François Bouffard

Stochastic Security for Operations Planning With Significant Wind Power Generation

In their attempt to cut down on greenhouse gas emissions from electricity generation, several countries are committed to install wind power generation up to and beyond the 10%-20% penetration mark. However, the large-scale integration of wind power represents a challenge for power system operations planning because wind power 1) cannot be dispatched in the classical sense; and 2) its output varies as weather conditions change. This warrants the investigation of alternative short-term power system operations planning methods capable of better coping with the nature of wind generation while maintaining or even improving the current reliability and economic performance of power systems. To this end, this paper formulates a short-term forward electricity market-clearing problem with stochastic security capable of accounting for nondispatchable and variable wind power generation sources. The principal benefit of this stochastic operation planning approach is that, when compared to a deterministic worst-case scenario planning philosophy, it allows greater wind power penetration without sacrificing security.

Market-clearing with stochastic security-part I: formulation

The first of this two-paper series formulates a stochastic security-constrained multi-period electricity market-clearing problem with unit commitment. The stochastic security criterion accounts for a pre-selected set of random generator and line outages with known historical failure rates and involuntary load shedding as optimization variables. Unlike the classical deterministic reserve-constrained unit commitment, here the reserve services are determined by economically penalizing the operation of the market by the expected load not served. The proposed formulation is a stochastic programming problem that optimizes, concurrently with the pre-contingency social welfare, the expected operating costs associated with the deployment of the reserves following the contingencies. This stochastic programming formulation is solved in the second companion paper using mixed-integer linear programming methods. Two cases are presented: a small transmission-constrained three-bus network scheduled over a horizon of four hours and the IEEE Reliability Test System scheduled over 24 h. The impact on the resulting generation and reserve schedules of transmission constraints and generation ramp limits, of demand-side reserve, of the value of load not served, and of the constitution of the pre-selected set of contingencies are assessed.

Decentralized Demand-Side Contribution to Primary Frequency Control

Frequency in large power systems is usually controlled by adjusting the production of generating units in response to changes in the load. As the amount of intermittent renewable generation increases and the proportion of flexible conventional generating units decreases, a contribution from the demand side to primary frequency control becomes technically and economically desirable. One of the reasons why this has not been done was the perceived difficulties in dealing with many small loads rather than a limited number of generating units. In particular, the cost and complexity associated with two-way communications between many loads and the control center appeared to be insurmountable obstacles. This paper argues that this two-way communication is not essential and that the demand can respond to the frequency error in a manner similar to the generators. Simulation results show that, using this approach, the demand side can make a significant and reliable contribution to primary frequency response while preserving the benefits that consumers derive from their supply of electric energy.

Scheduling and Pricing of Coupled Energy and Primary, Secondary, and Tertiary Reserves

Current practice in some electricity markets is to schedule energy and various reserve types sequentially, first clearing the energy market, followed by the reserves needed. Since distinct reserve services can in fact be strongly coupled, and the heuristics required to bridge the various sequential markets can ultimately lead to loss of social welfare, simultaneous energy/reserves market-clearing procedures have been proposed and are in use. However, they generally schedule reserve services subject to exogenous rules and parameters that do not relate to actual operating conditions. The weaknesses of the current approaches warrant the investigation of alternatives. In that regard, we present a different methodology to the simultaneous market clearing of energy and reserve services. This approach avoids the pitfalls of the sequential procedures, while at the same time its basis for scheduling reserve services does no longer rely on some rules of thumb. The salient feature of the proposed approach is that, under marginal pricing, it yields a single price for all reserve types scheduled at a bus, unlike the current approaches. We show that this common price is given by the nodal marginal cost of security. We present two specific implementations of a simultaneous security-constrained market-clearing procedure, one deterministic and one probabilistic. An example of joint market clearing of energy with reserves required for primary and tertiary regulation illustrates how their strong coupling affects their schedule and prices.

