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

In 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.

Seller, buyer and VPP agents behavior on a simulated electricity market

Competitive electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is an electricity market simulator able to model market players and simulate their operation in the market. As market players are complex entities, having their characteristics and objectives, making their decisions and interacting with other players, a multi-agent architecture is used and proved to be adequate. MASCEM players have learning capabilities and different risk preferences. They are able to refine their strategies according to their past experience (both real and simulated) and considering other agents’ behavior. Agents’ behavior is also subject to its risk preferences.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Distribution system operation supported by contextual energy resource management based on intelligent SCADA

Future distribution systems will have to deal with an intensive penetration of distributed energy resources ensuring reliable and secure operation according to the smart grid paradigm. SCADA (Supervisory Control and Data Acquisition) is an essential infrastructure for this evolution. This paper proposes a new conceptual design of an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). This SCADA model is used to support the energy resource management undertaken by a distribution network operator (DNO). Resource management considers all the involved costs, power flows, and electricity prices, allowing the use of network reconfiguration and load curtailment. Locational Marginal Prices (LMP) are evaluated and used in specific situations to apply Demand Response (DR) programs on a global or a local basis. The paper includes a case study using a 114 bus distribution network and load demand based on real data.

Practical aspects of slot-based task- splitting dispatching in its schedulability analysis

Consider the problem of scheduling a set of sporadic tasks on a multiprocessor system to meet deadlines using a tasksplitting scheduling algorithm. Task-splitting (also called semipartitioning) scheduling algorithms assign most tasks to just one processor but a few tasks are assigned to two or more processors, and they are dispatched in a way that ensures that a task never executes on two or more processors simultaneously. A certain type of task-splitting algorithms, called slot-based task-splitting, is of particular interest because of its ability to schedule tasks at high processor utilizations. We present a new schedulability analysis for slot-based task-splitting scheduling algorithms that takes the overhead into account and also a new task assignment algorithm.

A framework for programming sensor networks with scheduling and resource-sharing optimizations

Several projects in the recent past have aimed at promoting Wireless Sensor Networks as an infrastructure technology, where several independent users can submit applications that execute concurrently across the network. Concurrent multiple applications cause significant energy-usage overhead on sensor nodes, that cannot be eliminated by traditional schemes optimized for single-application scenarios. In this paper, we outline two main optimization techniques for reducing power consumption across applications. First, we describe a compiler based approach that identifies redundant sensing requests across applications and eliminates those. Second, we cluster the radio transmissions together by concatenating packets from independent applications based on Rate-Harmonized Scheduling.

Towards real multi-criticality scheduling

Componentised systems, in particular those with fault confinement through address spaces, are currently emerging as a hot topic in embedded systems research. This paper extends the unified rate-based scheduling framework RBED in several dimensions to fit the requirements of such systems: we have removed the requirement that the deadline of a task is equal to its period. The introduction of inter-process communication reflects the need to communicate. Additionally we also discuss server tasks, budget replenishment and the low level details needed to deal with the physical reality of systems. While a number of these issues have been studied in previous work in isolation, we focus on the problems discovered and lessons learned when integrating solutions. We report on our experiences implementing the proposed mechanisms in a commercial grade OKL4 microkernel as well as an application with soft real-time and best-effort tasks on top of it.

A compositional scheduling framework for digital avionics systems

ARINC specification 653-2 describes the interface between application software and underlying middleware in a distributed real-time avionics system. The real-time workload in this system comprises of partitions, where each partition consists of one or more processes. Processes incur blocking and preemption overheads and can communicate with other processes in the system. In this work we develop compositional techniques for automated scheduling of such partitions and processes. At present, system designers manually schedule partitions based on interactions they have with the partition vendors. This approach is not only time consuming, but can also result in under utilization of resources. In contrast, the technique proposed in this paper is a principled approach for scheduling ARINC-653 partitions and therefore should facilitate system integration.

Competitive analysis of static-priority partitioned scheduling on uniform multiprocessors

Consider the problem of scheduling a set of sporadically arriving tasks on a uniform multiprocessor with the goal of meeting deadlines. A processor p has the speed Sp. Tasks can be preempted but they cannot migrate between processors. On each processor, tasks are scheduled according to rate-monotonic. We propose an algorithm that can schedule all task sets that any other possible algorithm can schedule assuming that our algorithm is given processors that are √2 / √2−1 ≈ 3.41 times faster. No such guarantees are previously known for partitioned static-priority scheduling on uniform multiprocessors.

Exact analysis of TDMA with slot skipping

Consider a communication medium shared among a set of computer nodes; these computer nodes issue messages that are requested to be transmitted and they must finish their transmission before their respective deadlines. TDMA/SS is a protocol that solves this problem; it is a specific type of Time Division Multiple Access (TDMA) where a computer node is allowed to skip its time slot and then this time slot can be used by another computer node. We present an algorithm that computes exact queuing times for TDMA/SS in conjunction with Rate-Monotonic (RM) or Earliest- Deadline-First (EDF).

Real-time communications over cluster-tree sensor networks with mobile sink behaviour

Modelling the fundamental performance limits of wireless sensor networks (WSNs) is of paramount importance to understand the behaviour of WSN under worst case conditions and to make the appropriate design choices. In that direction, this paper contributes with a methodology for modelling cluster tree WSNs with a mobile sink. We propose closed form recurrent expressions for computing the worst case end to end delays, buffering and bandwidth requirements across any source-destination path in the cluster tree assuming error free channel. We show how to apply our theoretical results to the specific case of IEEE 802.15.4/ZigBee WSNs. Finally, we demonstrate the validity and analyze the accuracy of our methodology through a comprehensive experimental study, therefore validating the theoretical results through experimentation.

Multiprocessor scheduling with few preemptions

Consider the problem of scheduling a set of periodically arriving tasks on a multiprocessor with the goal of meeting deadlines. Processors are identical and have the same speed. Tasks can be preempted and they can migrate between processors. We propose an algorithm with a utilization bound of 66% and with few preemptions. It can trade a higher utilization bound for more preemption and in doing so it has a utilization bound of 100%.

Dynamic adaptation of stability periods for service level agreements

A QoS adaptation to dynamically changing system conditions that takes into consideration the user’s constraints on the stability of service provisioning is presented. The goal is to allow the system to make QoS adaptation decisions in response to fluctuations in task traffic flow, under the control of the user. We pay special attention to the case where monitoring the stability period and resource load variation of Service Level Agreements for different types of services is used to dynamically adapt future stability periods, according to a feedback control scheme. System’s adaptation behaviour can be configured according to a desired confidence level on future resource usage. The viability of the proposed approach is validated by preliminary experiments.

Implementation of a dominance protocol for wireless medium access

Consider the problem of scheduling sporadic message transmission requests with deadlines. For wired channels, this has been achieved successfully using the CAN bus. For wireless channels, researchers have recently proposed a similar solution; a collision-free medium access control (MAC) protocol that implements static-priority scheduling. Unfortunately no implementation has been reported, yet. We implement and evaluate it to find that the implementation indeed is collision-free and prioritized. This allows us to develop schedulability analysis for the implementation. We measure the response times of messages in our implementation and find that our new response-time analysis indeed offers an upper bound on the response times. This enables a new class of wireless real-time systems with timeliness guarantees for sporadic messages and it opens-up a new research area: schedulability analysis for wireless networks.