Search

This paper proposes a novel approach to designing technical and financial protocols needed to support the penetration of distributed energy resources (DERs). It first formulates a complex, hard‐to‐implement, centralized decision‐making objective for providing end‐to‐end electricity service. It then introduces a new taxonomy of an end‐to‐end interactive operations planning framework. The taxonomy rests on the dynamic monitoring and decisions systems (DyMoNDS) principles for supporting interactive protocols of (i) end‐to‐end interactions within a complex, multilayered multi‐voltage power system; (ii) dynamic energy resource management system (DERMS) interactions with their DERs as well as with the bulk power system (BPS) operators; and (iii) DERs interactions with DERMS. The distributed model predictive control for creating physically implementable cost functions is essential. Also, the minimal coordination of different layers utilizes an AC optimal power flow that is essential for ensuring power flow delivery. We next provide a proof‐of‐concept illustration on the IEEE 14 bus system augmented by two standardized microgrids of the proposed interactive protocols, and their potential use for enhancing dynamic host capacity (DHC). While novel, this approach is a natural outgrowth of the existing industry operations: It only requires enhancing decision‐making tools by the stakeholders, and carefully‐defined protocols for implementing their interactions. [ABSTRACT FROM AUTHOR]

This paper concerns a novel approach to the modeling and control design for transient stabilization of electric power systems using Flexible Alternating Current Transmission System (FACTS) devices. A nonlinear dynamic model of general interconnected electric power systems in the ordinary differential equation (ODE) form is proposed in terms of time-varying phasors of all dynamic components. This model captures previously unmodeled fast dynamics of inductors and capacitors of FACTS. Additionally, it allows us to observe the active power which is flowing through FACTS during transients. Using the derived model, an ectropy-based FACTS controller is proposed. The proposed controller regulates the active power through FACTS in order to shift the increment in energy created by disturbances. The energy increment is directed from generators into FACTS, preserving the synchronization between generators during disturbances. Simulation results obtained on the IEEE 14-bus system demonstrate the potential of this controller. The controller is shown to increase critical clearing time of the system in the case of a fault. [ABSTRACT FROM AUTHOR]

This paper defines flow control algorithms for loop flow cancellation based on the allocation and tracing of bilateral transactions and loop flows. In Part I of this paper, we have shown that the main difference between transportation and electrical networks is caused by the existence of loop flows. We have introduced a distributed framework for the modeling and tracing of bilateral transactions and the corresponding loop flows. Its zooming-out capability provides a valuable mechanism for representing external (inter-area) loop flows based on simplified topologies of individual areas. The tracing information accurately allocates bilateral transactions with associated contract paths to line flows and loop flows. Furthermore, this information can be used for determining the set points of control equipment so that loop flows are minimized. In this framework, phase angle regulators (PARs), commonly used for line flow control, are represented through their effects on loop flows. We define sufficient conditions for achieving complete loop flow cancellation. A new distributed algorithm for determining PAR set points in a coordinated way without revealing operating conditions of individual areas is introduced in this part. Finally, complete loop flow cancellation and the distributed algorithm for finding PAR set points are demonstrated in the Reliability Test System (RTS) 96-bus system with wheeling loop flows. [ABSTRACT FROM AUTHOR]

This paper introduces a novel multi-control area framework for explicit modeling, managing, and accounting of simultaneous bilateral transactions with specified contract paths. Our framework provides a modular and multi-layered electrical network representation with zooming-in and zooming-out capabilities. The zoomed-out representation concerns interconnections and inter-area transactions, while the zoomed-in representation concerns a single area and its internal transactions. The framework allows explicit modeling of bilateral transactions with contract paths through a transformation of a meshed electrical network into a spanning tree. Loop flows are introduced to represent a deviation between the contract paths of bilateral transactions and physical line flows. The effects of both intra-area and inter-area bilateral transactions and loop flows can be graphically traced in the framework. Moreover, these tracing methods allocate bilateral transactions to line flows and loop flows, essential for accounting and flow control. Our tracing methods differ from the distribution factor based method because the distribution factor matrix handles nodal injections only and it cannot account for contract paths of bilateral transactions and the resulting loop flows. The multi-layered network transformations and tracing methods are illustrated on the IEEE 14-bus system. [ABSTRACT FROM AUTHOR]

In Part I of this two-part paper, we introduce several possible methods for integrating wind power, price-responsive demand and other distributed energy resources (DERs). These methods differ with respect to information exchange requirements, computational complexity, and physical implementability. A novel look-ahead interactive dispatch that internalizes inter-temporal constraints at the DERs level, and dispatches the results of distributed decisions subject to spatial security constraints, is proposed as a possible effective algorithm. This method requires only the use of today's static security-constrained economic dispatch (SCED) by the system operators. The optimization accounting for inter-temporal constraints, and ramping rates in particular, is done by the DERs while they create their own supply and demand functions. To implement this method, today's supervisory control and data acquisition (SCADA) needs to be transformed into a multi-directional, multi-layered information exchange system. [ABSTRACT FROM PUBLISHER]

