase-shifting transformers, and non-network solutions, such as energy storage and demand-side management, to constitute valuable interim measures within a long-term planning strategy. The benefit of such flexible assets lies not only in the transmission services provided but also in the way they can facilitate and de-risk subsequent decisions by deferring commitment to capital-intensive projects until more information on generation development becomes available. A novel stochastic formulation for transmission expansion planning is presented that includes consideration of investment in these flexible solutions. The proposed framework is demonstrated with a case study on the IEEE-RTS where flexible technologies are shown to constitute valuable investment options when facing uncertainties in future renewable generation development. [ABSTRACT FROM PUBLISHER]

Many countries use auctions to select agents to which transmission concessions are awarded. Where multiple concessions are auctioned each year, there are potential benefits, for transcos and grid users, in using auction protocols allowing risk-averse bidders to explicitly consider complementary packages of transmission facilities: combinatorial and simultaneous descending auctions. We investigate the use of these protocols for transmission auctions, with aid of mixed-integer linear optimization models developed for this task and realistic case studies, while focusing on the treatment of the exposure problem. [ABSTRACT FROM AUTHOR]

Pricing for the use of the networks is essential in the way that it should be able to reflect the costs/benefits imposed on a network when connecting a new generator or demand and to provide forward-looking message to influence the site and size of future network customers. Studies have been extensively carried out over the years to achieve this pricing goal. Few methodologies can directly link nodal generation/demand increment to network long-run marginal/incremental costs. Even fewer consider network security in their pricing methodologies, considering it is one of the most important cost drivers. All networks are designed to be able to withstand credible contingencies, but this comes at a significant cost to network development. This paper proposes a new approach that can establish the direct link between nodal generation/demand increment and changes in investment cost while ensuring network security. The investment cost is reflected by the change in the spare capacity of a network asset from a nodal injection, which is in turn translated into an investment horizon, leading to the change in the present value of a future investment cost. The security is reflected in the pricing through a full N - 1 contingency analysis to define the maximum allowed power flow along each circuit, from which the time horizon of future investment is determined. This paper illustrates the implementation of the proposed pricing model for a system whose demand grows either at a uniform rate or at variable growth rates. The benefits of introducing security into the long-run pricing model are demonstrated on the IEEE 14-busbar system and a practical 87-busbar distribution network. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have been well recognized as a deferrable load with the flexibility to shift their energy demands over time. Although this one-dimensional flexibility has been extensively investigated both by research and industrial implementations, the expanding energy demand and the associated uncertainties still make the integration of a large population of EVs into power system reliably and economically greatly challenging. In this paper, we design an auction scheme via mechanism design to elicit two additional flexibilities from EVs, namely energy flexibility and deadline flexibility. An offline mechanism is firstly designed as a benchmark based on the famous Vickrey–Clark–Groves mechanism. Then based on the primal-dual approach, we propose an online auction, in which all bids are truthful, the loss of social welfare is bounded by competitive ratio, and the mechanism can be implemented in polynomial time. By the numerical results, we quantitatively show that both the power system operators and individual EVs can benefit from the integration of the multi-dimensional flexibilities through our proposed mechanisms. [ABSTRACT FROM AUTHOR]

This paper is the second of a two-paper series and presents a model to assess and promote investment projects defined in a plan of expansion of the transmission. We propose a model that consists of three main elements: valuation of a project based on the design of a linear contract, a principal-agent model to assess the optimal effort of an agent, and the right-of-way negotiating cost. We also define a model to evaluate bids by the agents. The value of the project depends on the number of competitors, the incentives to invest, and the right-of-way costs. The right-of-way cost is approached from the perspective of a bilateral bargaining problem. [ABSTRACT FROM PUBLISHER]

