Category Archives: Reliability & Stability

Service reliability and imperviousness to disturbance

Interoperability of Smart Grid (SG) Applications Is Mission-Critical, And Good For Business Too

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Dom Geraghty

 

It is clear to us that energy policy and regulations are the key drivers of the business case for SG applications, and not technologies. These policies/regulations promote, for example, RPS mandates, dynamic pricing, demand response, competitive market structures, self-optimizing customers (e.g., distributed generation and storage, smart appliances, micro-grids), electric vehicles, cyber-security, and data privacy. It is a kind-of “policy-push” market, with SG applications in a “catch-up” mode.

In order to implement the new policies and regulations in all of their complexities and not-designed-for impacts on the traditional electricity grid, while still maintaining the current levels of service reliability, stability and security, the grid needs to be smarter, and react faster. We will be operating “closer to the edge”.

The SG is at its core about automation, control, and optimization across the power system operations – both physical and market operations. For example, it comprises smart sensors, intelligent electronic devices, communications systems, M2M interfaces, data analytics, situation awareness and alerts, and control systems.

In its ideal form, the SG is a system of systems that in essence have the potential to optimize power system operations and capacity requirements. To realize this potential, i.e., for the grid to be “smart”, these systems ultimately need to be interoperable since the SG is an interconnected system from generation all the way to end-use of electricity.

The above new policies/regulations are out ahead of the SG in terms of technology, interoperability, and grid operations – the SG is playing “catch-up”. But more importantly, we also need the SG in order to realize the full benefits of these new policies and regulations.

The “catch-up” situation can lead to unintended/undesirable consequences related to the operation and reliability of the power system.

Fortunately, SG applications have the capability, if not yet the readiness, to mitigate these risks, provided they are interoperable.

The Transition to an “Ideal” SG Architecture Will Be Messy -- We Are Going To Feel Uncomfortable

DSC_1253-150x150As engineers, we like tidiness. In a perfect world, the transition to a fully-functional SG would be orderly and paced to accommodate new applications while protecting grid integrity: perhaps a three-stage transition -- from today’s operations’ data silos in utilities to a single common information bus, then to many common, integrated buses, and finally to a converged system.

But in a non-perfect world, i.e., reality, the SG will evolve as a hybrid of legacy and new systems -- it will not be an optimized process – there will not be a “grand plan” – clusters of interoperability will appear here and there across the SG.

The transition will take perhaps 30 years -- not for technology-based reasons, but because the “refresh cycle” for utility assets is lengthy – so, there’s time for a whole career for all of us in deploying SG applications! Continue reading

A Supply/Demand Curve for “Grid Flexibility” Products – The Price of “Optionality”

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Dom Geraghty

 

Operators of the power system are facing a paradox – on the one hand, the grid is becoming smarter which gives operators an extra “edge” in managing the grid, but, on the other hand, policy changes associated with the promotion of renewable power and customer choice are creating increased uncertainty in both supply and demand. Yet operators must still deliver power with an average service reliability of 3 x 9s (the LOLP or LOEP target in system planning models), while also maintaining short-term stability and security of supply, even as the inertia of the system decreases.

Supply Uncertainty

Increases in supply uncertainties are caused by the steadily increasing penetration of renewable energy production as a result of RPS mandates. Delivery uncertainties are on the rise due to lagging transmission construction leading to congestion.

Demand Uncertainty

Pole w/Wires 150x150Demand uncertainty is increasing as self-optimizing end-users install distributed energy and storage, smart appliances that use M2M controls and chargers for EVs, and take advantage of time-differentiated pricing.

Electricity dispatch is based on minute-to-minute forecasting and clearing of customers’ “net load”. That is, the end-use customer’s load minus any local power generation or discharging of energy storage devices.

But the utility or system operator usually does not have visibility into, or interconnection with, this generation behind the meter – creating demand uncertainty and an inability to take advantage of the distributed generation in reliability emergencies.

Price Volatility and Price Elasticity-Created Uncertainty

The market as structured also creates short-term operational challenges for the grid operators. Prices in wholesale markets can change rapidly over short periods of time, e.g., 15 minutes, leading to sharp changes in the availability of supply and in the level of demand, driven by price elasticity. These impacts of price volatility, combined with the increased percentage of intermittent resources, creates the need for additional fast-acting reserves to maintain the grid operator’s target service reliability level.

Managing Uncertainty

How can the power system operator cope with the increased physical- and market-driven uncertainties?

We suggest that a “least cost” coping approach can consist of a combination of (1) investments in the “smart grid” (smart sensors, advanced controls, data analytics), and (2) investments in flexibility products (to be defined below). Continue reading

Is Service Reliability the Next Business Opportunity?

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Dominic Geraghty

 

As described in our previous dialog, a number of new market factors are stressing utilities’ ability to deliver 3 x 9s reliability.

These factors fall into four categories: (1) new or expanded energy policies and regulations, (2) deployment of SG applications absent reliability-enhancing SG controls, (3) imperfect coordination between electricity market-clearing processes and the physical control processes of the power system, and (4) aging power system infrastructure.

Evolving Energy Policies and Regulations Have the Potential to Negatively Affect Reliability

Utilities dispatch power generation based on a net load forecast, where net load equals the native customer load minus any power generated by (1) a self-optimizing individual customer (e.g., distributed generation or energy storage discharge), (2) an aggregated self-optimizing set of customers, or (3) a micro-grid.