An electricity market with a probabilistic spinning reserve criterion

This paper addresses the problem of reliability-constrained market-clearing in pool-based electricity markets with unit commitment. In general, probabilistic reliability criteria that implicitly set the reserve requirement are defined by the loss-of-load probability and by the expected load not served. As the computation of such metrics is complicated by their nonlinear and combinatorial nature, we introduce the notion of hybrid metrics based on the probabilities of loss-of-load due to single and double generation outages only. The reliability-constrained market-clearing problem can then be formulated as a mixed-integer linear program and solved with large-scale commercial solvers. Numerical tests with data from the IEEE Reliability Test System indicate that the new method is computationally efficient and produces market-clearing results with the desired probabilistic characteristics.

Market-clearing with stochastic security-part II: case studies

This paper analyzes the market-clearing formulation with stochastic security developed in its companion paper through two case studies solved using mixed-integer linear programming techniques. The generation and reserve schedules as well as the nodal prices of energy and security are assessed under various conditions such as a) line flow limits, b) when nonspinning reserve is excluded from the formulation, c) demand-side valuation of energy not served, d) generator ramping limits, and e) the set of pre-selected contingencies.

Electric Vehicle Aggregator/System Operator Coordination for Charging Scheduling and Services Procurement

Summary form only given. In response to the need for the decarbonization of the transport sector, it is expected that large fleets of electric vehicles (EVs) will constitute an important share of the electricity demand. This evolution is likely to be accompanied by a parallel evolution of the electricity supply business with the deployment of smart grid technologies. As a consequence, it is expected that demand will feature higher potential for communication and control, which will enable its active participation in the daily operational planning of power systems. In particular, EVs being equipped with a battery can both defer their demand or inject electricity back into the system. However, to achieve volumes that can have an impact on the system, these demands need to be aggregated and operated as an ensemble. This paper proposes the necessary adaptations to include the input of EV aggregation to electricity markets. This permits the scheduling of EV charging and services in coordination with the system operator thus enhancing the power systems efficiency and security while reducing its environmental impact. Results show that the EVs penetration levels that the system would be able to absorb without requiring expansion of the supply side, are significantly increased when coordination over their charging schedule is performed.

Towards Full Integration of Demand-Side Resources in Joint Forward Energy/Reserve Electricity Markets

This paper proposes a security-constrained forward market clearing algorithm within which the inherent characteristics of demand flexibility are acknowledged when the provision of reserve from the demand side is considered. In the proposed formulation, we co-optimize the cost of scheduling the appropriate resources to guarantee the security of the system and the expected cost of operating under any credible system state. In addition, we consider that consumers can offer to provide spinning reserve capacity deployable by voluntary load reductions in response to contingencies. Due to the load recovery effect (i.e., since energy usage is essentially postponed when demand-side reserve is deployed), in post-contingency states, any voluntary reduction in the load has to be accompanied by a subsequent increase in demand from the initial forecast. We demonstrate that the marginal value of the reserve provided by the demand can only be calculated taking into account the cost of supplying the recovery consumption. Flexible consumers can reduce their payments on average if energy is settled through real-time prices.

Keeping the lights on and the information flowing

We proposed a new framework for analyzing the impact that failures in the information infrastructure can have on the quality and reliability of the electricity supply. An analysis of major incidents using the proposed framework shows that information failures are quite often a significant contributing factor in their development and severity. We identified some of the challenges posed by the increasing reliance on information flow in the course of power system operation. We also identified some mitigating measures which could reduce the risks associated with failures in the power system information infrastructure.

Stochastic security for operations planning with significant wind power generation

In their attempt to cut down on greenhouse gas emissions from electricity generation, several countries are committed to install wind power generation up to and beyond the 10-20% penetration mark. However, the large-scale integration of wind power represents a challenge for power system operations planning because wind power (i) cannot be dispatched in the classical sense; and, (ii) its output varies as weather conditions change. This warrants the investigation of alternative short-term power system operations planning methods capable of better coping with the nature of wind generation while maintaining or even improving the current reliability and economic performance of power systems. To this end, this paper formulates a short-term forward electricity market-clearing problem with stochastic security capable of accounting for non-dispatchable and variable wind power generation sources. The principal benefit of this stochastic operation planning approach is that, when compared to a deterministic worst-case scenario planning philosophy, it allows greater wind power penetration without sacrificing security.