Among the ancillary services, a great number of cost allocation strategies have been broadly developed in the deregulated environment. Generally, the utilization of such services can be determined by directly evaluating the actual amount of the usage or by indirectly analyzing the fair/reasonable contribution/attribution to the market participants. In the case of the primary frequency regulation (PFR) service, which is operated by the participating generating units to maintain the real-time balance between the generation and load, the discussion of the PFR service attributed to the load side has still received relatively little attention. In this paper, a new strategy of the cost allocation of the PFR service from the customer side is proposed. Two main factors, the load fluctuation and the frequent demand change, are considered to figure out the PFR reaction relating to the different substations. The design of a scheme for determining the cost allocation index of the PFR service can be applied to the presently exiting power market. In addition, the actually load series recorded from the extra-high voltage (EHV) substations of the Taipower system located in northern, central, and southern Taiwan are meticulously analyzed and utilized to verify the feasibility and practicability of cost allocation. [ABSTRACT FROM AUTHOR]

By the introduction of competitive supply, modern electric utilities are forced to operate their systems closer to their security limits. Under such fragile conditions, any disturbance could endanger system security and lead to system collapse. There is, therefore, a need to develop new methods which could evaluate optimal scheduling of operating reserve and forewarn the system operators to take necessary preventive actions in case need arises. An effective method is proposed in this paper to optimally allocate spinning reserve based on a well-being model. The method used in conventional well-being framework for classifying power system comfort zone into healthy and marginal states is initially revised. The optimal value of health index and system spinning reserve requirements are then evaluated on the basis of a trade off between the total cost of spinning reserve and the expected cost of energy not served. The effectiveness of the proposed method is examined using the IEEE-RTS. [ABSTRACT FROM AUTHOR]

A probabilistic method for a pool-based combined energy and reserve market, which considers both generators and interruptible loads (ILs), is proposed in this paper. We minimize generation production cost together with the cost associated with expected energy not supplied (EENS) due to outages of generating units and failures of ILs to supply the reserve when required. The proposed settlement scheme allocates equitably cost of reserve among generators and ILs. Given that the method takes into account reliability of individual generators and ILs, the proposed scheme provides incentives for all market participants to improve their performance. A number of case studies are carried out to illustrate the impact of participant's characteristics on the reserve cost allocation. [ABSTRACT FROM AUTHOR]

Security cost analysis is important in electricity markets to address the correlation between market operation and power system operation. This paper proposes an efficient security cost analysis method and describes its implementation using a three-tier client/server architecture and up-to-date web technologies. The proposed security cost analysis is based on a system security index and its sensitivities with respect to certain system parameters. The web implementation allows easy and effective access by all market participants to make competitive decisions based on the security costs and sensitivity information obtained through the proposed security cost analysis techniques. The web implementation of the proposed method is successfully tested on a six-bus system and a 129-bus system. [ABSTRACT FROM AUTHOR]

Market power has been a problematic issue for fair and transparent trades in various electricity markets. To deal with the problems of existing market power mitigation methods, such as complicated judgment criteria, excessive supervision probability, impersonal cost data accounting, and the requirements on perfect information circumstances, a novel spot market power mitigation clearing mechanism (MPMCM) is proposed, which manages to limit potential market power execution while avoiding overregulation and maintaining a real market supply–demand situation. The MPMCM consists of three processes, namely, market power evaluation, bidding capacity division, and bidding capacity constraint. The MPMCM is transformed into a set of bidding constraints and properly integrated in the common market clearing procedure. A bilevel mathematical problem with equilibrium constraints market equilibrium model is proposed to formulate the MPMCM for market simulation, and the mixed integer linear problem reformulation of the bilevel model is derived. Finally, an illustrative example is proposed to observe the strategic behaviors under various situations, thereby proving the validity and effectiveness of the MPMCM. A large-scale numerical example based on a modified IEEE 200-node system is proposed to prove the adaptivity of the MPMCM. [ABSTRACT FROM AUTHOR]

Transactive energy (TE) has been recognized as a promising technique for integrating responsive loads and distributed energy resources as well as advancing grid modernization. To help the industry better understand the value of TE and compare different TE schemes in a systematic and transparent manner, a comprehensive simulation-based TE valuation method is developed. The method has the following salient features: first, it formally defines the valuation scenarios, use cases, baseline, and valuation metrics; second, an open-source simulation platform for transactive energy systems has been developed by integrating transmission, distribution and building simulators, and plugin TE and non-TE agents through the framework for network cosimulation (FNCS); third, transparency and flexibility of the valuation is enhanced through separation of simulation and valuation, base valuation metrics, and final valuation metrics. A valuation example based on the smart grid interoperability panel use Case 1 is provided to demonstrate the developed TE simulation program and the valuation method. [ABSTRACT FROM AUTHOR]