In Part II of this paper, we demonstrate on a modified 24-bus IEEE Reliability Test System (RTS) that it is indeed possible to manage large-scale intermittent resources in coordination with price-responsive demand. The algorithms introduced in Part I of this paper are simulated assuming 20% and 50% wind capacity. We show that the look-ahead dispatch of the proposed method is physically implementable and, when used with elastic demand, can accommodate the integration of close to 50% wind capacity. This is contrasted with the observation that, without elastic demand, 50% wind integration is not physically implementable. From the perspective of total market surplus, the predictive dispatch of the proposed method is 3.8% suboptimal when compared to the centralized most efficient predictive economic dispatch. Further simulations are needed to test the feasibility of coordinating wind power and price-responsive demand on realistic large-scale power systems. [ABSTRACT FROM PUBLISHER]

This paper presents a novel mode) for optimization of investments in new power generation under uncertainty. The model can calculate optimal investment strategies under both centralized social welfare and decentralized profit objectives. The power ma!ket is represented with linear supply and demand curves. A stochastic dynamic programming algorithm is used to solve the investment problem, where uncertainty in demand is represented as a discrete Markov chain. The stochastic dynamic model allows us to evaluate investment projects in new base and peak load power generation as real options, and determine optimal timing of the investments. In a case study, we use the model to compare optimal investment strategies under centralized and decentralized decision making. A number of interesting results follow by varying the assumptions about market structure and price response on the demand side. [ABSTRACT FROM AUTHOR]

Presents a study which defined a price-based decision making process for participating in a reserve market for power systems reliability. Details on its need for a reserve market; Effect of reserve market on unit commitment; Conclusions.

Analyzes the strictly engineering aspects of Available Transmission Capacity (ATC). Basic notion of available transmission capacity in a non-linear power network; Decoupled real power-phase angle steady state problem; Monotonic response of a non-linear power network; Algorithms for computing ATC in monotonic non-linear networks; Non-monotonic response of a non-linear power network; Conclusions.

Presents a systematic framework for pricing transmission and ancillary services in competitive power markets. Framework for pricing transmission services; Cost-based pricing strategy; Ancillary services; Analysis of the proposed pricing approach; Numerical examples using the transmission line parameters; Conclusions.

Presents derivations of basic formulae for computing the contributions of each economic transaction to the network power flows throughout the system in steady-state operation of interconnected electric power systems. Notation; Mathematical formalae for decomposition of power flows; Computation of the major components; Load flow formulation using a distributed slack bus; Implications of distributed slack bus formulation on decomposition of network flows; Conclusions.

The aim of this study is to investigate the chemical composition of ethanol, acetone extracts and essential oil of the roots and aerial parts of Sanguisorba minor subsp. muricata. Flavonoids and phenolic acids were identified as the main components in the studied extracts herein. Rutin and quercetin-3-sophoroside were found to be dominant flavonoids in both extracts. Although it was observed that the determined chemical compositions of the essential oil obtained from the aerial parts and roots of the plant species were quite different from the data obtained by Headspace measurement, as expected, the essential oils obtained from the species were found to be rich in mainly monoterpene hydrocarbons and oxygenated monoterpenes. While salicylaldehyde, carvacrol and linalool were determined as the main components in the essential oil obtained from the aerial parts of the species, the main components in the essential oil obtained from the roots were observed as borneol, myrtenol and a-campholenol. [ABSTRACT FROM AUTHOR]

This paper is motivated by the need to ensure fast microgrid stability. Modeling for purposes of establishing stability criterion and possible implementations are described. In particular, this paper proposes that highly heterogeneous microgrids comprising both conventional equipment and equipment based on rapidly emerging new technologies can be modeled as purely electric networks in order to provide intuitive insight into the issues of network stability. It is shown that the proposed model is valid for representing fast primary dynamics of diverse components (gensets, loads, and PVs), assuming that slower variables are regulated by the higher level controllers. Based on this modeling approach, an intuitively appealing criterion is introduced requiring that components or their combined representations must behave as closed-loop passive electrical circuits. Implementing this criterion is illustrated using a typical commercial feeder microgrid. Notably, these set the basis for standards that should be required for groups of components (subgrids) to ensure no fast instabilities in complex microgrids. Building the need for incrementally passive and monotonic characteristics into standards for network components may clarify the system level analysis and integration of microgrids. [ABSTRACT FROM AUTHOR]

• Demand flexibility exhibits important dynamics that cannot be modelled by price elasticity alone. • Demand response to price is non-linear and hysteretic, and hysteresis depends on load use density. • To understand hysteresis, aggregate response dynamic models are derived from particle-hopping models of load shifting. • Challenges in parameterizing dynamic models of aggregate response are discussed. • Machine learning inputs necessary to overcome predictability are presented. Demand flexibility and its responsiveness under price-based control is a major research field. Much attention has been paid to model demand elasticity as synonymous with demand flexibility. But demand flexibility comes mostly as load shifting, and load shifting dynamics have been neglected when modelling demand response. In this paper, we model load shifting dynamics to simulate aggregate responses and analyse their predictability under time-varying prices. Our experience with simulation is then used to discuss possible enhancements in machine learning capable of predicting aggregate load dynamics. [ABSTRACT FROM AUTHOR]