RPS energy policies as well as regulatory policies encouraging DG, EVs, distributed storage, CHP, and micro-grids are having increasingly significant effects on the shape of the net load and on the first derivative of the shape. For example, Mike Niggli, CEO, SDG&E, speaking in Distributech 2013’s plenary session, referred to expected load ramp rates in March 2020 of 4,500 MW down in two hours and 12,500 MW up in two hours, on a 25,000 MW system.

In most cases, the utility does not have visibility into customers’ distributed generation decisions ahead of time. The challenge for the utility is to maintain its target level of service reliability despite the uncertainty associated with the ensuing net load.

IMG_3406 150x150To a certain extent, short-term volatility in the net load caused by intermittent generation (distributed PV) may threaten system stability, especially if aggregated. Some utilities have established rules of thumb for the maximum percentage of PV they will allow on a feeder, e.g., 15%. However, it appears that these rules of thumb/heuristics are overly conservative. One private study simulating a typical distribution system found that its feeders, even in low load situations, could tolerate PV capacity of more than 50% of the load when appropriate (and not too complicated) control equipment is put in place.

To decrease the uncertainty in the net load forecast, and to access additional existing capacity next to the load center that can help maintain reliability in tight supply situations, some utilities offer a “virtual power plant (VPP)” program to their customers. For example, ConEd, PGE, CPS Energy/San Antonio, Duke’s Microgrid Program, AEP, and Europe’s FENIX program offer VPP programs of different types.

In some of these VPP programs, the utility interconnects, maintains, and operates the customer-owned generation/demand reduction applications as a bundle of dispatchable capacity, in return for which the utility provides the customer with certain tariff concessions.

Jurisdictions offering dynamic pricing, e.g., TOU, CPP, and RTP, also create uncertainty in the load forecast. Automated customer price responses can produce large, rapid, swings in the net load. If the consumer’s price response is not automated, i.e., not “smart”, the net load forecast uncertainty can likely be reduced over time based on increasingly accurate (“learned”) estimates of the price elasticity of customer segments -- it helps that price responses will likely be diversified across the service area.

To incentivize an acceptable level of service reliability, state regulators in over 50% of states have mandated penalties for SAIDI or CAIDI performances above a predetermined acceptable range, or have instituted service quality mandates with quantitative metrics. The penalties can be costly -- they provide a strong incentive for utilities to install equipment that improves reliability.

Naturally, these equipment costs are subsequently reflected in customers’ bills. However, the solutions simultaneously improve utility asset utilization and can even prolong the lifetime of some utility assets.

Somewhat Surprisingly, Initial Deployment of SG Applications Can Have a Negative Impact on Reliability

IMG_2597-150x150While SG applications can help enhance reliability through smart sensors and increased automation, it appears that the initial SG applications could negatively impact system reliability before subsequent D.A. applications provide ameliorating automation, i.e., SG can be first a sword against, and later a shield for, reliability.

Here we will address the negative impacts and follow-up below with some business opportunities for SG applications that mitigate these negative effects on reliability. Continue reading

Providing 99.87% Reliability* Is Going to Cost a Lot More – Are There Related SG 2.0 Business Opportunities?

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Dom Geraghty

 

Historically, utilities have provided about “3 x 9s” reliability. The cost of this reliability is currently bundled into the price of electricity. This includes the cost of maintaining reserves, contingency plans, and automated generation control to cover the stochastic behavior of forced outages and electricity demand.

This cost is going up. Why?

Bulk Power Supply Uncertainty Is Affecting Reliability

The implementation of the RPS mandates is increasing the proportion of intermittent power production plants and by default decreasing the inertia, i.e., the damping ability, of the power system. As a result, a substantial amount of extra generation reserves and ancillary services are required to cover the increased uncertainty of supply while maintaining “3 x 9s” reliability levels. Recognizing this, most ISO markets trade various reserve and ancillary service products.

Trans-15-almost-purple-New-Image-150x150The transmission system is becoming more congested and there is widespread resistance against building new transmission lines. As a result, to maintain target levels of reliability and system security, more contingencies and remedial action plans and systems are needed to cover the increased uncertainty of delivery capability. Recognizing this, the ERCOT wholesale market trades month-ahead “congestion revenue right” products.

Real-World Examples of Related Supply-Side Reliability Events

A recent article by Dr. Paul-Frederik Bach, an expert in power system operations, discusses the impact of renewables penetration on the German power Grid. “The number of interventions has increased dramatically from 2010-2011 to 2011-2012…….

Bottlenecks are often detected in local grids. It makes no difference to the owner of a wind turbine if local or national grids are congested…………..In an attempt to establish an impression of the extent of interventions in Germany, EON Netz will be used as an example………..

During the first quarter of 2012, EON Netz has issued 257 interventions. The average length was 5.7 hours. Up to 10 interventions have been issued for the same hour. A total of 504 hours had one or more interventions. Thus, there have been interventions active for 23.1 percent of the hours during the first quarter of 2012..........

The total amount of curtailed energy from wind and CHP is probably modest, but the observations seem to indicate that German grids are frequently loaded to the capacity limits. Strained grids have a higher risk of cascading outages caused by single events.”

Another informative and very detailed analysis of a widespread outage in Europe in 2006 -- one which overloaded power lines and transformers in Poland by 120% and 140%, respectively -- can be found here. It includes a very interesting map of the European interconnected system showing voltage phase angle differences between substations varying from +60° to -50° across the region.

Demand-Side Uncertainty Is Also Affecting Reliability

Limited band-width, short-term frequency and voltage control is provided by traditional power plants.

However, the power industry does not have closed loop control between demand and supply. Continue reading