The stochastic nature of wind alters the unit commitment and dispatch problem. By accounting for this uncertainty when scheduling the system, more robust schedules are produced, which should, on average, reduce expected costs. In this paper, the effects of stochastic wind and load on the unit commitment and dispatch of power systems with high levels of wind power are examined. By comparing the costs, planned operation and performance of the schedules produced, it is shown that stochastic optimization results in less costly, of the order of 0.25%, and better performing schedules than deterministic optimization. The impact of planning the system more frequently to account for updated wind and load forecasts is then examined. More frequent planning means more up to date forecasts are used, which reduces the need for reserve and increases performance of the schedules. It is shown that mid-merit and peaking units and the interconnection are the most affected parts of the system where uncertainty of wind is concerned. [ABSTRACT FROM AUTHOR]

This paper presents an approach for the allocation of transmission network costs by controlling the nodal electricity prices. The proposed approach introduces generation and nodal injection penalties into the traditional economic dispatch so as to create nodal price differences that recover the required transmission revenue from the resulting congestion rent. As a consequence, the new electricity prices reflect not only the marginal costs of production subject to transmission constraints but also the capital costs of the network. This is the approach commonly adopted with most commodities whose price includes the unit cost of the good itself as well as the transportation cost from the production centers to the final consumer. [ABSTRACT FROM AUTHOR]

Different regulatory frameworks have implemented competitive mechanisms to increase efficiency in transmission, a natural monopoly. Conflicts of interest and hidden costs make necessary to define methods to obtain an appropriate valuation of new transmission assets. [ABSTRACT FROM PUBLISHER]

Efficient and well-timed investments in electric transmission networks that cope with the large ongoing power market uncertainties are currently an open issue of significant research interest. Strategic flexibility for seizing opportunities and cutting losses contingent upon an unfavorable unfolding of the long-term uncertainties is an attribute of enormous value when assessing irreversible investments. In this sense, flexible AC transmission systems (FACTS) devices appear as an effective manner of adding flexibility to the transmission expansion planning. This article proposes an investment valuation approach which properly assesses the option value of deferring transmission lines investments whereas gaining flexibility by investing in FACTS devices. The flexibility provided by FACTS investments—option to abandon and to relocate—is assessed through a real option valuation approach based on the novel least square Monte Carlo method. In order to illustrate the practicability of the proposed valuation approach, a traditional expansion strategy (lines) and a flexible investment strategy (lines and FACTS) are compared in a real study case. The article shows that a proper combination of lines and FACTS leads to efficient investments by allowing a progressive adaptation of the transmission grid to the changing scenarios. [ABSTRACT FROM PUBLISHER]

A routine task faced by Microgrid (MG) operators is to optimally allocate incoming power demand requests while accounting for the underlying power distribution network and the associated constraints. Typically, this has been formulated as an offline optimization problem for day-ahead scheduling, assuming perfect forecasting of the demands. In practice, however, these loads are often requested in an ad-hoc manner and the control decisions are to be computed without any foresight into future inputs. With this in view, the present work contributes to the modeling and algorithmic foundations of real-time load scheduling problem in a demand response (DR) program. We model the problem within an AC Optimal Power Flow (OPF) framework and design an efficient online algorithm that outputs scheduling decisions provided with information on past and present inputs solely. Furthermore, a rigorous theoretical bound on the competitive ratio of the algorithm is derived. Practicality of the proposed approach is corroborated through numerical simulations on two benchmark MG systems against a representative greedy algorithm. [ABSTRACT FROM AUTHOR]

We describe the new method used in Chile to allocate transmission charges among generating companies and customers, as defined in Law 19940 of March 2004 (also known as Ley Corta or Short Law). We show that the new Chilean transmission charge scheme is a hybrid based on marginal cost pricing, identification of use through economic benefits and flow identification methods, and last, a postage stamp to redistribute almost all the charges that customers have to pay. We also estimate the direct per kilowatthour charge that customers will pay and discuss its effect on location and expansion signals. [ABSTRACT FROM AUTHOR]