Demand response in future power systems management – a conceptual framework and simulation tool

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Global material analysis on phosphorus flows, supply horizon and impact assessment on phosphorus depletion

Different problems are daily discuss on environmental aspects such acid rain, eutrophication, global warming and an others problems. Rarely do we find some discussions about phosphorus problematic. Through the years the phosphorus as been a real problem and must be more discussed. On this thesis was done a global material flow analysis of phosphorus, based on data from the year 2004, the production of phosphate rock in that year was 18.9 million tones, almost this amount it was used as fertilizer on the soil and the plants only can uptake, on average, 20% of the input of fertilizer to grow up, the remainder is lost for the phosphorus soil. In the phosphorus soil there is equilibrium between the phosphorus available to uptake from the plants and the phosphorus associate with other compounds, this equilibrium depends of the kind of soil and is related with the soil pH. A reserve inventory was done and we have 15,000 million tones as reserve, the amount that is economical available. The reserve base is estimated in 47,000 million tones. The major reserves can be found in Morocco and Western Sahara, United Sates, China and South Africa. The reserve estimated in 2009 was 15,000 million tone of phosphate rock or 1,963 million tone of P. If every year the mined phosphate rock is around 22 Mt/yr (phosphorus production on 2008 USGS 2009), and each year the consumption of phosphorus increases because of the food demand, the reserves of phosphate rock will be finished in about 90 years, or maybe even less. About the value/impact assessment was done a qualitative analysis, if on the future we don’t have more phosphate rock to produce fertilizers, it is expected a drop on the crops yields, each depends of the kind of the soil and the impact on the humans feed and animal production will not be a relevant problem. We can recovery phosphorus from different waste streams such as ploughing crop residues back into the soil, Food processing plants and food retailers, Human and animal excreta, Meat and bone meal, Manure fibre, Sewage sludge and wastewater. Some of these examples are developed in the paper.

Need for, demand for, and use of European Union information

The discussion and analysis of the diverse outreach activities in this article provide guidance and suggestions for academic librarians who are interested in outreach and community engagement of any scale and nature. Cases are draw from a wide spectrum and are particularly strong in the setting of large academic libraries, special collections and programming for multicultural populations. The aim of this study is to present the results of research carried out regarding the needs, demand and consumption of European Union information by users in European Documentation Centres (EDC). A quantitative methodology was chosen based on a questionnaire with 24 items. This questionnaire was distributed within the EDC of Salamanca, Spain, and the EDC of Porto, Portugal, during specific time intervals between 2010 and 2011. We examined the level of EU information that EDC users possess, and identified the factors that facilitate or hinder access to EU information, the topics most demanded, and the types of documents consulted. Analysis was made of the use that the consumer of European information makes of databases and their behaviour during the consultation. Although the sample used was not very significant owing to its small size, it is a faithful reflection of the scarce visits made to EDCs. This study can be of use to managers of EDCs, providing them with better knowledge of the information needs and demands of their users. Ultimately this should lead to improvements in the services offered. The study lies within a frame of research scarcely addressed in specialized scholarly literature: European Union information.

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.

A few what-ifs on using statistical analysis of stochastic simulation runs to extract timeliness properties

Modern real-time systems, with a more flexible and adaptive nature, demand approaches for timeliness evaluation based on probabilistic measures of meeting deadlines. In this context, simulation can emerge as an adequate solution to understand and analyze the timing behaviour of actual systems. However, care must be taken with the obtained outputs under the penalty of obtaining results with lack of credibility. Particularly important is to consider that we are more interested in values from the tail of a probability distribution (near worst-case probabilities), instead of deriving confidence on mean values. We approach this subject by considering the random nature of simulation output data. We will start by discussing well known approaches for estimating distributions out of simulation output, and the confidence which can be applied to its mean values. This is the basis for a discussion on the applicability of such approaches to derive confidence on the tail of distributions, where the worst-case is expected to be.

