Unit commitment for systems with significant wind penetration

The stochastic nature of wind alters the unit commitment and dispatch problem. By accounting for this uncertainty when scheduling the system, more robust schedules are produced, which should, on average, reduce expected costs. In this paper, the effects of stochastic wind and load on the unit commitment and dispatch of power systems with high levels of wind power are examined. By comparing the costs, planned operation and performance of the schedules produced, it is shown that stochastic optimization results in less costly, of the order of 0.25%, and better performing schedules than deterministic optimization. The impact of planning the system more frequently to account for updated wind and load forecasts is then examined. More frequent planning means more up to date forecasts are used, which reduces the need for reserve and increases performance of the schedules. It is shown that mid merit and peaking units and the interconnection are the most affected parts of the system where uncertainty of wind is concernedpower generation dispatch; power system economics; stochastic systems; wind power generation

Unit Commitment for Systems With Significant Wind Penetration

The stochastic nature of wind alters the unit commitment and dispatch problem. By accounting for this uncertainty when scheduling the system, more robust schedules are produced, which should, on average, reduce expected costs. In this paper, the effects of stochastic wind and load on the unit commitment and dispatch of power systems with high levels of wind power are examined. By comparing the costs, planned operation and performance of the schedules produced, it is shown that stochastic optimization results in less costly, of the order of 0.25%, and better performing schedules than deterministic optimization. The impact of planning the system more frequently to account for updated wind and load forecasts is then examined. More frequent planning means more up to date forecasts are used, which reduces the need for reserve and increases performance of the schedules. It is shown that mid-merit and peaking units and the interconnection are the most affected parts of the system where uncertainty of wind is concerned.Science Foundation IrelandElectricity Research Centre (ERC) Industry Memberske SB. 26/7/1

Preventative spend: Public Services and Governance

While there is a current emphasis on shifting spend on public services towards prevention, it is increasingly being noted that progress is slow and challenging. This policy briefing looks at: Why is there such as gap between our expectations for prevention policy and the actual result? Rather than providing a "how-to" guide on preventative spend and specific policies, if offers evidence on the common reasons why initiatives do not gain traction and offers a range of possible solutions. Key points: Preventative spend is seen as a key way for governments to use their resources more efficiently and effectively While a lot of emphasis is placed on it as a policy approach, there has been limited success in implementation The concept of preventative spend can be vague and used imprecisely which makes implementation more difficult Shifting resources toward prevention requires difficult political choices that may impact negatively on existing services The evidence base for preventative spend is patchy, and even "gold standard" evidence-based policies may not be replicable in different contexts While preventative spend tends to focus on human services, there is also evidence that, as an approach, it is applicable in a wider range of public service areas

Restricted Size Ramsey Number for Matching versus Tree and Triangle Unicyclic Graphs of Order Six

Let F, G, and H be simple graphs. The graph F arrows (G,H) if for any red-blue coloring on the edge of F, we find either a red-colored graph G or a blue-colored graph H in F. The Ramsey number r(G,H) is the smallest positive integer r such that a complete graph Kr arrows (G,H). The restricted size Ramsey number r∗(G,H) is the smallest positive integer r∗ such that there is a graph F, of order r(G,H) and with the size r∗, satisfying F arrows (G,H). In this paper we give the restricted size Ramsey number for a matching of two edges versus tree and triangle unicyclic graphs of order six