Demand-side view of electricity markets

Kirschen, Daniel S.

doi:10.1109/tpwrs.2003.810692

Cited by 684 publications

(339 citation statements)

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“…The flexibility of the demand side is primarily associated with the ability to shift the operation of some loads from periods of higher prices to periods of lower prices [23]. In other words, load reduction during certain periods is accompanied by a load recovery effect during preceding or succeeding periods.…”

Section: Problem Definitionmentioning

confidence: 99%

“…Constraint (4) represents its power limits. In order to maintain energy neutrality, the storage energy content at the start and the end of the operating horizon are assumed equal (5).The flexibility of the demand side is primarily associated with the ability to shift the operation of some loads from periods of higher prices to periods of lower prices [23]. In other words, load reduction during certain periods is accompanied by a load recovery effect during preceding or succeeding periods.…”

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confidence: 99%

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Stochastic Dual Dynamic Programming for Operation of DER Aggregators Under Multi-Dimensional Uncertainty

Fatouros

Konstantelos

Papadaskalopoulos

et al. 2019

IEEE Trans. Sustain. Energy

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Abstract--The operation of aggregators of distributed energy resources (DER) is highly complex, since it entails the optimal coordination of a diverse portfolio of DER under multiple sources of uncertainty. The large number of possible stochastic realizations that arise, can lead to complex operational models that become problematic in real-time market environments. Previous stochastic programming approaches resort to two-stage uncertainty models and scenario reduction techniques to preserve the tractability of the problem. However, two-stage models cannot fully capture the evolution of uncertain processes and the a priori scenario selection can lead to suboptimal decisions. In this context, this paper develops a novel stochastic dual dynamic programming (SDDP) approach which does not require discretization of either the state space or the uncertain variables and can be efficiently applied to a multi-stage uncertainty model. Temporal dependencies of the uncertain variables as well as dependencies among different uncertain variables can be captured through the integration of any linear multidimensional stochastic model, and it is showcased for a porder vector autoregressive (VAR) model. The proposed approach is compared against a traditional scenario-tree-based approach through a Monte-Carlo validation process, and is demonstrated to achieve a better trade-off between solution efficiency and computational effort.Index Terms--Aggregator, distributed energy resources, multidimensional uncertainty, stochastic dual dynamic programming, vector autoregressive modeling. I. NOMENCLATURE A. IndexesIndex of time periods, running from 1 to . Index of energy storage (ES) units, running from 1 to . Index of flexible loads (FL), running from 1 to . Index of wind turbines (WT), running from 1 to . Index of micro-generators, running from 1 to . B. ParametersEnergy market price at period . Operating cost of micro-generator . Cost of demand shedding. C. VariablesPower sold to (positive)/bought from (negative) the market at period . ,Power output of micro-generator at period . Demand shed at period ., Energy level of ES unit at period . ,Power input (positive) / output (negative) of ES unit at period . , ℎChange of demand of FL at period due to load shifting. ,Demand of FL at period after load shifting., Dispatched wind power output of WT at period . II. INTRODUCTIONA. Background FUNDAMENTAL feature of the emerging Smart Grid paradigm involves the integration of a large number of distributed energy resources (DER) storage units, in order to support the economic operation of the future low-carbon power system [1]- [2]. However, the large number, small individual size and inherent stochasticity characterizing these DER have complicated system scheduling and market coordination. Furthermore, driven by the wide integration of renewable generation in power systems, there is a general consensus to move energy trading as close as possible to real-time [3]- [4], which intensifies the complexity of DER coordination. These challenges have...

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Section: Problem Definitionmentioning

confidence: 99%

mentioning

confidence: 99%

Stochastic Dual Dynamic Programming for Operation of DER Aggregators Under Multi-Dimensional Uncertainty

Fatouros

Konstantelos

Papadaskalopoulos

et al. 2019

IEEE Trans. Sustain. Energy

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“…percentage change in the demanded quantity on response to one percent change in price [21]. The formula for the price elasticity of demand is expressed in (1), where Quantity is the quantity of the usage of the good or service and Price is the price of this good or service [22].…”

Section: Price Elasticitymentioning

confidence: 99%

“…The concept of Electricity Markets (EMs) appeared in the most developed countries as a consequence of power system deregulation and power sector restructuring [1]. Traditionally, the entities involved in power systems have determined tasks and are remunerated according to defined regulations.…”

Section: Introductionmentioning

confidence: 99%

“…The implementation of EMs was expected to lead to relevant advantages concerning the increase in power system efficiency and price reduction due to the end of monopolies [1]. However, the experience has proved that some problems can occur [2e4], due to the very specific electrical energy characteristics which make some rules and methods usually used in other commodities markets not useful in the EMs context.…”

Section: Introductionmentioning

confidence: 99%

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Demand response in electrical energy supply: An optimal real time pricing approach

Faria

Vale

2011

Energy

289

124

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a b s t r a c tIn competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities. This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer's profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer's profit.The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers' decision making.

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Control of Power Converters inacanddcMicrogrids

Dragičević

Meng

Blaabjerg

et al. 2019

Wiley Encyclopedia of Electrical and Electronics Engineering

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In this paper a repetitive control (RC) approach to improve current sharing between parallel-connected boost converters in DC microgrids is presented. The impact of changes in line impedance on current sharing is investigated. A repetitive controller is designed and connected in series with current controller of the boost converters to control the switching signals such that by regulating of the output voltage of each converter, the circulating current is minimized. The performance of the proposed control strategy is validated through simulation.

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Demand-side view of electricity markets

Cited by 684 publications

References 31 publications

Stochastic Dual Dynamic Programming for Operation of DER Aggregators Under Multi-Dimensional Uncertainty

Stochastic Dual Dynamic Programming for Operation of DER Aggregators Under Multi-Dimensional Uncertainty

Demand response in electrical energy supply: An optimal real time pricing approach

Control of Power Converters inacanddcMicrogrids

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