On the adaptation of broadcast transactions in token-passing fieldbus networks with heterogeneous transmission media

Broadcast networks that are characterised by having different physical layers (PhL) demand some kind of traffic adaptation between segments, in order to avoid traffic congestion in linking devices. In many LANs, this problem is solved by the actual linking devices, which use some kind of flow control mechanism that either tell transmitting stations to pause (the transmission) or just discard frames. In this paper, we address the case of token-passing fieldbus networks operating in a broadcast fashion and involving message transactions over heterogeneous (wired or wireless) physical layers. For the addressed case, real-time and reliability requirements demand a different solution to the traffic adaptation problem. Our approach relies on the insertion of an appropriate idle time before a station issuing a request frame. In this way, we guarantee that the linking devices’ queues do not increase in a way that the timeliness properties of the overall system turn out to be unsuitable for the targeted applications.

Privatization and entry of a foreign firm with demand uncertainty

We investigate the effects of trade with a foreign firm and privatization of the domestic pubUc firm on an incentive for the domestic firm to reduce costs by undertaking R&D investment, under demand uncertainty. We suppose that the domestic firm is less efficient than the foreign firm. However, the domestic firm can lower its marginal costs by conducting cost-reducing R&D investment. We examine the impacts of entry of a foreign firm, and the effects of demand uncertainty, on decisions upon cost-reducing R&D investment by the domestic firm and how these affect the domestic welfare.

Innovative manufacturing process for hybrid pultruded products based on cork and polymeric pre-shapes

Pultruded products are being targeted by a growing demand due to its excellent mechanical properties and low chemical reactivity, ensuring a low level of maintenance operations and allowing an easier assembly operation process than equivalent steel bars. In order to improve the mechanical drawing process and solve some acoustic and thermal insulation problems, pultruded pipes of glass fibre reinforced plastics (GFRF) can be filled with special products that increase their performance regarding the issues previously referred. The great challenge of this work was drawing a new equipment able to produce pultruded pipes filled with cork or polymeric pre-shaped bars as a continuous process. The project was carried out successfully and the new equipment was built and integrated in the pultrusion equipment already existing, allowing to obtain news products with higher added-value in the market, covering some needs previously identified in the field of civil construction.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

Modified Particle Swarm Optimization Applied to Integrated Demand Response and DG Resources Scheduling

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

Dynamic load management in a smart home to participate in demand response events

In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heating systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources’ management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.

Virtual Power Player Using Demand Response to Deal with Unexpected Low Wind Power Generation

Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.

Simulated Annealing Approach Applied to the Energy Resource Management Considering Demand Response for Electric Vehicle

The aggregation and management of Distributed Energy Resources (DERs) by an Virtual Power Players (VPP) is an important task in a smart grid context. The Energy Resource Management (ERM) of theses DERs can become a hard and complex optimization problem. The large integration of several DERs, including Electric Vehicles (EVs), may lead to a scenario in which the VPP needs several hours to have a solution for the ERM problem. This is the reason why it is necessary to use metaheuristic methodologies to come up with a good solution with a reasonable amount of time. The presented paper proposes a Simulated Annealing (SA) approach to determine the ERM considering an intensive use of DERs, mainly EVs. In this paper, the possibility to apply Demand Response (DR) programs to the EVs is considered. Moreover, a trip reduce DR program is implemented. The SA methodology is tested on a 32-bus distribution network with 2000 EVs, and the SA results are compared with a deterministic technique and particle swarm optimization results.

Constrained Consumption Shifting Management in the Distributed Energy Resources Scheduling Considering Demand Response

Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.

Demand Response Programs Definition Using Demand Price Elasticity to Define Consumers Aggregation for an Improved Remuneration Structure

The positioning of the consumers in the power systems operation has been changed in the recent years, namely due to the implementation of competitive electricity markets. Demand response is an opportunity for the consumers’ participation in electricity markets. Smart grids can give an important support for the integration of demand response. The methodology proposed in the present paper aims to create an improved demand response program definition and remuneration scheme for aggregated resources. The consumers are aggregated in a certain number of clusters, each one corresponding to a distinct demand response program, according to the economic impact of the resulting remuneration tariff. The knowledge about the consumers is obtained from its demand price elasticity values. The illustrative case study included in the paper is based on a 218 consumers’ scenario.