South Carolina business opportunities

This is a listing, published twice per week, of proposed procurements in construction, information technology, supplies & services as well as other information of interest to the business community.

South Carolina business opportunities

This is a listing, published twice per week, of proposed procurements in construction, information technology, supplies & services as well as other information of interest to the business community.

South Carolina business opportunities

This is a listing, published twice per week, of proposed procurements in construction, information technology, supplies & services as well as other information of interest to the business community.

South Carolina business opportunities

This is a listing, published twice per week, of proposed procurements in construction, information technology, supplies & services as well as other information of interest to the business community.

South Carolina business opportunities

This is a listing, published twice per week, of proposed procurements in construction, information technology, supplies & services as well as other information of interest to the business community.

South Carolina business opportunities

This is a listing, published twice per week, of proposed procurements in construction, information technology, supplies & services as well as other information of interest to the business community.

South Carolina business opportunities

This is a listing, published twice per week, of proposed procurements in construction, information technology, supplies & services as well as other information of interest to the business community.

South Carolina business opportunities

This is a listing, published twice per week, of proposed procurements in construction, information technology, supplies & services as well as other information of interest to the business community.

South Carolina business opportunities

This is a listing, published twice per week, of proposed procurements in construction, information technology, supplies & services as well as other information of interest to the business community.

Validating A knowledge transfer framework in health services

The study of knowledge transfer (KT) has been proceeding in parallel but independently in health services and in business, presenting an opportunity for synergy and sharing. This paper uses a survey of 32 empirical KT studies with their 96 uniquely named determinants of KT success to identify ten unique determinants for horizontal knowledge transfer success. These determinants, the outcome measure of Knowledge Use, and separate explicit and tacit transfer flows constitute the KT Framework, extending the work of previous KT framework authors. Our Framework was validated through a case study of the transfer of clinical practice guideline knowledge between the cardiac teams of selected Ontario hospitals, using a survey of senders and receivers developed from the KT literature. The study findings were: 8 of 10 determinants were supported by the Successful Transfer Hospitals; and 4 of 10 determinants were found to a higher degree in the Successful than non-Successful transfer hospitals. Taken together, the results show substantive support for the KT Framework determinants, indicating aggregate support of 9 of these determinants, but not the 10th - Knowledge Complexity. The transfer of tacit knowledge was found to be related to the transfer of the explicit knowledge and expressed as the transfer or recreation of resource profile and internal process tacit knowledge, where this tacit transfer did not require interactions between Sender and Receiver. This study provides managers with the building blocks to assess and improve the success rates of their knowledge transfers.

Business Models for Cloud Computing: Experiences from Developing Modeling & Simulation as a Service Applications in Industry

The potential of cloud computing is gaining significant interest in Modeling & Simulation (M&S). The underlying concept of using computing power as a utility is very attractive to users that can access state-of-the-art hardware and software without capital investment. Moreover, the cloud computing characteristics of rapid elasticity and the ability to scale up or down according to workload make it very attractive to numerous applications including M&S. Research and development work typically focuses on the implementation of cloud-based systems supporting M&S as a Service (MSaaS). Such systems are typically composed of a supply chain of technology services. How is the payment collected from the end-user and distributed to the stakeholders in the supply chain? We discuss the business aspects of developing a cloud platform for various M&S applications. Business models from the perspectives of the stakeholders involved in providing and using MSaaS and cloud computing are investigated and presented.

ANN based day-ahead ancillary services forecast for electricity market simulation

Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Ancillary services market clearing simulation: a comparison between deterministic and heuristic methods

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tool must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case based on California Independent System Operator (CAISO) data concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.